World Bank East Asia and Pacific Economic Update, April 2019

WORLD BANK EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

MANAGING HEADWINDS

WORLD BANK EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Managing Headwinds

© 2019 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW, Washington, DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some rights reserved 1 2 3 4 22 21 20 19 This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Nothing herein shall constitute or be considered to be a limitation upon or waiver of the privileges and immunities of The World Bank, all of which are specifically reserved. Rights and Permissions

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MANAGING HEADWINDS

Contents List of Abbreviations

xii

Preface and Acknowledgments

xv

Executive Summary Part I. Recent Developments and Outlook

xvii 1

I.A. Recent Developments 2 Global headwinds contributed to softening growth momentum in the region 2 Trade momentum eased significantly in 2018 10 Robust domestic demand supported growth outcomes in 2018 15 Inflationary pressures were subdued in the larger regional economies and elevated in the smaller economies 16 Financial markets recovered in early 2019 after significant volatility during 2018 17 The approach to fiscal policy was mixed 22 Recent developments in the Pacific Island Countries 23 Resilient domestic demand supported poverty reduction in the region 24 I.B. Outlook and Risks Regional growth is expected to moderate slightly in 2019 Robust domestic demand is expected to continue to support poverty reduction in the region Risks to the outlook remain firmly tilted to the downside and in some cases have intensified

28 28 32 33

1.C. Policy Considerations Policy considerations in the short term will need to address increasing global headwinds Moderating global economic activity heightens the urgency associated with undertaking medium-term structural reforms Rebalancing China’s growth model will present challenges and opportunities for the region Enhance social protection measures that protect the poor

43 43

Part I References

55

Part II. Medium-Term Development Agenda

46 50 54

59

II.A. Piecing Together the Poverty Puzzle in Developing East Asia and Pacific 60 Broader measures of poverty are important 60 Higher standards fit for a growing region 62 Non-monetary measures are important to tackle poverty in all its forms 64 Conclusion 74

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Contents continued II.B. Tackling the Food Safety Challenges of Middle-Income East Asia and Pacific The region is devoting increased attention and resources to improving food safety The economic costs of safe food take multiple forms and have both short-and long-term dimensions The way forward

76 76 78 86

Part II References

89

Part III. Country Summaries and Key Indicators 91 Cambodia 92 Central Pacific Islands 95 China 98 Fiji 101 Indonesia 104 Lao PDR 107 Malaysia 110 Mongolia 113 Myanmar 116 North Pacific Islands 119 Papua New Guinea 122 Philippines 125 Solomon Islands 128 South Pacific Islands 131 Thailand 134 Timor-Leste 137 Vietnam 140

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List of Figures Part I. Recent Developments and Outlook I.A. Recent Developments Figure I.A.1. Growth in developing East Asia and Pacific moderated in 2018 Figure I.A.2. Manufacturing activity softened in most major regional economies Figure I.A.3. Monthly indicators hint at recovering momentum in China Figure I.A.4. Growth softened in region’s largest economies Figure I.A.5. Growth was solid in most of the region’s smaller economies Figure I.A.6. Export value growth deteriorated in line with a moderation in global trade… Figure I.A.7…as did export volume growth Figure I.A.8. Overall imports growth remained resilient despite weak Q4 outcomes Figure I.A.9. China's imports from major ASEAN economies remain subdued Figure I.A.10. Current account balances deteriorated slightly in 2018 Figure I.A.11. Strong domestic demand supported growth in 2018 Figure I.A.12. Inflationary pressures have eased markedly in major economies… Figure I.A.13. …but remain elevated in some smaller regional economies Figure I.A.14. Growth in producer prices fell sharply at the end of 2018 Figure I.A.15. Inflation remained below target in the region’s major economies Figure I.A.16. Major currencies regained lost ground at the end of 2018 Figure I.A.17. Following a period of corrections, stock markets have begun to recover Figure I.A.18. Uncertainty triggered stock market volatility in 2018 Figure I.A.19. External corporate and sovereign bond spreads widened in 2018 Figure I.A.20. International reserves supported interventions in foreign exchange markets Figure I.A.21. The region witnessed declining net FDI inflows in 2018 Figure I.A.22. Net portfolio flows declined in 2018 Figure I.A.23. Credit growth outcomes were mixed Figure I.A.24. Fiscal policy stances varied Figure I.A.25. Poverty has continued to decline across the region Figure I.A.26. Wage growth was strong across the majority of large economies

2 2 6 9 9 10 10 11 11 11 16 17 17 17 17 18 18 18 21 21 21 21 22 23 24 25

I.B. Outlook and Risks Figure I.B.1. Domestic demand will continue to drive growth over the forecast period Figure I.B.2. Fiscal deficits are expected to remain at similar levels to the recent past Figure I.B.3. Government debt is expected to remain contained Figure I.B.4. Total debt levels are reasonably contained

32 41 41 41

1.C. Policy Considerations Figure I.C.1. Government expenditure by type of social spending

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List of Figures continued

Part II. Medium-Term Development Agenda II.A. Piecing Together the Poverty Puzzle in Developing East Asia and Pacific Figure II.A.1. Distribution of the population in developing East Asia and Pacific by consumption per capita, 2018 62 Figure II.A.2. Number of poor by poverty line – selected countries 62 Figure II.A.3. Developing East Asia and Pacific poverty rates, by poverty line, 2002 and 2018 63 Figure II.A.4. Countries with similar levels of GNI per capita can have very different poverty lines 64 Figure II.A.5. Multi-dimensional poverty in 13 East Asia and Pacific countries vs 119 economies worldwide 67 Figure II.A.6. Deprivations in non-monetary dimensions – selected East Asia and Pacific countries 68 Figure II.A.7. Deprivations in non-monetary dimensions are higher in rural areas 68 Figure II.A.8. Non-monetary deprivations vary within countries 69 Figure II.A.9. The headcount rate, by alternative poverty measures, Indonesia 70 II.B. Tackling the Food Safety Challenges of Middle-Income East Asia and Pacific Figure II.B.1. Food safety lifecycle: Relating the burden of unsafe food to levels of economic development 78 Figure II.B.2. E stimated ‘productivity loss’ due to foodborne disease, 2016 80 Figure II.B.3. T he relative economic cost of unsafe food: FBD 'productivity losses'/total food expenditures 80 Figure II.B.4. D eveloping East Asia and Pacific exports of high value foods 82 Figure II.B.5. C apacity and need for capacity for food safety systems for animal sourced foods 84 Part III. Country Summaries and Key Indicators

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Cambodia Figure 1. Real GDP growth, contribution to real growth Figure 2. Garment and footwear exports

94 94

Central Pacific Islands Figure 1. Sources of domestic revenue - projections to 2020 Figure 2. Sovereign wealth fund balances - projections to 2020

97 97

China Figure 1. Real GDP growth, contribution to real growth Figure 2. Poverty estimates and projections

100 100

Fiji Figure 1. Real GDP growth and total investment Figure 2. Fiscal balance and public debt

103 103

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List of Figures continued Indonesia Figure 1. Real GDP growth, contribution to real growth Figure 2. Poverty rate, actual and projected

106 106

Lao PDR Figure 1. Real GDP growth, contribution to real growth Figure 2. Actual and projected poverty rates and real GDP per capita

109 109

Malaysia Figure 1. Real GDP growth, contribution to real growth Figure 2. Actual and projected poverty rates and real private consumption per capita

112 112

Mongolia Figure 1. Real GDP growth, contribution to real growth Figure 2. Poverty rate (official poverty line): 2010–16

115 115

Myanmar Figure 1. Real GDP growth, contribution to real growth Figure 2. Actual and projected poverty rates and real GDP per capita

118 118

North Pacific Islands Figure 1. Former sector employment Figure 2. Overall fiscal balance

121 121

Papua New Guinea Figure 1. Real GDP growth, contribution to real growth Figure 2. Key fiscal and debt indicators

124 124

Philippines Figure 1. Real GDP growth, contribution to real growth Figure 2. Actual and projected poverty rates, 2006–21

127 127

Solomon Islands Figure 1. Real GDP per capita Figure 2. Trade balance

130 130

South Pacific Islands Figure 1. Incidence of poverty at international poverty lines and national hardship thresholds Figure 2. Public and publicly guaranteed external debt

133 133

Thailand Figure 1. Real GDP growth, contribution to real growth Figure 2. Employment growth and unemployment rate

136 136

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List of Figures continued

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Timor-Leste Figure 1. Real GDP growth, contribution to real growth Figure 2. Fiscal aggregates

139 139

Vietnam Figure 1. Real GDP growth, contribution to real growth Figure 2. Actual and projected poverty rates and real GDP per capita

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List of Tables Part I. Recent Developments and Outlook I.B. Outlook and Risks Table I.B.1. EAP economic outlook Table I.B.2. Poverty in developing East Asia and Pacific is projected to continue falling

31 32

Part II. Medium-Term Development Agenda II.B. Tackling the Food Safety Challenges of Middle-Income East Asia and Pacific Table II.B.1. Comparative public health burden: Disability adjusted life years lost per 100,000 people Table II.B.2. Comparative rejection rates for high value foods entering the EU (2014–16) Part III. Country Summaries and Key Indicators Cambodia Selected Indicators Central Pacific Islands Selected Indicators China Selected Indicators Fiji Selected Indicators Indonesia S elected Indicators Lao PDR Selected Indicators Malaysia Selected Indicators Mongolia Selected Indicators Myanmar Selected Indicators North Pacific Islands Selected Indicators Papua New Guinea S elected Indicators Philippines S elected Indicators Solomon Islands Selected Indicators South Pacific Islands Selected Indicators Thailand Selected Indicators Timor-Leste S elected Indicators Vietnam Selected Indicators

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94 97 100 103 106 109 112 115 118 121 124 127 130 133 136 139 142

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List of Boxes Part I. Recent Developments and Outlook I.A. Recent Developments Box I.A.1. Recent Global Developments Figure BI.A.1.1. Global economic growth rates, 2010–18 Figure BI.A.1.2. Global economic policy uncertainty Figure BI.A.1.3. Regional economic growth rates, 2012–18 Figure BI.A.1.4. Global trade growth Figure BI.A.1.5. Commodity price indices Box I.A.2. How big data can improve our understanding of macroeconomic trends in East Asia and Pacific Figure BI.A.2.1. A news-based sentiment index can act as a leading indicator for growth… Figure BI.A.2.2. …resulting in reduced forecast errors compared with consensus projections Box I.A.3. Do robots threaten trade between the OECD and East Asia and Pacific countries? Figure BI.A.3.1. Drivers of robot adoption Figure BI.A.3.2. Estimated impact of OECD automation on exports to, and imports from, East Asia and Pacific countries Figure BI.A.3.3. Effects of robot price reductions on robot use, labor allocation, wages and welfare Box I.A.4. The costs of trade tensions for East Asian financial markets Figure BI.A.4.1. Which country group suffers more because of the "trade war"? Figure BI.A.4.2. Which stock market index suffers more because of the “trade war”? Table BI.A.4.1. Cumulative impact of protectionist announcements: the stock market perspective Box I.A.5. Subnational monetary poverty in developing East Asia and Pacific Figure BI.A.5.1. Subnational poverty map, LMIC poverty line ($3.2/day 2011 PPP)

3 3 3 4 4 4 6 7 8 12 13 14 15 19 19 19 20 25 26

I.B. Outlook and Risks Box I.B.1. Global Outlook and Risks 28 Figure BI.B.1.1. Aggregate GDP growth rates, estimated and projected 29 Figure BI.B.1.2. Regional GDP growth rates, estimated and projected 29 Figure BI.B.1.3. World commodity price forecasts 29 Box I.B.2. P ropagation of macroeconomic shocks through input-output and geographic networks in China 34 Figure BI.B.2.1. Network effects 34 Figure BI.B.2.2. Regional network effects 35 Figure BI.B.2.3. Network effects and the economy 36 Box I.B.3. D o U.S. import tariffs on Chinese goods have bite? Preliminary estimates of the effects on U.S. imports 37 Table BI.B.3.1. Value of U.S. imports from China targeted by tariff measures 37 Table BI.B.3.2. Estimated effects of U.S. tariffs on U.S. imports from China and overall ($ million) 38 Figure BI.B.3.1. Short-run elasticity of U.S. tariffs on Chinese goods on U.S. imports from Southeast Asia 39

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List of Boxes continued 1.C. Policy Considerations Box I.C.1. Debt in the Pacific Island Countries Figure BI.C.1.1. Debt-to-GDP ratio for selected Pacific Island Countries Figure BI.C.1.2. Economic growth in the Pacific: History and projections Box I.C.2. The unfinished agenda for investing in East Asia and the Pacific’s people Table BI.C.2.1. The Human Capital Index – a global overview Figure BI.C.2.1. The learning gap Box I.C.3. Fiscal spending to support growth in China Figure BI.C.3.1. General government investment, 2011–15 average Figure BI.C.3.2. Capital output ratio by sector Figure BI.C.3.3. Selected general government expenditures Figure BI.C.3.4. Public spending on health by province, 2016 Figure BI.C.3.5. Public spending on education by province, 2015

44 44 44 47 48 48 51 51 51 52 52 52

Part II. Medium-Term Development Agenda II.A. Piecing Together the Poverty Puzzle in Developing East Asia and Pacific Box II.A.1. Beyond the twin goals – Higher poverty lines 61 Table BII.A.1.1. National poverty lines, circa 2011 62 Box II.A.2. Why look beyond monetary poverty? 65 Box II.A.3. Beyond the twin goals - Multidimensional poverty measure 66 Table BII.A.3.1. Dimensions of well-being and indicators of deprivation 66 Box II.A.4. Multidimensional welfare in Myanmar 71 Figure BII.A.4.1. Percentage of individuals experiencing multiple disadvantages (number of indicators) 71 Figure BII.A.4.2. Multidimensial Index at state/region and township level 73

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List of Abbreviations AML/CFT APEC ARMM bbl BI BMI CBM CPI DALY DPT3 EAPTSD EBA ECB EMDEs EU FAO FBD FCV FDI FERG FX FY GDP GNI GSP GVCs HCI IFC IFR IMF IPL LGFV LMIC LMICs LNG MDI

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Anti-Money Laundering and Combating the Financing of Terrorism Asia-Pacific Economic Cooperation Autonomous in Muslim Mindanao per barrel Bank Indonesia Body mass index Central Bank of Myanmar Consumer Price Index disability-adjusted life years diphtheria-pertussis-tetanus vaccine East Asia and Pacific Team for Statistical Development Everything But Arms European Central Bank emerging market and developing economies European Union The Food and Agriculture Organization of the United Nations foodborne disease fragile, conflict and violence foreign direct investment The World Health Organization’s Foodborne Disease Burden Epidemiology Reference Group foreign exchange fiscal year gross domestic product gross national income Generalized System of Preferences global value chains Human Capital Index International Finance Corporation International Federation of Robotics International Monetary Fund International Poverty Line local government financing vehicles lower-middle-income class low and middle income countries liquified natural gas Multidimensional Disadvantage Index

MPI MPM MTDP NAFTA NBS NDP OECD OIE PVS OJK OPEC PBOC PICs PMI PPP PVS Q1 Q2 Q3 Q4 REER RPC SAAR SAR SBV SME SOE TVET UMIC UNCTAD UNDP UNIDO USTR VAT WTO y/y

Multidimensional Poverty Index multi-dimensional poverty measure Medium-Term Development Plan The North American Free Trade Agreement Chinese National Bureau of Statistics National Development Plan Organisation for Economic Co-operation and Development OIE Tool for the Evaluation of Performance of Veterinary Service Indonesian Financial Services Authority Organization of the Petroleum Exporting Countries People’s Bank of China Pacific Island Countries Purchasing Managers’ Index purchasing power parity performance of veterinary services first quarter second quarter third quarter fourth quarter real effective exchange rate Regional Processing Centre seasonally adjusted annual rate Special Administrative Region The State Bank of Vietnam small and medium-sized enterprise state-owned enterprise training and vocational education upper-middle-income class The United Nations Conference on Trade and Development United Nations Development Programme The United Nations Industrial Development Organization United States Trade Representative Value Added Tax World Trade Organization year-over-year

List of Abbreviations

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List of Abbreviations continued

Regions, World Bank Classification and Country Groups

ASEAN EAP ECA

Association of Southeast Asian Nations East Asia and Pacific Eastern Europe and Central Asia

Country Abbreviations

ARG AUS AZE BDI BGD BGR BIH BLR BOL BRA BRN CAN CHN CIV COD COL CRI CYM DEU DZA ECU EGY ETH FJI FSM GBR GEO GHA GTM HKG HND IDN IND IRN JAM

Argentina Australia Azerbaijan Burundi Bangladesh Bulgaria Bosnia-Herzegovina Belarus Bolivia Brazil Brunei Darussalam Canada China Côte d'Ivoire Congo, DRC Colombia Costa Rica Cayman Islands Germany Algeria Ecuador Egypt Ethiopia Fiji Federated States of Micronesia United Kingdom Georgia Ghana Guatemala Hong Kong SAR, China Honduras Indonesia India Iran Jamaica

List of Abbreviations

LAC MENA PICs SAR SSA

Latin America and the Caribbean Middle East and North Africa Pacific Island Countries South Asia Sub-Saharan Africa

JOR JPN KAZ KEN KHM KIR KOR LAO LKA LSO MAR MEX MHL MKD MMR MNG MRT MWI MYS NER NGA NPL NRU PAK PER PHL PLW PNG RCB RMI ROU RUS SDN SEN SGP SLB SLV

Jordan Japan Kazakhstan Kenya Cambodia Kiribati Republic of Korea Lao People’s Democratic Republic Sri Lanka Lesotho Morocco Mexico Marshall Islands Macedonia Myanmar Mongolia Mauritania Malawi Malaysia Niger Nigeria Nepal Nauru Pakistan Peru Philippines Palau Papua New Guinea Congo, Republic Republic of the Marshall Islands Romania Russia Sudan Senegal Singapore Solomon Islands El Salvador

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List of Abbreviations continued

SRB TCD THA TKM TLS TON TUN TUR

Serbia Chad Thailand Turkmenistan Timor-Leste Tonga Tunisia Turkey

Currency Units

A $NZ B CR D F$ K K

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Australian dollar New Zealand dollar Thai baht Cambodian riel Vietnamese dong Fiji dollar Myanmar kyat Papua New Guinea kina

TUV UKR USA UZB VNM VUT WSM ZAF

Tuvalu Ukraine United States Uzbekistan Vietnam Vanuatu Samoa South Africa

Kip P RM RMB Rp SI$ Tog US$ US$

Lao kip Philippine peso Malaysian ringgit Chinese renminbi Indonesian rupiah Solomon Islands dollar Mongolian turhrik Timor-Leste (U.S. dollar) United States dollar

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Preface and Acknowledgments The East Asia and Pacific Economic Update is a joint product of the World Bank office of the Chief Economist, East Asia and Pacific Region, and the Macroeconomics, Trade and Investment Global Practice, prepared in collaboration with the Poverty and Equity Global Practice, Prospects Group, and the Finance and Markets Global Practice. The report was prepared by Ergys Islamaj (Co-Task Team Leader) and Dhruv Sharma (Co-Task Team Leader), under the guidance of Andrew Mason (Acting Chief Economist, East Asia and Pacific Region). Ndiame Diop, Deepak Mishra and Salman Zaidi provided valuable advice to the team. Chapter I was prepared by Dhruv Sharma (lead), Ergys Islamaj, Vera Kehayova, Ekaterine Vashakmadze, and Judy Yang. Contributions were received from the Chapter III team (listed below), as well as Erhan Artuc, Ana Maria Aviles, Paulo Bastos, Massimiliano CalĂŹ, Luc Christiaensen, Leslie K. Elder, Samuel Fraiberger, Amer Hasan, Martin Kessler, Elitza Mileva, Keita Miyaki, Trevor Monroe, Ha Nguyen, Francesca de Nicola, Richard Record, Bob Rijkers, Hazmi Ash Shidqi, Diego Sourrouille, Radu Tatucu, Robert Utz, Shiyao Wang, Hernan Winkler, Jinxin Wu, and Luan Zhao. Chapter II was prepared by Judy Yang (Chapter II.A) and Steven M. Jaffee (Chapter II.B). Chapter III was prepared by staff from the Macroeconomics, Trade and Investment Global Practice and the Poverty and Equity Global Practice: Kiatipong Ariyapruchya, Mahama Samir Bandaogo, Davaadalai Batsuuri, Hans Beck, Andrew Blackman, Derek Hung Chiat Chen, Yew Keat Chong, Kevin Chua, Olga Da Conceicao, Souleymane Coulibaly, Kevin Cruz, Francis Addeah Darko, Somneuk Davading, Georgia Demarchi, Gabriel Demombynes, Reno Dewina, Viet Tuan Dinh, Sebastian Eckardt, Kim Alan Edwards, Birgit Hansl, Kristen Himelein, Taufik Ramadhan Indrakesuma, Demet Kaya, Annette De Kleine, Chandana Kularatne, John Litwack, Wei Loh, Xubei Luo, Sodeth Ly, Miguel Eduardo Sanchez Martin, Pedro Miguel Gaspar Martins, Elitza Mileva, Thi Da Myint, Darian Naidoo, Arvind Nair, Jean-Pascal Nguessa Nganou, Clarence Tsimpo Nkengne, Keomanivone Phimmahasay, Obert Pimhidzai, Sharon Faye Alariao Piza, Ririn Purnamasari, Rong Qian, Richard Record, Alief Aulia Rezza, Anna Robinson, Carlos Orton Romero, Frederico Gil Sander, Ilyas Sarsenov, Dhruv Sharma, Altantsetseg Shiilegmaa, Kenneth Simler, Sailesh Tiwari, Kimsun Tong, Ikuko Uochi, Shiyao Wang, Judy Yang, and Luan Zhao. The work was managed by Ndiame Diop and Deepak Mishra for the Macroeconomics, Trade and Investment Global Practice, and by Salman Zaidi for the Poverty and Equity Global Practice. Thi Thanh Thanh Bui, Kristina Catherine Tan Mercado, and David Andrew Stephan, made substantive contributions to the model, table production and assisting staff with their forecasts. Angkanee Luangpenthong, Yulita Sari Soepardjo and Ivana Ticha provided technical support. Assistance with communications and outreach was provided by Marcela Sanchez-Bender, LĂ­via Pontes and Alejandro Cedeno Ulloa (External Communications, East Asia and Pacific Region). The report was edited by Peter Milne, William Shaw and Diane Stamm, and designed and typeset by Budy Wirasmo. Administrative support was provided by Cecile Wodon.

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Preface continued

Throughout the report, geographic groupings are defined as follows: Developing East Asia and Pacific comprises Cambodia, China, Indonesia, Lao People’s Democratic Republic (PDR), Malaysia, Mongolia, Myanmar, Papua New Guinea, the Philippines, Thailand, Timor-Leste, Vietnam, and the Pacific Island Countries. The Pacific Island Countries comprise Fiji, Kiribati, Republic of the Marshall Islands, the Federated States of Micronesia, Palau, Samoa, the Solomon Islands, Tonga, Tuvalu, and Vanuatu. The ASEAN member countries comprise Brunei Darussalam, Cambodia, Indonesia, Lao PDR, Malaysia, Myanmar, the Philippines, Singapore, Thailand, and Vietnam. The ASEAN-5 comprise Indonesia, Malaysia, the Philippines, Thailand, and Vietnam. This report is based on data available through April 17, 2019, inclusive.

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Executive Summary Growth in the developing East Asia and Pacific region slowed to 6.3 percent in 2018 in line with earlier forecasts. This slowdown largely reflected a structural moderation in China and more challenging external conditions. Output in the rest of the region grew by 5.2 percent in 2018—slightly weaker than the forecast in the last edition of this Update. The recovery in trade and manufacturing activity observed in the first half of 2018 lost momentum but domestic demand has remained resilient in much of the region, partly offsetting the impact of slowing exports. The recent slowdown notwithstanding, the developing East Asia and Pacific region remains a key driver of the global economy, accounting for around one-third of global growth, mainly due to China. The region’s economies faced less favorable external conditions in 2018. Countries experienced weakening global demand, heightened trade tensions, and a substantial tightening of financing conditions. Global growth eased in 2018 with global manufacturing activity decelerating sharply in the fourth quarter. Among the advanced economies, growth in the United States picked up in 2018, bolstered by fiscal stimulus measures, but activity slowed toward the end of the year. Euro Area growth decelerated notably in 2018, reflecting weak external demand. The deterioration in global economic conditions manifested itself in weaker demand for exports and financial market volatility. Macro-financial assets, such as currencies, bonds, and equities, all suffered losses in 2018 on the back of financial market turbulence caused primarily by monetary policy normalization in the United States and risks of contagion stemming from currency crises in Argentina and Turkey. Growth in developing East Asia and Pacific has been resilient to the challenging headwinds stemming from the external environment. Several large economies in the region have faced some combination of capital outflows, currency depreciation, equity market corrections, and foreign reserve losses. But, overall, the region has coped relatively well with the bouts of financial volatility, largely due to effective policy frameworks and strong fundamentals, including diversified economies, flexible exchange rates, and solid policy buffers. Global conditions remain challenging in 2019. Global growth is projected to slow to 2.7 percent in 2019, reflecting decelerating activity in advanced economies and in many large emerging market and developing economies. Global trade has weakened further amid slowing global investment and manufacturing activity. While trade policy uncertainty has abated somewhat, global trade growth is expected to moderate further. As growth prospects have softened, the tightening pace of international financing conditions has eased, providing some respite to countries with large external financing needs. Growth in developing East Asia and Pacific is projected to slow to 6.0 percent in 2019 and 2020. This largely reflects a continued gradual policy-guided slowdown in China to 6.2 percent in 2019 and 2020, down from 6.6 percent in 2018. Growth in the large ASEAN countries is projected to remain broadly stable, supported by resilient domestic demand. Growth in Indonesia and Malaysia is projected to remain unchanged in 2019, while growth rates in Thailand and Vietnam are expected to be slightly lower in 2019. In the Philippines, while growth is expected to accelerate compared to 2018, the delay in approving the 2019 national government budget and the ban on construction of public works during the election period is expected to weigh on GDP growth in 2019.

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Growth prospects among the smaller economies in the region remain favorable. Large infrastructure projects are expected to drive an acceleration in growth for Lao PDR and Mongolia. Cambodia’s growth is projected to remain robust over the forecast horizon, although at a slower pace than in 2018, mainly due to weaker-than-expected external demand. Expansionary fiscal policy in the lead-up to elections in 2020 is expected to boost growth in Myanmar in the short term, while recent structural reforms are expected to support growth in the medium term. Growth is expected to pick up in Papua New Guinea in 2019 as the economy recovers from a catastrophic earthquake in 2018. Growth in Fiji is projected to continue to rise, albeit at a more tempered pace as reconstruction efforts near completion in the aftermath of tropical cyclones. Growth in the Pacific Island countries is expected to be supported by major infrastructure investments and construction projects. Poverty in the region is expected to decline further supported by resilient growth. Extreme poverty (based on the number of people living under the international poverty line of $1.90/day in 2011 PPP terms) in the region is now at historical lows and concentrated in a few countries—Lao PDR, Papua New Guinea, and Timor-Leste—as well as in remote locations in more affluent countries. A further reduction in extreme poverty is expected over the next few years, with the poverty rate projected to dip below 3 percent by 2021. A staggering half a billion people in the region remain economically insecure as of 2018, however, based on a higher poverty threshold ($5.50/day in 2011 PPP terms). While this number is projected to decline by one-fifth by 2021, it serves as a reminder of the scale of the challenges facing policymakers. Risks to the outlook remain firmly tilted to the downside, with the biggest risk stemming from a further deceleration of activity in major economies. There is considerable uncertainty around the outlook for the global economy, especially with ongoing indications that global demand is softening. Around 80 percent of advanced economies are expected to register slowing growth in 2019. In the Euro Area, this risk has risen alongside significant growth disappointments since mid-2018. These developments could have broad-ranging repercussions for countries in developing East Asia and Pacific. Although unlikely in the near term, the simultaneous occurrence of sharper-thanexpected slowdowns in China, the Euro Area, and the United States—which together account for 50 percent of global GDP—could trigger a significant downturn in overall global activity. While most of the East Asia and Pacific region managed to weather the deterioration of external conditions in 2018, the risk of conditions worsening would place additional pressure on policymakers despite most countries having reasonably sound economic fundamentals and robust domestic demand. A faster-than-expected moderation in growth in China would pose significant risks to the region. Slower-thanexpected growth in China, alone, would lead to spillovers to other regional economies. Estimates suggest that a 1percentage-point slowdown in China’s growth could reduce growth in other developing countries in the region by around 0.5 of a percentage point, on average, in the next two years. Some of the smaller economies remain highly exposed to China through commodity exports (Mongolia, Papua New Guinea, and the Solomon Islands) or through tourism and FDI linkages (Cambodia and Palau). Unresolved trade tensions and the possibility of new ones arising are another source of risk. While the United States and China appear to be getting closer to resolving trade disputes, uncertainty around trade in the region remains high, with signs of changes in the within-region landscape of trade and financial flows. At the same time, talk of traderelated concerns between the United States and other countries over the past few months may weigh on confidence in the global arena and in the region. The United States has announced the removal of India and Turkey from its Generalized

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Executive Summary

MANAGING HEADWINDS

System of Preferences agreement, which provides exemptions from tariffs on goods exported to the United States. The risks to the region’s economies (other than China) stem from their relatively high level of integration in regional and global value chains. Additional trade tensions and any re-escalation of trade tensions between the United States and China could also be highly disruptive to global activity given the presence of complex value chains. Finally, the East Asia and Pacific region remains vulnerable to risks posed by disorderly financial market developments. Renewed episodes of substantial financial market stress could have pronounced and widespread effects. A surge in safe-haven demand among investors over the past month has not yet led to a reversal in yields in developing East Asia and Pacific but, given the region’s historical vulnerability to sudden reversals in capital flows, any sustained market pessimism could pose challenges for several regional economies. Increased headwinds that are weighing on regional growth will need to be managed actively. In the context of moderating global growth and faltering trade momentum, the priority for the region’s countries will be to ensure a growth pattern that is sustainable and supported by macroeconomic fundamentals to buffer against future disruptions in the global economy. As such, countries will need to focus in the short term on managing global headwinds by strengthening depleted buffers, including rebuilding international reserves that were drawn upon to manage exchange rate volatility in 2018. Monetary policy may also need to be adjusted to become more neutral as risks of capital outflows have abated. In the medium-term, a renewed focus on structural reforms in the context of changing global economic forces, and efforts to raise investment and boost human capital, will be needed. Addressing significant capital gaps—both physical and human—will be critical to ensuring sustainable growth in the medium term. Investing in human assets is particularly important in developing East Asia and Pacific given the prevalence of relatively high stunting rates. Stunting rates (for children under the age of five) in Cambodia, Indonesia, Myanmar, are close to 30 percent and in Vietnam the rate is 25 percent. Stunting can result in lower productivity, lower lifetime earnings, lost job opportunities, and lower potential economic growth. Investing in human capital, beginning with adequate nutrition in the first 1,000 days of a child’s life, is critical in ensuring the high learning outcomes required for the region to continue its transition toward higher-income status. Improving private sector opportunities will play an important role in ensuring a more sustainable growth pattern. Pressure to improve the business environment is particularly acute given that the significant currency depreciations seen throughout the region in 2018 do not appear to have provided much of a competitiveness boost to exports. A developing policy challenge for the region’s governments will be to reverse the ongoing productivity slowdown and boost competitiveness. Governments in the region will need to maintain their commitment to the openness that has served their countries well in the recent past, despite temptations to lean toward protectionism in the current global climate. A policy focus on reforming the services sector—which remains very restricted compared with the goods sectors—will be essential to capitalize on the new opportunities that trade in services and technological developments offer. A key dimension to renew the growth prospects of the region is fostering more innovation. To take full advantage of the benefits from innovation, policy makers need to adopt a more comprehensive view of innovation that supports accumulation of knowledge and other forms of capital, fostering firms' capabilities and appropriate incentives to innovate, facilitating the transfer of knowledge between universities/public research institutions and industry, and strengthening government capabilities to formulate and implement adequate and effective innovation policies.

Executive Summary

xix

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

The rebalancing of China’s growth model will present challenges and opportunities for the region. Reduced demand for some exports could create challenges for policymakers in the rest of the region. China’s rebalancing could also create opportunities, however. For example, there could be an increase in China’s demand for imports for domestic consumption, relative to its demand for imported inputs into processing trade. This could mean higher demand for final goods and a different mix of intermediate imports. As China moves up regional and global value chains, new opportunities will also potentially be available for those countries that have a conducive domestic business environment. The intensification of some risks also underscores the need to continue to strengthen social assistance and insurance programs to increase resilience to systemic shocks. To increase resilience to shocks and promote greater economic security, governments in the region can focus on strengthening social insurance and assistance programs. Indeed, an important aim for policy makers is not only to reduce poverty but also to help protect households from falling back into poverty or experiencing significant income losses in case of shocks. At present, developing East Asia and Pacific stands out as the region with the lowest benefit incidence of social assistance among the poorest 20 percent of the population. Pacific Island Countries need to focus on maintaining debt sustainability. Despite relatively low levels of public debt as a share of GDP, the majority of Pacific Island Countries (PICs) are rated as being at high risk of debt distress. These high debt distress ratings are due to structural factors, including modest long-term economic growth prospects, high vulnerability to natural disasters, high infrastructure and public services costs, and limited public sector capacity. Given the low debt capacity in Pacific Island economies, continued efforts to strengthen debt management, improve quality of spending, and build fiscal space will be crucial to improve debt sustainability.

xx

Executive Summary

WORLD BANK EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Part I. Recent Developments and Outlook

1

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

I.A. Recent Developments Growth momentum in the developing East Asia and Pacific region softened in 2018 as global conditions deteriorated and China’s economy continued its structural moderation. Despite these headwinds, the region’s economy exhibited resilience through 2018, led by robust domestic demand on the back of benign inflationary pressures, strong labor market outcomes and, in some cases, fiscal stimulus. Poverty continued to fall, albeit at a slightly slower pace than in the past. External headwinds have intensified with global manufacturing activity decelerating sharply at the end of 2018, global trade declining, economic activity in the United States slowing toward the end of the year, and Euro Area growth decelerating notably in 2018. The deterioration in global economic conditions manifested itself in weaker demand for the region’s exports and financial market volatility.

Global headwinds contributed to softening growth momentum in the region Growth in the developing East Asia and Pacific region softened in 2018. The region grew 6.3 percent in 2018, down slightly from 6.5 percent in 2017 (Figure I.A.1). Growth in the region, excluding China, eased marginally to 5.2 percent compared with 5.4 percent in 2017. Growth was underpinned by strong domestic demand and was resilient when put in the context of increasing global economic headwinds. The deceleration reflected continued moderation in economic growth in China, while the recovery in trade and manufacturing activity seen in the first half of 2018 lost momentum. The slower pace of growth in China during Q3 and Q4 of 2018 was broadly in line with expectations. Despite the overall downtick, the region remains a key driver of global economic activity, accounting for over one-third of global growth, with China contributing the lion’s share. Figure I.A.1. G rowth in developing East Asia and Pacific moderated in 2018

Figure I.A.2. Manufacturing activity softened in most major regional economies

GDP growth rates, percent change, y/y

Purchasing Manager’s Index (manufacturing; seasonally adjusted, 50+=expansion), 3-month moving avg.

8

57

7

56 55

6 54 5

53

4

52

3

51 50

2

49 1

48

9 r-1

n-

▬▬PHL

Ja

▬▬THA

Ma

19

8 v1

p18

No

▬▬VNM

Se

l-1

▬▬MYS

Ju

▬▬IDN

8

8 y1 Ma

8

▬▬CHN

n-

r-1

▬▬Developing EAP

Ma

▬▬China

Sources: Haver Analytics; World Development Indicators.

18

JJDeveloping EAP and China

47

Ja

Q4

-2 0 Q1 14 -2 0 Q2 15 -2 0 Q3 15 -2 0 Q4 15 -2 0 Q1 15 -2 0 Q2 16 -2 0 Q3 16 -2 0 Q4 16 -2 0 Q1 16 -2 0 Q2 17 -2 0 Q3 17 -2 0 Q4 17 -2 0 Q1 17 -2 0 Q2 18 -2 0 Q3 18 -2 0 Q4 18 -2 01 8

0

▬▬50+ expansion

Sources: Haver Analytics; Central Bank of the Philippines; World Bank staff estimates.

The external environment exerted downward pressure on regional growth. The global economy grew by 3 percent in 2018 with global manufacturing activity easing significantly in Q4 2018. Remaining trade tensions between the United States and China, tighter financial conditions than one year ago, and slower growth in global demand as some advanced economies and China grew at a slower pace added downward pressure to regional growth (Box I.A.1). Manufacturing activity in the developing East Asia and Pacific region softened by year end (Figure I.A.2). Geopolitical developments, such as Brexit deliberations in the U.K. and sanctions against Iran, compounded the challenges facing the global economy.

2

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

Box I.A.1. Recent Global Developments1 Global growth is estimated to have edged down to 3.0 percent in 2018 (Figure BI.A.1.1). Growth momentum eased to a near three-year low of 2.2 percent (q/q saar) in 18Q3 and incoming data suggest that the subdued momentum persisted in 18Q4. Goods trade growth has stagnated, and industrial production growth declined to a 26-month low of 1.8 percent (y/y) in December 2018. The weakness in global growth seems to have continued into 2019, with the global manufacturing Purchasing Managers’ Index (PMI) falling to 50.6 in February—its lowest level in more than two years. Global inflation, which trended up during most of 2018, has been dampened by sharp drops in oil prices observed since October. Global economic policy uncertainty remains elevated, likely contributing to the deceleration in activity (Figure BI.A.1.2). Figure BI.A.1.1. Global economic growth rates, 2010–18

Figure BI.A.1.2. Global economic policy uncertainty

Percent

Index, 2005=100

8

350

7

300

6

250

5

200

4 150 3 100 2 50

1

▬▬Advanced economies

Ja n Fe -19 b19

8 t-1 Oc

8 l-1 Ju

8 r-1 Ap

18

7

7

n-

2019f

Ja

2018e

t-1

2017

Oc

2016

l-1

2015

Ju

2014

r-1

2013

Ap

2012

n-

17

JJWorld

2011

Ja

2010

7

0

0

▬▬Emerging and developing economies

Source: Haver Analytics; World Bank. Note: Updated data will be published in the June 2019 issue of the World Bank’s Global Economic Prospects. The Global Economic Policy Uncertainty Index is a current price GDP weighted average of 18 national indices. Last observation is February 2019. The red line is the average for January 2015 to February 2019.

Among the advanced economies, U.S. growth picked up in 2018 to 2.9 percent, bolstered by fiscal stimulus measures. The most recent data suggest growth is slowing but remains resilient. In light of muted inflation and rising risks from the external environment, the Federal Reserve paused monetary policy tightening. Euro Area growth slowed notably in 2018 to 1.8 percent amid weakening external demand. In response to slowing activity, several governments announced plans for limited fiscal stimulus. In addition, the European Central Bank (ECB) has announced that it will provide banks with additional low-cost credit, starting in September 2019. Core inflation remains just above 1 percent, and the ECB is not expected to begin raising its main refinancing rate above zero until at least 2020. Growth in Japan slowed to an estimated 0.7 percent in 2018, partly reflecting the dampening effect of natural disasters. Fiscal stimulus is expected to soften the negative impact of the VAT hike planned in the second half of 2019. The Bank of Japan (BoJ) continues to provide exceptional stimulus by keeping long-term rates near zero and adding to its balance sheet. Growth moderated in about 45 percent of emerging markets and developing economies (EMDEs) in 2018, with notable declines in countries facing currency and financial market pressures. The cyclical upswing in regions with many commodity exporters, including Latin America and the Caribbean, and the Middle East (continued) 1

This box was prepared by Ekaterine Vashakmadze.

I.A. Recent Developments

3

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

(Box I.A.1 continued)

and North Africa, has been proceeding at a more moderate pace than previously anticipated, partly reflecting a contraction in some large economies (e.g., Argentina, Iran, and Venezuela). Growth in regions with large numbers of commodity importers, including South Asia and East Asia, remains solid reflecting robust domestic demand amid slowing export growth (Figure BI.A.1.3). Figure BI.A.1.3. R egional economic growth rates, 2012–18

Figure BI.A.1.4. Global trade growth

Percent

Percent

9

6

8 5 7 6

4

5 3 4 3

2

2 1 1 0

0 EAP

JJ2012–16

SAS

JJ2017

ECA

JJ2018e

LAC

JJ2019f

MENA

SSA

▬▬Average growth

Source: Haver Analytics; The World Bank. Note: The updated data will be published in the June 2019 issue of the World Bank’s Global Economic Prospects. Lines denote long-run (1990–2018) average growth.

2016

2017

2018

▬▬2000–18 average Source: The World Bank. Note: Aggregate growth rates calculated using constant 2010 U.S. dollar GDP weights. Trade measured as the average of export and import volumes.

After reaching a six-year high of 5.5 percent in 2017, global trade growth slowed to an estimated 4 percent in 2018, the sharpest deceleration since 2012 (Figure BI.A.1.4). Trade weakness has extended into the first quarter of 2019 amid weakening global demand and higher tariffs introduced in 2018, which affected about 12 percent of U.S. goods imports, 6.5 percent of China’s goods imports, and 2.5 percent of global goods trade. The World Trade Organization (WTO) World Trade Outlook Indicator dropped to 96.3 in February (a reading below 100 indicates below-trend growth), its lowest value since March 2010. The new export orders index fell to 49.1 in February, the lowest reading since mid-2016. Policy uncertainty remains elevated amid continued United States-China trade talks, and the possibility of tariff hikes on imports of automobiles and parts to the United States.

4

Figure BI.A.1.5. Commodity price indices Index, in nominal U.S. dollar terms. 2010 = 100 140 120 100 80 60 40 20

8 l-1

8

Ja n Fe -19 b19

Ju

7 l-1

7

n1 Ja

Ju

6

n1

l-1

6

▬▬Metals & minerals

Ja

Ju

5

n1

5

l-1

Ja

Ju

4 l-1

n1 Ja

4

▬▬Energy

Ju

n1 Ja

l-1

3

0

Ju

Commodity markets remain volatile. Oil prices have been rising since the beginning of the year, with Brent crude oil prices averaging $65/bbl over the first quarter of the year (Figure BI.A.1.5). This increase was driven by a fall in the global oil supply, mainly due to planned production cuts by Organization of the Petroleum Exporting Countries (OPEC) members and their nonOPEC partners, with Saudi Arabia contributing the most to the reduction. Metals prices edged up in the first half of 2019 reflecting improved market sentiment about easing United States-China trade tensions. Supply shortfalls and declining inventories in most metals markets—particularly copper, nickel, lead, and

▬▬Agriculture

Sources: The World Bank. Note: Last observation is March 18, 2019.

(continued)

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

(Box I.A.1 continued)

zinc—added to the recovery in prices. Iron ore prices were boosted at the start of the year by the Vale mining disaster in Brazil, which led to the temporary closure of mines. Agricultural prices were stable, on average, in the first quarter of 2019, amid high stock levels and favorable crop conditions for the fourth consecutive year. Wheat prices, which had outperformed other agricultural prices, fell sharply on positive supply news, particularly in Europe and Russia. Global financing conditions: recent rebound. Amid a deterioration in global economic prospects, major central banks have adopted a more dovish stance, with the U.S. Federal Reserve placing its tightening cycle on hold, and the ECB delaying the end of its negative interest rate policy and implementing new measures to stimulate credit and activity. A significant shift in market expectations about the future path of U.S. policy interest rates, together with a downward adjustment in U.S. inflation expectations, contributed to a significant easing of U.S. borrowing costs since the end of 2018. Euro Area yields also dropped considerably, with German 10-year bond yields falling below zero for the first time since 2016. Financing conditions and capital flows to EMDEs are recovering. As long-term yields pulled back in advanced economies, external financing conditions improved across EMDEs and capital flows recovered. Aggregate EMDE sovereign bond spreads have dropped by nearly 60 basis points since the start of 2019, although they remain above 2017 levels in many countries. Bond issuance improved as many borrowers took advantage of more favorable market conditions to tap into international debt markets. Some easing of external financing pressures, combined with moderating inflation, allowed many EMDE central banks to cut interest rates or put their tightening cycles on hold. A recovery in EMDE equity prices was also supported by expectations of reduced trade tensions between the United States and China, which contributed to improved investor risk appetite.

Financial market volatility, prevalent in the region for most of 2018, abated toward the end of the year. Macro-financial assets such as currencies, bonds and equities all suffered losses in 2018 on the back of financial market turbulence caused primarily by monetary policy normalization in the United States and risks (ultimately unrealized) of contagion stemming from currency crises in Argentina and Turkey. An emphasis on building buffers and bolstering macroeconomic fundamentals over the past few years helped regional economies to weather the worst of the turbulence. China’s economic growth moderated to 6.6 percent in 2018 from 6.8 percent in 2017, as the structural slowdown continued. Investment growth eased as the economy rebalances toward a consumption-driven growth model, while resilient consumption helped to prop up domestic demand and partly make up for a deceleration of exports towards the end of 2018. Higher-frequency data point to a moderation in growth, with indicators of manufacturing easing in recent months. The manufacturing Purchasing Managers' Index (PMI) recently fell below levels last seen in mid-2016, despite stimulatory policy initiatives in Q4 2018, while the services-related PMI rose and remained solidly in expansionary territory (Figure I.A.3).1

1

March data showed expansion in manufacturing PMI for China, possibly suggesting a tick-up in growth momentum. At the same time, 3-month average manufacturing PMI still showed under 50 as of March. Box I.A.2 provides evidence on how high-frequency data, and specifically a news-based sentiment index, can be used for forecasting.

I.A. Recent Developments

5

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Figure I.A.3. Monthly indicators hint at recovering momentum in China Panel A.

Panel B.

Monthly indices

Monthly indices

66

55

64

54

62 53 60 58

52

56

51

54 50 52 49

50 48

▬▬NBS PMI, construction

19 Ma r-1 9

18

Ja n-

Oc t-

Ju l-1 8

18

r-1 8 Ap

17

Ja n-

Oc t-

Ju l-1 7

17

r-1 7 Ap

16

▬▬NBS PMI, services

Ja n-

Oc t-

Ju l-1 6

r-1 6 Ap

19 Ma r-1 9

18

Ja n-

Oc t-

Ju l-1 8

18

r-1 8 Ap

17

Ja n-

Oc t-

Ju l-1 7

r-1 7

17

▬▬NBS PMI, manufacturing

Ap

16

Ja n-

Oc t-

Ju l-1 6

Ap

r-1 6

48

▬▬Caixin: composite PMI

Sources: CEIC and Wind Info. Note: 50+ = expansion. NBS refers to the Chinese National Bureau of Statistics.

Box I.A.2. How big data can improve our understanding of macroeconomic trends in East Asia and Pacific1 In recent years, there has been a massive proliferation of large, and often unstructured, datasets offering additional insights on macroeconomic trends. Examples of such datasets include media articles, satellite imagery, mobile phone call detail records, social media posts, and web searches (Fraiberger 2016; Donaldson and Storeygard 2016; Toole et al. 2015; Antenucci et al. 2014; Choi and Varian 2012). While these datasets have mostly been exploited by private companies, they can also be leveraged by policymakers aiming to improve the measurement and forecasting of economic conditions and inform policy decisions on a high frequency basis. The World Bank’s Big Data program has collected a large corpus of about 4 million media articles published by Reuters during the period from 1996 to 2016 and focusing on issues related to the economy in 25 countries. Exploiting information from media articles has two main advantages. First, media articles are available in real time, at a daily frequency, and across a large number of countries. Second, media articles describing economic conditions in a country convey information about economic forces that might not be easily captured by traditional data sources, such as the collective sentiment regarding economic prospects. News-based sentiment is measured using the proportion of positive words relative to the proportion of negative words appearing in these articles. This is done drawing on a pre-existing list of about 11,000 words classified in previous research (Loughran and Mc Donald 2011; Young and Sokora 2012) as either positive (e.g., “gain”, “improve”, and “agreement”) or negative (e.g. “concern”, “fear”, and “decline”). Then, one can count their occurrences in the text of each article, allowing for repetitions. These news-based media sentiments are shown to affect equity prices, affecting especially foreign investors (Fraiberger et al. 2018).

(continued) 1

6

This box was prepared by: Samuel Fraiberger, Richard Record and Trevor Monroe.

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

(Box I.A.2 continued)

The news-based sentiment comoves with GDP growth in major East Asia and Pacific countries. This box follows the approach of the World Bank’s Big Data program and extracts information from non-traditional sources to construct an indicator of media sentiment for major East Asia and Pacific economies. By restricting the sample to articles on one specific country, one can construct a country-specific news-based sentiment indicator. The resulting news sentiment index closely follows variations in GDP growth in that country (Figure BI.A.2.1), capturing both small fluctuations, as well as major downturns such as the 1997–98 Asian financial crisis or the 2007–09 global financial crisis. Figure BI.A.2.1. A news-based sentiment index can act as a leading indicator for growth… China

Indonesia

Percent positive, - percent negative

Annual percent

Percent positive, - percent negative

Annual percent

0

5

-0.5

8

-0.5

4

-1.0

6

-1.0

3

-1.5

4

-1.5

2

-2.0

2

-2.0

1

-2.5

0

-2.5

0

▬▬GDP growth, rhs

20

20

20

20

▬▬Sentiment, lhs

Malaysia

▬▬GDP growth, rhs

Philippines

Percent positive, - percent negative

Annual percent

2.0

15

1.5

10

1.0 5

0.5 0

0

Percent positive, - percent negative

Annual percent

2.5

10

2.0

8

1.5

6

1.0 0.5

4

0

2

-0.5

▬▬Sentiment, lhs

▬▬Sentiment, lhs

15 20

12 20

09 20

20

20

20

19

▬▬GDP growth, rhs

06

-6

03

-4

-2.5

00

-2.0

91

02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15

20

01

00

20

99

20

19

98

19

97

-15

-1.5

97

-2.0

-2

19

-10

-1.5

0

-1.0

94

-5

-1.0

19

-0.5

19

20

20

14 20

20

20

20

09

20

20

07

20

20

05 20

20

04 20

20

02

20

20

▬▬Sentiment, lhs

05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15

10

03

6

0

04

0.5

01

12

02

7

0.5

00

1.0

13

14

12

8

1.0

11

1.5

10

16

08

9

1.5

06

2.0

03

18

01

2.0

▬▬GDP growth, rhs

Thailand Percent positive, - percent negative

Annual percent

4

25

3

20 15

2

10 1 5 0

0

-1

-5

▬▬Sentiment, lhs

20 15

12 20

09 20

06 20

03 20

20

19

19

00

-15

97

-10

-3

94

-2

▬▬GDP growth, rhs

Source: World Bank Big Data program staff calculations. Note: The sentiment index is computed using the fraction of positive minus negative words appearing in a corpus of 4 million economic news articles from Reuters, after having classified articles by the country they focus on. The resulting sentiment index is averaged at a quarterly frequency and tracks fluctuations in quarterly GDP growth.

I.A. Recent Developments

7

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

(Box I.A.2 continued)

The news-based sentiment index can also help improve forecasts of GDP growth in developing East Asia and the Pacific. Policymakers have relied on the consensus forecast of annual GDP growth as a benchmark, which is produced on a monthly basis by a panel of professional forecasters, thus, arguably, enhancing the accuracy of information extracted from macroeconomic data sources with the opinions of well-informed professionals (Consensus Economics). The new-based media sentiment index can improve on the accuracy of forecasts relying on traditional sources. For a given forecasting horizon across a sample of East Asia and Pacific countries, the forecast error of a regression of annual GDP growth on the consensus forecast is consistently larger than the forecast error of a regression that additionally includes the sentiment index (averaged during the month prior to the release of the consensus forecast) as an explanatory variable. The results are similar for individual countries. Across the sample of East Asia and Pacific countries with available data, the average reduction in forecast error is equal to 15.4 percent relative to the consensus forecast, for forecasting horizons ranging from one to six months (Figure BI.A.2.2). Figure BI.A.2.2. …resulting in reduced forecast errors compared with consensus projections A.

B.

GDP growth forecast error, annual percent

GDP growth forecast error, annual percent

4.0

1.8

3.5

1.6

3.0

1.4 1.2

2.5

1.0 2.0 0.8 1.5

0.6

1.0

0.4

0.5

0.2 0

0 0

2

4

6

8

10

12

14

16

18

20

22

24

Philippines

Indonesia

Malaysia

China

Thailand

Horizon, months ▬▬Consensus forecast

▬▬Sentiment-adjusted forecast

JJConsensus forecast

JJSentiment-adjusted forecast

Source: World Bank Big Data program staff calculations. Note: a: Forecast error (root mean square error) of a forecasting regression of GDP growth on the consensus forecast (red) and including the sentiment index (blue) at different forecasting horizons. Regression includes country and time fixed effects. b: forecast error per country, averaged across horizons ranging from one to six months. Regressions include time fixed effects.

These results illustrate the value of using big datasets to provide policymakers with an additional source of high-frequency data. Similar approaches have been successfully applied using other forms of unstructured data. This work is still at an early stage, however. An important next step currently being pioneered by the Big Data program team consists of carefully combining the signals obtained from multiple big data sources to reduce the idiosyncrasies stemming from each source taken individually. Governments and development organizations would benefit from investing in the acquisition of big datasets, and in the tools and human resources necessary to analyze them. This would allow them to track variations in economic conditions in real time and at high resolution, complementing traditional sources of data, and enabling policymakers to react faster and more effectively to evolving economic conditions.

8

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

Q4 -2 01 Q1 4 -2 01 Q2 5 -2 01 Q3 5 -2 01 Q4 5 -2 01 Q1 5 -2 01 Q2 6 -2 01 Q3 6 -2 01 Q4 6 -2 01 Q1 6 -2 01 Q2 7 -2 01 Q3 7 -2 01 Q4 7 -2 01 Q1 7 -2 01 Q2 8 -2 01 Q3 8 -2 01 Q4 8 -2 01 8

Growth in the region’s other economies moderated Figure I.A.4. Growth softened in region’s largest economies slightly, on average, in 2018. Growth in Indonesia Percent, year-on-year 8 increased slightly compared to 2017, led by an uptick in 7 the growth rates of private consumption and investment. 6 Strong investment also helped support growth in the 5 Philippines. However, private consumption was subdued 4 as authorities battled to contain inflationary pressures 3 and combined with weak exports, resulting in GDP growth 2 moderating to 6.2 percent (from 6.7 percent in 2017), 1 below the government’s target range of 6.5 to 7.0 percent. 0 Strong domestic demand in Thailand helped offset a slowdown in exports and helped the economy expand by ▬▬CHN ▬▬IDN ▬▬MYS ▬▬PHL ▬▬THA ▬▬VNM 4.1 percent compared with 3.9 percent in 2017. Growth Sources: Haver Analytics; World Development Indicators. in Vietnam was broad-based and at its fastest pace, 7.1 percent, in 11 years, comfortably surpassing the government’s growth target of 6.7 percent. Growth ticket up in Q4 2018 as economic activity in several ASEAN economies surprised on the upside, mainly driven by robust domestic demand (Figure I.A.4). Growth rates in the region’s smaller economies remained firm, despite a slight moderation in activity (Figure I.A.5). Lao PDR grew by a solid 6.5 percent in 2018, down slightly from the previous year as growth in its extractives sector failed to offset a fall in agriculture production caused by floods (World Bank 2019a). The other smaller economies in the region also recorded solid growth outcomes. Despite weakening external conditions, Cambodia’s garment and footwear exports growth rate doubled that recorded in 2017. Mongolia’s mining sector drove economic growth in 2018 due to higher commodity prices and the easing of trade bottlenecks at the borders. Natural disasters in Papua New Guinea weighed on its growth outcomes (World Bank 2019b). Meanwhile, economic growth is estimated to have contracted in Timor-Leste on the back of constrained public spending. Private consumption and investment outcomes were also subdued owing to political uncertainty in 2018 with a new political cycle beginning in mid-2018 and the President vetoing the initial budget proposal.2 Figure I.A.5. Growth was solid in most of the region’s smaller economies Percent

Percent

10

9

9

8 7

8

6

7

5

6

4 3

5

2

4

1 0

3

-1

2

-2 1

-3 -4

0 2014

▬▬KHM

2015

▬▬LAO

2016

▬▬MNG

2017

▬▬MMR

2018e

2014

▬▬FJI

2015

▬▬TLS

2016

▬▬PNG

2017

2018e

▬▬SLB

Source: World Bank staff estimates.

2

The state budget was passed in February 2019.

I.A. Recent Developments

9

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Trade momentum eased significantly in 2018

r-1

9

8

Ma

Ap

Oc

r-1

t-1

8

7

t-1

Oc

Ap

r-1

7

6

t-1

Oc

6

r-1

Ap

5

t-1

Oc

Ap

r-1

5

Trade momentum decelerated in the second half of Figure I.A.6. Export value growth deteriorated in line with a moderation in global trade… 2018. Momentum stalled following the trade dispute Export value growth (12-month moving average, year-on-year percent change) between the United States and China (Figure I.A.6). Both 25 countries engaged in tit-for-tat trade restrictions with 20 a temporary cease fire being in December followed by 15 several rounds of high-level negotiations. China’s exports 10 to the United States held up in the first three quarters 5 of 2018 before slowing down in Q4—a reflection of 0 -5 strong economic activity in the United States, renminbi -10 depreciation against the U.S. dollar, and some front -15 loading of exports ahead of the new tariffs. China’s -20 imports from the United States also held up in the first three quarters due to strong domestic demand before ▬▬CHN ▬▬THA ▬▬MYS ▬▬IDN ▬▬PHL ▬▬VNM dropping in the final quarter of 2018. High-frequency Sources: Haver Analytics; World Bank staff estimates. trade indicators (such as monthly trade data from various customs agencies) suggest that the developing East Asia and Pacific region was not immune to the broader moderating trend in global trade. The increase in global commodity prices in the first half of 2018 supported commodity exporters in the region, and the sharp moderation in the second half of 2018 also drove trade outcomes (Figure I.A.7). The precipitous drop in the Philippines’ exports was due to a reduction in electronics exports and weaker services exports. The depreciation in regional currencies may have played a dampening role in the growth of imports in several of the region’s economies, but strong domestic demand appears to have played an offsetting role (Figure I.A.8). The notable exception was Myanmar, where the depreciation of the Myanmar kyat appears to have contributed to curbing imports of investment goods. Bilateral trade between major ASEAN economies and China appears to have suffered over the recent months, affected partly by increased uncertainty over trade tensions, disruptions of value chains, and reallocation of production (Figure I.A.9). Figure I.A.7…as did export volume growth Export volume growth (percent, 12-month growth rate)

Panel A

Panel B

12

30

10

25

8

20

6 15 4 10 2 5

0

▬▬EAP excl. China

▬▬IDN

▬▬THA

▬▬MYS

19 Fe b-

18 Au

g-

18 Fe b-

17 gAu

17 Fe b-

16 gAu

16 Fe b-

gAu

15 Fe b-

19 Fe b-

18 gAu

18 Fe b-

17 gAu

17 Fe b-

16 gAu

Fe b-

gAu

Fe b-

▬▬China

16

-10

15

-6

15

-4

-5

15

0

-2

▬▬PHL

Sources: Haver Analytics; World Bank staff estimates.

10

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

Figure I.A.8. O verall imports growth remained resilient despite weak Q4 outcomes Percent 30 25 20 15 10 5 0 -5 -10 -15

Q4 -2 01 5 Q1 -2 01 6 Q2 -2 01 6 Q3 -2 01 6 Q4 -2 01 6 Q1 -2 01 7 Q2 -2 01 7 Q3 -2 01 7 Q4 -2 01 7 Q1 -2 01 8 Q2 -2 01 8 Q3 -2 01 8 Q4 -2 01 8

-20

▬▬CHN

▬▬IDN

▬▬MYS

▬▬PHL

▬▬THA

▬▬VNM

Sources: Haver Analytics; World Bank staff calculations.

Moderating exports and resilient imports weighed on current account balances (Figure I.A.10). China’s current account surplus declined from 1.4 percent of GDP in 2017 to 0.4 percent of GDP in 2018. Depreciating currencies in some of the region’s economies also weighed on current account balances. Indonesia’s current account deficit increased to 3 percent of GDP in 2018 from 1.7 percent in 2017 on the back robust investment growth, which required large imports of raw material and capital imports. Indonesia is a net oil importer and the upward movements in oil prices in the middle of 2018 contributed to the wider current account deficit. Similarly, Mongolia’s current account deficit widened sharply due to imports of capital goods needed for a major mining construction

Figure I.A.9. China's imports from major ASEAN economies remain subdued Export value growth (year-on-year percent change)

Panel A. China's exports to major ASEAN economies

Panel B. China's imports from major ASEAN economies

30

40

25 30 20 20

15 10

10 5 0

0 -5

-10 -10

▬▬MYS

▬▬PHL

▬▬THA

▬▬VNM

▬▬IDN

▬▬PHL

▬▬THA

9 r-1 Ma

19 nJa

No

v-

18

18 Se

p-

8 l-1

yMa

▬▬MYS

Ju

8 r-1 Ma

Ja

n-

18

9 r-1 Ma

Ja

No

n-

v-

19

18

18 pSe

Ju

Ma

Ma

y-

l-1

8

18

8 r-1

18 nJa

▬▬IDN

18

-20

-15

▬▬VNM

Sources: CEIC; World Bank staff estimates.

Figure I.A.10. C urrent account balances deteriorated slightly in 2018 Current account balance as a percentage of GDP (seasonally adjusted, percent) 16 14 12 10 8 6 4 2 0 -2 -4

▬▬CHN

▬▬MYS

▬▬PHL

8 01

8 -2 Q4

01

8

▬▬THA

Sources: Haver Analytics; Central Bank of the Philippines; World Bank staff calculations.

I.A. Recent Developments

-2 Q3

Q2

-2

01

8 01

7 -2 Q1

-2

01

7 01 -2 Q3

Q4

7 -2

01

7

▬▬IDN

Q2

-2

01

6 01 -2 Q4

Q1

6 01 -2

-2

01

6 Q3

Q2

Q1

-2

01

6

-6

project, as well as imported oil products becoming more expensive following increases in commodity prices. In the Philippines, imports growth continued to significantly outpace exports growth and high frequency data showed a sharp contraction in the Philippines’ main export, electronics, in Q4 2018, partly due to the completion of the global technology inventory restocking cycle, which led to a slowdown in global electronics output and trade. Thailand’s current account surplus narrowed due to a reduction in services exports caused by fewer tourists from China (after a boating accident affected confidence) and a reduction in automotive parts exports to China due to the trade dispute between the United States and China. Higher global oil and gas prices helped Papua New Guinea’s

11

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

current account record a fourth consecutive annual surplus in 2018, despite disruptions from a major earthquake in February. Fiji’s current account deficit in 2018 is estimated to have widened to 5.9 percent of GDP, reflecting a larger trade deficit due to rising imports of vehicles and declining sugar exports. Early 2019 brought tentative signs of a détente in the United States-China trade dispute as the countries agreed to a further round of talks to try and resolve differences and thus avoid an escalation in protectionism. Trade representatives from both countries met at the end of January and in February in an attempt to end the trade dispute and to avoid an escalation on March 1, when the United States had intended to increase tariffs (from 10 to 25 percent) on US$200 billion worth of imports from China. Reports indicate that in a sign of willingness to reach a deal, China is revisiting new foreign investment regulations aimed at bolstering protections for foreign firms with regard to protecting intellectual property and ‘forced’ technology transfers, and offering to increase its purchases of U.S. agricultural commodities, energy products and manufactured goods over the next six years.3 The United States also wants China to make a number of structural reforms to level the playing field for businesses in China's market. That includes demands that China end pressure on American companies to hand over technology to Chinese partners to do business in China and reduce government subsidies and other advantages that Chinese companies and stateowned enterprises enjoy. While further rounds of negotiations are a positive development, the reported content of the discussions only highlight the difficulties that need to be overcome by both sides. Trade-related issues between the United States and other countries have also arisen in recent weeks and may weigh on confidence in the global arena and in the region. The United States has announced the removal of India and Turkey from its Generalized System of Preferences (GSP) agreement which provides exemptions from tariffs on goods exported to the United States. The United States believes that India does not provide equitable access to certain sectors in its own markets and that Turkey is sufficiently economically developed not to need preferential market access.4 Unlike the very real threat of protectionism, concerns that automation will reduce trade between the region and the United States or Europe appear to be overstated, at least in the foreseeable future (Box I.A.3).

Box I.A.3. Do robots threaten trade between the OECD and East Asia and Pacific countries?1 Modern industrial robots can perform a variety of repetitive tasks with consistent precision, and are increasingly being used in a wide range of industries and applications. Global sales of industrial robots reached a new record of 387,000 units last year (IFR 2018), and robot adoption is projected to continue to grow rapidly. The accelerating automation of production has stoked fears that large swaths of especially the unskilled workforce may suffer wage and job losses (Bloom, McKenna, and Prettner 2018). These fears are in part predicated on the experience of the OECD countries, where robot adoption has contributed to productivity growth at the expense of the employment share of low-skilled workers (Acemoglu and Restrepo 2017; Graetz and Michaels 2018). Recent estimates suggest that around 14 percent of jobs across OECD countries are at risk of disappearing because of automation, while another 32 percent are likely to see significant changes (OECD 2018).2 (continued) 1 2

This box was prepared by Erhan Artuc, Paulo Bastos, Luc Christiaensen, Bob Rijkers, and Hernan Winkler. In this analysis, included OECD countries are Belgium, Denmark, France, Italy, Japan, Rep. of Korea, Netherlands, Sweden, and the United States, while included East Asia and Pacific countries are China, Indonesia, Malaysia, the Philippines, Thailand, and Vietnam.

3 https://www.ft.com/content/4e60755e-2455-11e9-8ce6-5db4543. 4 https://ustr.gov/about-us/policy-offices/press-office/press-releases/2019/march/united-states-will-terminate-gsp.

12

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

(Box I.A.3 continued)

Concerns also have been raised about the impact of automation on jobs in the East Asia and Pacific region. Robotization might reduce the scope for OECD-EAP trade and incentivize production closer to home, thus undermining the prospects for export-led development (Hallward-Driemeier and Nayyar 2018). Such automation-induced trade declines could particularly affect East Asia and Pacific countries, such as Vietnam, that have relied on low labor costs to break into global markets by taking on repetitive and labor-intensive tasks. Moreover, developing countries may not have the requisite skills and infrastructure to meaningfully participate in future global value chains, as automation diminishes the importance of low labor costs as a determinant of competitiveness (Rodrik 2018). Recent research shows that, at least for now and for the foreseeable future, these fears about OECD automation hurting workers in East Asia and Pacific are overblown. Automation in OECD countries did not have a significant impact on labor market outcomes in developing countries, even within highly integrated trade blocs such as the North American Free Trade Agreement (NAFTA) (Artuc, Christiaensen, and Winkler 2019). On the contrary, OECD robotization promotes OECD-EAP trade through increased demand for intermediate inputs in global value chains, and is likely to benefit workers and consumers in developing countries (Artuc, Bastos, and Rijkers 2018). While OECD countries were among the first to adopt industrial robots on a large scale, East Asia and Pacific countries are catching up rapidly. In addition to technological feasibility, potential cost savings seem to be an important determinant of robot adoption, since richer countries—where both wages and the opportunity cost of labor are higher—tend to use more robots (Figure BI.A.3.1, Panel A). In recent years, East Asia and Pacific countries, and in particular China, have demonstrated accelerated robot adoption rates (Figure BI.A.3.1, Panel B). Figure BI.A.3.1. Drivers of robot adoption A. Robot adoption is associated with the (opportunity) cost of labor

B. East Asia and Pacific countries are automating rapidly

Robot density

IFR Operational robot stock, average by industry

1.4

2,000

DEU BEL

1.2

SWE FIN ITA NLD FRA USA

1.0

SVN

0.8

DNK

HUN 0.4

1,200 1,000

GBR CZE

PRT

SVK

1,600 1,400

ESP 0.6

1,800

800 600

IRL

400 0.2

POL ROU HRV BGR EST 0 LVA

Initial GDP per capita, constant 2010 USD

▬▬World

15 20

13 20

09

20 11

20

07 20

03

05 20

20

99

▬▬OECD

20 01

97

19

50,000

19

40,000

95

30,000

19

20,000

93

0

10,000

19

0

200

GRC

▬▬EAP

Source: Authors’ calculations. Note: Panel A shows the relationship between the number of robots per 1,000 workers (robot density) and per capita GDP. Panel B show evolution of the number of robots over time in the OECD, East Asia and Pacific, and the world.

Rather than crippling OECD-EAP trade, automation has catalyzed it. Both exports from the OECD to East Asia and Pacific countries, and imports of OECD countries from the East Asia and Pacific region have surged as a result of increased automation. Figure BI.A.3.2 shows that a 10-percent increase in robot density in the OECD is associated with a 10.9-percent increase in exports to, and a 6.6-percent increase in imports from East Asia (continued)

I.A. Recent Developments

13

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

(Box I.A.3 continued)

and Pacific countries. The increased exports from the OECD are easily explained by robot-induced reductions in production costs, while striking growth in imports from the East Asia and Pacific reflects increasing intermediate input demand within the global value chains. Simulation analysis shows that workers in the East Asia and Pacific region are likely to benefit from automation in the medium and long run. Robot 1.8 prices relative to labor costs have declined by more 1.6 1.4 than 70 percent in the United States and more than 1.2 50 percent in Germany since 1990 (The Economist 1.0 2008). Simulation analysis shows the impact of this past 0.8 0.6 decline and continuing future declines in automation 0.4 costs. After a reduction in robot prices, producers in 0.2 0 OECD countries, who face higher wages, adopt more Exports Imports robots (Figure BI.A.3.3, Panel A). Subsequent price In, 1+robots per million hours declines make it profitable for East Asia and Pacific QQImports Exports Source: Authors’ calculations. countries, where producers face lower labor costs, to Note: The instrumental variables regression shows the impact of an increase in the number of robots per worker by industry and country on exports and imports between East Asia and Pacific and OECD. also robotize production. Robot adoption is associated The number of robots is instrumented with per capita GDP, the number of replaceable tasks by industry and growth of the global robot stock. with an initial reduction in the number of jobs in the automating sector (Figure BI.A.3.3, Panel B), and thus in real wages (Figure BI.A.3.3, Panel C). However, the impact of robot price reductions on employment is nonlinear. Once all tasks that can be automated are performed by robots, further reductions in robot prices boost the demand for labor in the robotized sector, because they make workers in those sectors more productive. As a result, labor demand and real wages begin to rise in the simulations once the fall in robot prices approaches 90 percent. While robots compete with workers in the early stages of adoption, they complement them in subsequent stages. As OECD producers demand progressively more intermediate inputs to enable their expansion of production, their demand for East Asia and Pacific exports of intermediates surges. Interestingly, workers in East Asia and Pacific enjoy increases in real wages. As robot prices fall, aggregate welfare increases in all countries, but more so in the countries that adopt more robots (Figure BI.A.3.3, Panel D). Figure BI.A.3.2. E stimated impact of OECD automation on exports to, and imports from, East Asia and Pacific countries

In summary, industrial robots will most likely continue to catalyze, rather than reduce, OECD-EAP trade and enhance global welfare. This conclusion is likely to be reinforced by the fact that other new technologies— such as high-speed internet, blockchain, and digital platforms—will reduce even further the costs of trading and coordinating across borders (Brynjolfsson, Hui, and Liu 2018) and can lead to the creation of new products and tasks (Acemoglu and Restrepo 2018). At the same time, trade and technological change will necessitate labor market adjustment and may create severe distributional tensions.

(continued)

14

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

(Box I.A.3 continued)

Figure BI.A.3.3. Effects of robot price reductions on robot use, labor allocation, wages and welfare A. Robot use

B. Labor allocation in robotized industries

Robot use per worker

Percent change in number of workers

1.0

0

0.9

-5

0.8

-10

0.7 0.6

-15

0.5

-20

0.4

-25

0.3

-30

0.2

-35

0.1 0

-40 0

10

20

30

40

50

60

70

80

90

0

10

20

Percent reduction in robot price ▬▬EAP

30

40

50

60

70

80

90

70

80

90

Percent reduction in robot price

▬▬OECD

▬▬EAP

▬▬OECD

C. Wages

D. Welfare

Percent change in real wage

Percent change in real GDP

4

6

3

5

2

4

1

3

0 2 -1 1

-2

0

-3

-1

-4 0

10

20

30

40

50

60

70

80

90

0

10

20

Percent reduction in robot price ▬▬EAP

▬▬OECD

30

40

50

60

Percent reduction in robot price ▬▬EAP

▬▬OECD

Source: Authors’ calculations. Note: The simulations show the impact of a reduction in robot prices, or equivalently a change in robots’ productivity, on robot use, labor allocation, wages and welfare. The simulations are based on a trade in tasks model with two production stages, calibrated with East Asia and Pacific and OECD trade, input-output linkages and wage data using world input-output tables from Timmer et al. (2015).

Robust domestic demand supported growth outcomes in 2018 Robust domestic demand supported growth in the region’s economies. In several major regional economies, private consumption, supported by benign inflation, drove growth (Figure I.A.11). Private consumption in Thailand grew at its fastest pace in almost six years on the back of a supportive low-inflation and low-unemployment environment as well as the expiration of the holding period for cars purchased in the first-car tax rebate program. Strong private consumption in Indonesia supported growth throughout 2018, helped by low consumer price inflation and robust labor market conditions with the employment rate reaching a two-decade high of 65.7 percent and the unemployment rate falling to a 17-year low of 5.1 percent. In China, consumption remained the main contributor to GDP growth. Robust consumption was supported by the government of China’s modestly accommodative fiscal policy stance, which included tax incentives to boost household spending. In contrast, in the Philippines private consumption growth eased slightly as inflationary pressures weighed on consumption. Consumption tax holidays, special payments to civil servants and pensioners, stable labor market conditions and moderating inflation combined to support private consumption in Malaysia (World Bank 2018a). Consumption was constrained in some of the smaller economies in the region, for example, in Myanmar due to inflationary pressures and in Timor-Leste due to political and economic uncertainty.

I.A. Recent Developments

15

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Figure I.A.11. Strong domestic demand supported growth in 2018 Contribution of expenditure components to change in GDP (percentage points, year-on-year)

Q3 8 Q4 201 -2 8 01 Q1 8 -2 01 Q3 6 -2 01 Q1 6 -2 01 Q3 7 -2 01 Q1 7 -2 01 Q3 8 -2 Q4 01 -2 8 01 Q1 8 -2 01 Q3 6 -2 01 Q1 6 -2 01 Q3 7 -2 01 Q1 7 -2 01 Q3 8 -2 Q4 01 -2 8 01 Q1 8 -2 01 Q3 6 -2 01 Q1 6 -2 01 Q3 7 -2 01 Q1 7 -2 01 Q3 8 -2 Q4 01 -2 8 01 Q1 8 -2 01 Q3 6 -2 01 Q1 6 -2 01 Q3 7 -2 01 Q1 7 -2 01 Q3 8 -2 Q4 01 -2 8 01 8

7

01

Q1

-2

7

01

Q3

-2

6

01 -2

Q1

01 -2

-2 Q1

Q3

01

6

18 16 14 12 10 8 6 4 2 0 -2 -4 -6 -8 -10

China

JJPrivate consumption

Indonesia

JJGross capital formation

JJGovernment consumption

Malaysia

JJNet exports

Philippines

JJStatistical discrepancy

Thailand

▬▬GDP growth

Source: Haver Analytics; Thailand Office of the National Economic and Social Development Board; World Bank staff calculations. Note: For China, consumption refers to both government and private consumption.

The region showed signs of a maturing investment cycle in 2018. While investment growth played a supportive role in the region there were some signals of softness. Investment growth in China eased, despite a pickup in private fixed asset investment, following the government’s continued efforts to rebalance the economy and a contraction in public infrastructure investment (World Bank 2018b). Investment growth momentum in Malaysia remained soft in the second half of 2018 as public sector investment eased due to the completion of several major infrastructure projects, as well as the deferment or cancellation of other projects. In Indonesia, while investment growth strengthened overall in 2018, a maturing investment cycle eased investment growth in Q4. Fiscal consolidation efforts in Vietnam that reduced public investment drove an easing of investment growth. In contrast, investment growth in the Philippines increased in 2018 (despite a significant moderation in growth in the second half of the year) on the back of increased construction-related investment (World Bank 2019c).

Inflationary pressures were subdued in the larger regional economies and elevated in the smaller economies Price pressures were mixed across the region. Most of the region’s larger economies recorded moderating inflation (Figure I.A.12), as monetary policy tightened in response to exchange rate depreciation in the aftermath of the U.S. Federal Reserve's efforts to normalize interest rates. Energy subsidies in Indonesia also helped to play a role in keeping inflation subdued. The notable exception was the Philippines, where inflation rose through much of the year, to rates not seen since 2009. However, aggressive monetary policy tightening in 2018, a decline in global oil prices since October 2018, and improvements in the supply of key staple commodities, reduced inflation in Q4 2018 and Q1 2019 (to the lowest rate in 15 months). By contrast, the smaller economies (such as Cambodia, Lao PDR, Myanmar, Papua New Guinea, and Timor-Leste) recorded elevated inflation (Figure I.A.13), largely due to low base effects from the end of 2017 and rising food and energy costs. The surge in prices in Myanmar in 2018 was largely due to a depreciation of the Myanmar kyat and adverse weather conditions, which affected key crops and drove inflation higher than the 2018 target of 6 percent. Producer prices followed the trajectory of consumer prices and peaked in mid-2018 (Figure I.A.14). Given that many regional economies are capital importers, the recovery in currencies in Q4 2018 played a role in dampening pressure on input prices. Moderating economic activity in 2018 also exerted downward pressure on prices. Inflation remains well below the target inflation rate in most of the major economies (Figure I.A.15).

16

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

Figure I.A.12. I nflationary pressures have eased markedly in major economies…

Figure I.A.13. …but remain elevated in some smaller regional economies

Headline inflation (end of period year-on-year, percent)

Headline inflation (end of period year-on-year, percent)

7

10

6 8 5 6 4 3

4

2 2 1 0

0 -1

▬▬IDN

▬▬MYS

▬▬PHL

▬▬THA

▬▬VNM

▬▬KHM

▬▬LAO

▬▬MMR

▬▬MNG

-1 9 Fe b

Oc t-1 8

18 Ju n-

-1 8 Fe b

Oc t-1 7

17 Ju n-

-1 7 Fe b

Oc t-1 6

16 Ju n-

-1 6 Fe b

Ju l-1 8 Oc t-1 8 Ja n1 Ma 9 r-1 9

Ju l-1 7 Oc t-1 7 Ja n18 Ap r-1 8

r-1 6

▬▬CHN

Ju l-1 6 Oc t-1 6 Ja n17 Ap r-1 7

Ap

Ja n-

16

-2

▬▬TLS

Source: Haver Analytics.

Figure I.A.14. G rowth in producer prices fell sharply at the end of 2018

Figure I.A.15. Inflation remained below target in the region’s major economies

Producer Price Index (end of period year-on-year change, percent)

Percent

12

5

10 8

4

6 4 3 2 0 2

-2 -4

1

-6 -8

▬▬CHN

▬▬MYS

▬▬PHL

▬▬THA

Source: Haver Analytics. Note: The official Producer Price Index of the Philippines only covers the manufacturing sector.

9 r-1

0 Indonesia

Ma

Se

p-

18

8 r-1 Ma

Se

p-

17

7 r-1

pSe

▬▬IDN

Ma

16

6 r-1 Ma

15 pSe

Ma

r-1

5

-10

JJ2016

Vietnam

JJ2017

China

Malaysia

JJ2018

Philippines

Thailand

▬▬2018 inflation target

Source: Haver Analytics, World Bank.

Financial markets recovered in early 2019 after significant volatility during 2018 Macro-financial conditions in the region have stabilized following turmoil in 2018, which resulted in currency depreciations, capital outflows, and equity market corrections. Major economies in the developing East Asia and Pacific region (Indonesia, Malaysia and Thailand) witnessed net capital outflows in 2018 Q2 and Q3 as investors sought safe havens. Major currencies in the region have begun to regain the ground lost last year against the U.S. dollar and started 2019 on a high note (Figure I.A.16). Both the Indonesian rupiah and the Philippine peso have recovered (since the October 2018 EAP Economic Update), supported by tightening monetary policy. The region’s major stock markets also have regained some of the ground lost in 2018 (Figure I.A.17). Equities in China have surged by around 30 percent this year after decreasing by more than 40 percent from the peaks of early 2018. Indonesia has completely reversed the losses from 2018, while the trajectories—especially since the start of

I.A. Recent Developments

17

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

2019—in the other major stock markets are also looking bullish. Stock market volatility has begun to abate, not only in the developing East Asia and Pacific region but more broadly in emerging markets, after spiking sharply in mid-2018 due to crises in Argentina and Turkey, and the imposition of trade restrictions between the United States and China (Box I.A.4). While fears of a prolonged crisis and financial contagion eased toward the end of 2018, volatility remains at an elevated level, especially compared with early 2017 and early 2018 (Figure I.A.18).

▬▬IDN

▬▬MYS

▬▬PHL

▬▬THA

▬▬CHN

▬▬IDN

8 Ma r Ap -1 r-19 9

c-1

18

▬▬THA

De

pSe

n-

18

8

▬▬PHL

Ju

7

r-1 Ma

c-1 De

p-

17

▬▬MYS

Se

Ju

n-

6

r-1

c-1

De

▬▬VNM

Source: Haver Analytics.

Ma

5 c-1

r-1

Se

Ma

p-

r-1

Se

Ma

p-

r-1

Se

Ma

p-

r-1 Ma

▬▬CHN

p-

70

De

85

Se

90

16

90

n-

110

Ju

95

r-1

130

Ma

100

9

150

18

105

8

170

17

110

7

190

16

115

6

210

17

Equity market indices ($, Index, end-2015=100)

120

7

U.S. dollar to local currency (December 2015=100)

16

Figure I.A.17. Following a period of corrections, stock markets have begun to recover

6

Figure I.A.16. Major currencies regained lost ground at the end of 2018

▬▬VNM

Sources: Thomson Reuters; Datastream; International Finance Corporation Global Macro & Market Research.

Figure I.A.18. Uncertainty triggered stock market volatility in 2018 Percent, 3-month moving average

▬▬IDN

▬▬MYS

▬▬PHL

▬▬THA

▬▬VNM

▬▬BRA

▬▬MEX

▬▬ARG

▬▬TUR

9 r-1 Ap

19 Ja

n-

8 t-1 Oc

Ju

l-1

8

8 r-1 Ap

18 Ja

n-

7 t-1

17 nJa

r-1 Ap

nJa

Oc

t-1

8 l-1 Ju

r-1 Ap

nJa

t-1 Oc

7 l-1 Ju

r-1 Ap

nJa

▬▬CHN

Oc

0

7

0

l-1

0.1

Ju

0.2

0.1

r-1

0.3

0.2

9

0.3

19

0.4

8

0.5

0.4

8

0.6

0.5

18

0.6

7

0.7

7

0.8

0.7

17

0.9

0.8

7

Panel B

0.9

Ap

Panel A

▬▬RUS

Source: Thomson Reuters; Datastream; International Finance Corporation Global Macro & Market Research; Haver Analytics; World Bank staff calculations. Note: The volatility in stock prices is the ratio of the absolute value of the cyclical component over the trend component of the indices. The Hodrick-Prescott filter is used to decompose the natural log of the stock price indices into cyclical and trend components. All indices are rebased to December 2015 = 100.

18

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

Box I.A.4. The costs of trade tensions for East Asian financial markets1 Stock market returns in East Asia have been affected by the recent announcements of protectionist measures by the United States and China. These tensions, which started in 2017 after the current United States administration took over and intensified in 2018, had a global impact, given the size of the two economies and the dense networks of value chains in East Asia. This box compares returns on the main stock market indices immediately after threats, announcements and implementation of trade barriers by the United States and China.2 If announcements are unexpected and if market prices fully and immediately reflect all new information, changes in market indices after protectionist announcements should reflect the financial markets’ expectation of the loss of value for the firms in the index. Identifying the exact timing of the effect is important. When announcements are made in the United States, markets are closed in Asia. This box examines the effects on valuations in the next trading day when Asian markets can react. When announcements occur in Asia, markets are assumed to react immediately. When events occur on a weekend or on a day when markets are closed, the effect for the next open day is examined. The impact of the “trade war” on Asian stock markets is statistically significant and economically large (Figure BI.A.4.1). China being at the center of the “trade war”, its financial markets suffer the brunt of the losses and fall by 0.6 percent after a negative announcement. The effect is halved for higher-income countries (0.36 percent) and is even smaller for middle-income countries, which are less integrated with China. Differences across countries in East Asia emerge when looking at individual financial markets (Figure BI.A.4.2). A negative protectionist event tends to be associated with a decline in stock market valuation, with the Shenzen Composite Index falling as much as 0.8 percent.

0.6 0.4 0.2 0 -0.2 -0.4 -0.6 -0.8 -1.0 -1.2 -1.4 -1.6

T SE d an

Th ail

its

Tim

sit e ra St

Sh

en zh

en

Co m

po

sit

E

po

PS ai

Co m

es an gh

i2 0

X

50 Ph ili

Ni kk ei

ng

pp in Sh

SE FT

Middle-income High-income All countries Only mainland China countries countries Source: CEIC data and authors' calculation. Note: Results based on the full sample; results from 2018-sample are stronger. Lines with bars show confidence intervals. "High-income countries" include Japan, Korea, Hong Kong SAR, China, and Singapore; “middle-income countries” include Indonesia, Malaysia, the Philippines, and Thailand.

Bu

-0.9

Ha

rsa

Ma

-0.8

Se

lay

ng

sia

-0.7

JS

-0.6

sp

-0.5

ia

-0.4

Ko

-0.3

es

-0.2

In do n

-0.1

e

Percent

0

e

Percent

0

Figure BI.A.4.2. W hich stock market index suffers more because of the “trade war”?

0

Figure BI.A.4.1. W hich country group suffers more because of the "trade war"?

Source: CEIC data and authors' calculation. Note: Results based on the full sample, results from 2018-sample are stronger. Lines with bars show confidence intervals.

(continued) 1 2

This box was prepared by Francesca de Nicola, Martin Kessler, Ha Nguyen. Specifically, we estimate returnit = ci + ai * eventt + εit, where returnit is the realized return of stock market i at time t, eventt is a categorical variable that takes value 0 on non-event days, 1 on negative event days, and -1 on positive event days. The cumulative loss is measured as ∏t (1 + α)t – 1, where α is the index-specific coefficient for the impact of a protectionist event. Interest rate hikes by the U.S. Federal Reserve—and subsequent capital outflows—may have also played a role in the overall decline in stock markets. The analysis in this box focuses on specific trading days, which will likely isolate the impact of trade wars, but it does not separately investigate any effects of monetary policy tightening on stock markets in East Asia.

I.A. Recent Developments

19

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

(Box I.A.4 continued)

Protectionist announcements resulted in huge stock market losses in 2018. From January to August 2018, protectionist announcements accounted for about half of the total stock market decline in China and as much as 80 percent of the decline in the Rep. of Korea. The total cumulative loss for the region related to “trade war” announcements during this period is estimated to exceed $2 trillion (Table BI.A.4.1). While this approach cannot measure the impact of these financial losses on jobs or output, it shows that “trade war” announcements are associated with significant financial costs. Table BI.A.4.1. Cumulative impact of protectionist announcements: the stock market perspective

Index

FTSE Bursa Malaysia Hang Seng Indonesia JSX Kospi200 Nikkei 500 Philippines PSE Shanghai Composite Shenzhen Composite Straits Time Thailand SET

Estimated changes due to "trade war" announcements Accumulated Accumulated Accumulated Losses in US Actual changes impact (estimated, impact (upper impact (lower dollars (billion) (percent) percent) bound, percent) bound, percent) (estimated)

0.3 -9.6 -7.1 -11.5 -8.2 -14.0 -19.4 -24.4 -6.6 -4.3

-7.3 -11.0 2.5 -9.8 -5.9 -4.7 -8.5 -13.5 -4.7 -6.6

-14.4 -20.7 -5.9 -18.1 -16.8 -13.1 -17.7 -26.4 -13.8 -13.1

-0.6 -2.1 10.2 -2.2 4.0 3.0 -0.1 -2.1 3.7 -0.4

-33 -514 14 -149 -365 -18 -490 -1,038 -7 -36

Source: Authors' calculations. Note: Counterfactual scenario relies on estimates from the 2018-only sample. Higher and lower bound impacts are based on the 95 percent confidence interval estimates. Numbers in bold are equity markets with statistically significant impacts. The losses in US dollars are based on the initial market capitalization of the index (in local currency), converted in US dollars using the exchange rate at the end of the period (August 2018).

External corporate and sovereign bond spreads began to narrow at the end of 2018 after significant widening during most of the year (Figure I.A.19). Movements in yields in 2018 were heavily influenced by a reluctance to assume risk, as investors sought safe havens following financial market turbulence and monetary policy normalization in the Unites States. Investor appetite for risk appears to be returning with spreads now declining. Spreads in China also declined in the beginning of 2019, although they remain at the levels of the 2018 maximum (the January 2019 spread was about 50 basis points higher than the same time last year). Indonesia bond yields—which saw the sharpest increase in the developing East Asia and Pacific region of just under 240 basis points in 2018—also remain elevated, but have been trending downward over the past couple of months. The Indonesia bond spread in March 2019 was about 60 basis points lower than the widest spread in 2018, but still around 40 basis points higher than the lowest spread, seen in March 2018. Several economies tightened monetary policy in 2018 in an attempt to manage exchange rate volatility and to stem capital outflows. Bank Indonesia (BI) was particularly active in attempting to manage Indonesian rupiah volatility and a widening current account deficit. Similarly, the Central Bank of Myanmar was heavily involved in managing exchange rate volatility—primarily through the use of its foreign exchange reserves and supported by moving toward a de-facto floating exchange rate regime and allowing currency swaps with domestic banks. While central bank authorities in the Philippines also hiked interest rates, their rationale was to curb high inflation with depreciation pressures on the peso, seen as a secondary concern. In contrast to tightening policies elsewhere in developing East Asia and Pacific, the authorities in China recently eased reserve requirement ratios and established a bond swap facility to support growth.

20

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

The People’s Bank of China noted that the central objective was to increase financing support for the economy. Central banks in the region relied on both policy rates and international reserves drawdowns to defend against disorderly currency depreciation (Figure I.A.20). Figure I.A.19. E xternal corporate and sovereign bond spreads widened in 2018

Figure I.A.20. International reserves supported interventions in foreign exchange markets

Emerging Market Bond Index spreads, basis points

International reserves in percent of imports of goods and services

450

500

900 800

400 400

350

700 600

300 300

500

250

400

200

200 300

150 100

200

100

100

50

0

▬▬IDN

▬▬MYS

▬▬PHL

▬▬VNM

▬▬EM global diversified

▬▬PHL

-2 Q4 018 -2 01 8

8

Q3

-2

01

7

▬▬THA

Q1

-2

01

7 Q3

Q1

-2

01

6 01

6 -2

01 -2

Q3

5

▬▬MYS

Q1

Q3

-2

01

5 01 -2

01

▬▬IDN

Sources: JP Morgan; International Finance Corporation Global Macro & Market Research.

Q1

Q3

-2

01 -2 Q1

rAp 19 r-1 9

De

Ma

c-1

8

18 p-

Ju

Se

n-

r-1

18

8

7 c-1

Ma

Ju

Se

De

p-

17 n-

7 r-1 Ma

▬▬CHN

17

4

0

4

0

▬▬VNM

▬▬CHN, rhs

Source: Haver Analytics; World Bank staff calculations. Note: rhs=right hand side.

Safe haven demand coupled with the United States’ monetary policy normalization resulted in reduced net foreign direct investment (FDI) inflows for most of 2018, but capital began to return in early 2019. The rise in financial market volatility during 2018 resulted in FDI inflows into the region slowing (Figure I.A.21). Net portfolio flows, which tend to be more volatile than FDI flows, also recorded outflows as investors sought less risky assets and sought to limit exposure to depreciating currencies (Figure I.A.22). Figure I.A.21. T he region witnessed declining net FDI inflows in 2018

Figure I.A.22. Net portfolio flows declined in 2018

Net FDI inflows, US dollar billion, cumulative over four quarters

Portfolio investment: Net inflows, 4-quarter moving average, percent GDP

25

250

20

200

12

15

10 8

10 15

150

10 100

6 4

5

2

5 50 0

0

0

-2

0

-5

-4

-5

▬▬MYS

▬▬PHL

Source: Haver Analytics. Note: rhs=right-hand side.

▬▬THA

▬▬VNM

-6 -8

JJTotal excl. CHN, rhs

▬▬CHN

▬▬IDN

▬▬MYS

▬▬PHL

▬▬THA

8

Q4

-2

01

8 Q3

-2

01

8 Q1

-2

01

7 Q3

-2

01

7 Q1

-2

01

6 Q3

-2

01

6 Q1

-2

01

5 Q3

-2

01

5 -2 Q1

-2 Q4

▬▬CHN, rhs

01

8

-10

01

8 Q3

-2

01

8 Q1

-2

01

7 Q3

-2

01

7 01 Q1

-2

01 Q3

-2

01 Q1

-2

01 Q3

-2

01 -2 Q1

▬▬IDN

6

-100

6

-15

5

-50

5

-10

▬▬VNM

Source: Haver Analytics, World Bank staff estimates. Note: rhs=right-hand side.

Credit growth was mixed across the region (Figure I.A.23). Accommodative monetary policy stances in 2017 supported an upward trajectory for some economies (Indonesia, Malaysia, and Thailand) in 2018. The impact of robust credit growth was mixed with investment (which typically is positively correlated with credit growth) contributing strongly to economic

I.A. Recent Developments

21

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

growth in Indonesia and Thailand, while detracting from growth in Malaysia. In other countries (China, the Philippines, and Vietnam) credit growth continued the downward trajectory from 2017. China’s trajectory reflected a continuation of corporate deleveraging that began a couple of years ago. In Lao PDR, overall credit growth eased in 2018 mainly due to the government’s fiscal tightening efforts. Private sector credit growth also eased but remained similar to that in 2017. Credit growth remained elevated in smaller economies such as Cambodia. Figure I.A.23. Credit growth outcomes were mixed Real growth in net domestic credit Panel A

Panel B

Year-on-year, percent

Year-on-year, percent

22

35

20

30

18

25

16 20

14 12

15

10

10

8

5

6

▬▬VNM

▬▬KHM

▬▬LAO

8 c-1 De

18 Ju

n-

7 c-1 De

17 Ju

n-

6 c-1 De

16 Ju

n-

5 c-1 De

Ju

n-

4 c-1 De

19

8

bFe

t-1

18 n-

Oc

18

▬▬THA

Ju

7

b-

t-1

Fe

17

▬▬PHL

Oc

17

nJu

b-

t-1

▬▬MYS

Fe

16

Oc

nJu

b-

15

t-1

▬▬IDN

Fe

Oc

b-

nJu

Fe

▬▬CHN

6

-10

16

0

5

-5

15

2

15

0

4

▬▬TLS

Sources: Haver Analytics; World Bank staff estimates. Note: Nominal growth in domestic credit is deflated by the CPI. For Vietnam, we refer to total credit. For Cambodia, we refer to net credit to the private sector (loans).

The approach to fiscal policy was mixed There was a mix of fiscal policy stances in the region with the balance in favor of a more prudent approach (Figure I.A.24). This partly indicates a shift in macroeconomic policy priorities in recent years toward improving macroeconomic fundamentals, which helped the developing East Asia and Pacific region to emerge relatively unscathed from global financial market disruptions in 2018. Improved tax administration and revenue mobilization played a key role in supporting fiscal consolidation in several countries in the region, including Indonesia, Lao PDR and Vietnam in 2018. Increased revenue collections stemming from favorable commodity prices supported consolidation efforts in Mongolia. Fiscal policy in China was expansionary in the second half of 2018. The government of China introduced tax cuts and bumped up local government investment. The expansionary stance in the second half of the year contrasted with policy in the first half of the year, when revenues grew faster than government expenditure. Some of the region’s smaller economies (such as Cambodia and Fiji) also had accommodative fiscal policies in 2018. In Fiji’s case, fiscal policy was expansionary due to the roll-over of capital expenditure in the aftermath of Tropical Cyclone Winston and increases in the wage bill and social welfare.

22

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

Figure I.A.24. Fiscal policy stances varied General government fiscal balance Panel A

Panel B

Percent of GDP

Percent of GDP 5

1 2 0 -1

0

0

-2 -5

-2

-3 -4

-4

-10

-6

-15

-5 -6 -7

2013

▬▬CHN

-20

-8

-8 2014

▬▬IDN

2015

▬▬MYS

2016

▬▬PHL

2017

▬▬THA

2018

▬▬VNM

2013

▬▬KHM

2014

▬▬FJI

2015

▬▬LAO

2016

▬▬MMR

2017

▬▬PNG

2018

▬▬MNG, rhs

Source: World Bank staff estimates. Note: These data refer to general government fiscal balances in all countries except Indonesia, where the data refer to the central government fiscal balance; fiscal deficits do not reflect off-budget expenditures.

Recent developments in the Pacific Island Countries Growth in the Pacific Island Countries (PICs) is estimated to have been positive in 2018. Development-partnerfunded construction continued to bolster economic growth in the region as well as agricultural exports (logging in the case of the Solomon Islands and fishery exports in Kiribati). In Tuvalu, economic activity accelerated due to the hosting of a regional summit that led to an increase in large infrastructure and housing projects. The pace of growth in the South Pacific economies (Samoa, Tonga and Vanuatu) moderated, largely due to natural disasters and economic shocks. Economic growth slowed in Samoa due to the closure of a major manufacturer of automotive wire harnesses and the reversion of fishing exports to more moderate levels following two very strong years. Increased public infrastructure investment and activity related to the hosting of regional summits were not enough to offset the negative effects. Growth in the North Pacific Countries—the Federated States of Micronesia (FSM), the Republic of the Marshall Islands (RMI) and Palau—was also positive. In the case of FSM, the estimated 2018 outcome ensured a fourth consecutive year of growth. Overall fiscal positions in the PICs were solid due to improved revenue collection. Revenue from fishing licenses drove budget surpluses in the Central and North Pacific countries while prudent fiscal policy stances in the South Pacific countries helped balance Samoa’s budget and supported a small surplus in Tonga. Fiscal consolidation via a reduction in development expenditures helped the Solomon Islands to achieve a balanced budget. One of the main driving forces behind the tighter fiscal policy stance in the Solomon Islands is the expectation of lower revenues from logging exports in line with a more sustainable approach to logging.

I.A. Recent Developments

23

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Resilient domestic demand supported poverty reduction in the region Poverty continued to decline amid strong private consumption growth. Robust private consumption was supported by low inflation, strong labor market outcomes in some countries, and government fiscal policies. Coupled with a history of strong economic growth, developing East Asia and Pacific is now a region comprised of exclusively lower-middle and upper-middle income countries. In China, Malaysia, Mongolia, and Thailand, the extreme poverty rate at the International Poverty Line (IPL, $1.90/day in 2011 PPP) is less than 1 percent. While the region has proven very successful at poverty reduction based on the IPL (in 2018, developing East Asia and Pacific’s regional poverty rate is based on the IPL and is 1.5 percent), some prosperous countries in the region require poverty monitoring at higher standards (Figure I.A.25).5 Figure I.A.25. Poverty has continued to decline across the region Poverty rate and number of poor (size of bubble, million) Panel A. Developing EAP

Panel B. Developing EAP excluding China

Poverty rate, percent

Poverty rate, percent

60

60

50

50

343 942 828

40

335

328

316

304

291 278

40

757 690 645

30

30

589

183

538

174

165

455

147

20

140

20

339

243

10

221

139 70

58

44

0 2012

2013

128

119

28

25

294

2014

2015

39 2016

192 34 2017

168 30 2018

10

51

44

39

34

31

0 2012

2013

2014

2015

2016

QQInternational Poverty Line ($1.90 per day 2011 PPP)

QQInternational Poverty Line ($1.90 per day 2011 PPP)

QQLower-Middle Income Class poverty line ($3.20 per day 2011 PPP)

QQLower-Middle Income Class poverty line ($3.20 per day 2011 PPP)

QQUpper-Middle Income Class poverty line ($5.50 per day 2011 PPP)

QQUpper-Middle Income Class poverty line ($5.50 per day 2011 PPP)

2017

2018

Sources: World Bank East Asia and Pacific Team for Statistical Development; PovcalNet.12 Note: For a description of the lower-middle and upper-middle income class poverty lines, see Box II.A.1 in Part II.A. A Broader View of Poverty in EAP.

Wage growth is supporting robust private consumption in some countries (Figure I.A.26). In Malaysia, labor market conditions remained stable throughout the second half of 2018. Manufacturing wages grew strongly at 9.8 percent in Q4 2018, significantly outpacing wage growth in the services sector. In the Philippines, the expansion of real wages beginning the second half of 2018 and the continued movement of workers from agricultural employment to nonagricultural wage jobs, likely contributed to the increase in household incomes. It is likely that the growth of household incomes, especially of the bottom 40 percent of the population, continued in 2018 although the impact of inflation may have slowed down poverty reduction.

5 6

24

The International Poverty Line (IPL) was first derived from the national poverty lines of the world’s poorest countries, at a time when 60 percent of the global population lived in lowincome countries. In 2013, the share of population living in low-income countries was much lower at 8 percent (Fantom and Serajuddin, 2016). The most recent household survey used for actual estimates vary from 2006 in Kiribati to 2016 in Indonesia and Mongolia. Estimates prior to 2016 are: (i) derived directly from household survey data; (ii) China 2013 is a survey break and data are not comparable with previous years (iii) interpolated between existing surveys; or (iv) extrapolated based on per-capita GDP growth and historical estimates of the growth elasticity of poverty, but China, Papua New Guinea and Pacific Island countries based on neutral growth distribution. For 2016 onwards, estimates are projected based on projected per-capita GDP growth and the GEP (Global Economic Prospects), and are hence preliminary and subject to revision. In China, data through 2012 are not comparable with those for subsequent years, owing to a change in the survey methodology which acted to lower reported poverty, and may account for nearly half of the reported decrease in the poverty headcount between 2012 and 2013. In late 2012, separate urban and rural household surveys were replaced with a single national household survey, which uses stratified, multi-stage sampling methods. There were significant changes in the collection of information from migrants (now treated as part of the urban population when measuring aggregate disposable income), and the treatment of net taxes and transfers in rural areas; and rents from home ownership are now imputed. This latter factor in particular may have had a substantial effect on reported poverty.

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

Understanding of poverty can be improved by recognizing it is a complex and multifaceted problem (Part II.A). The poverty threshold guides policymakers’ understanding to who and how many people are considered poor. The estimated number of poor in developing East Asia and Pacific in 2018 based on the international ($1.9), lower-middle income class ($3.2), and uppermiddle income class ($5.5) poverty lines are 30 million, 168 million, and 538 million respectively (Figure I.A.25).7 In addition, poverty is not one-dimensional. Being poor encompasses not only a shortfall in income and consumption but also low educational achievement, poor health and nutritional outcomes, lack of access to basic services, and an unsafe living environment, making poverty a multidimentional concept (Box II.A.3). While many countries in developing East Asia and Pacific have made good progress in tackling poverty, the region as a whole is very diverse and a number of sub-regions still face daunting poverty reduction challenges.8

Figure I.A.26. Wage growth was strong across the majority of large economies Real wage growth, year-over-year percent change 10 8 6 4 2 0 -2 -4 -6 -8 2014

▬▬PHL

2015

▬▬MYS

2016

▬▬MNG

▬▬CHN

2017

▬▬VNM

2018

▬▬THA

Source: World Bank staff estimates using official sources. Note: For China, data refer to urban nonprivate wage growth. For the Philippines, 2018 wage is preliminary. Wages data for Indonesia refer to August of each year.

Box I.A.5. Subnational monetary poverty in developing East Asia and Pacific1 Following strong growth during the past two decades, developing East Asia and Pacific is now a region made up entirely of middle-income countries, most of whom have also seen rapid reductions in extreme poverty.2 At the same time, rising incomes and wealth have led to legitimate questions as to whether the international poverty line ($1.90/day 2011 PPP) is now too low to define whether someone is poor in developing East Asia and Pacific. Higher poverty lines are needed that are better suited to track progress and match aspirations in more developed countries. The lower-middle-income and upper-middle-income poverty lines, set at $3.20/ day 2011 PPP and $5.50/day 2011 PPP, respectively, are better aligned with basic standards of living among households in lower-middle-income countries (LMICs) and upper-middle-income countries (UMICs).3 Some regions in developing East Asia and Pacific face daunting poverty reduction challenges. Residents of developing East Asia and Pacific live at all levels of economic well-being, stability, and environmental fragility. Eight out of 36 countries worldwide in fragile, conflict and violence (FCV) settings are located in East Asia and Pacific.4 Even in relatively stable countries, subnational FCV areas exist, such as Southern Thailand and Mindanao Philippines. Most of developing East Asia and Pacific countries are island nations, which are frequently hit by (continued) 1 2 3 4

7 8

This box was prepared by Judy Yang and Shiyao Wang. The extreme poverty rate is based on the international poverty line (IPL) of $1.90/day 2011 PPP. Specifically, $3.20/day 2011 PPP represents the median of national poverty lines among LMIC countries when converted to 2011PPP units, and the $5.5/day 2011 PPP represents the median of national poverty lines of UMIC countries. They are designed to complement, not replace, the $1.90/day extreme poverty line, also referred to as international poverty line (IPL). See Box 1 in Part II.A for more detailed information. EAP FCV countries in FY2019: Kiribati, Republic of the Marshall Islands, Federated States of Micronesia, Myanmar, Solomon Islands, Tuvalu, Papua New Guinea, and TimorLeste. http://pubdocs.worldbank.org/en/892921532529834051/FCSList-FY19-Final.pdf.

See Box II.A.1 in Part IIA for a discussion of definitions of the lower-middle income class (LMIC) and upper-middle income class (UMIC) poverty lines. See Box I.A.5. for a description on subnational variation in poverty rates.

I.A. Recent Developments

25

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

(Box I.A.5 continued)

natural disasters. These disasters are not limited to the seasonal and somewhat predictable, but also include earthquakes and volcanic eruptions that can take populations by surprise. Substantial variation in poverty rates exists at the subnational level, especially at these higher poverty lines. The percentage of the population in developing East Asia and Pacific living under $3.2/day (the LMIC poverty line) is estimated to be 8.2 percent. However, across 78 regions, this percentage varies from 0.0 percent in Bangkok, Thailand (2017) to 84.5 percent in Oecussi, Timor-Leste (2014) (Figure BI.A.5.1). At the even higher standard, 51 regions have populations where over half are living below the UMIC poverty line ($5.5/day). This variation underscores the immense diversity of the region. For relevant and targeted policymaking, poverty should be monitored in a geographically disaggregated manner, especially to acknowledge the variation in living standards within the same country. When this is done, pockets of poor become noticed, even in relatively well-off countries. In the Philippines, the LMIC poverty rate is about 5.8 percent in the capital region. However, in the conflict-affected region of Autonomous Region in Muslim Mindanao (ARMM), the LMIC poverty rate is 68.3 percent. In Lao PDR, the poverty rate in the capital city is less than half that measured elsewhere in the country. Figure BI.A.5.1. S ubnational poverty map, LMIC poverty line ($3.2/day 2011 PPP) 0–1 1–8 8–15 15–22 22–29 29–33.5 33.5–42 42–45.5 45.5–65.5 >65.5 Cambodia

(continued)

26

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

(Box I.A.5 continued)

Pacific Island Countries (left to right): The Solomon Islands, Vanuatu, Fiji, Tonga 0–1 1–8 8–15 15–22 22–29 29–33.5 33.5–42 42–45.5 45.5–65.5 >65.5 Cambodia

Source: EAPTSD. Note: Data are not available for countries in gray: Cambodia. The subnational poverty map uses data from the EAPPOV data collection managed by the East Asia and Pacific Team for Statistical Development, World Bank. There are 78 subnational regions on this map. Subregions are the smallest geographic level where poverty rates are representative or can be shown due to data constraints. In some countries, only the national poverty rates can be shown, due to either the small size of the country or data confidentiality issues. These countries include China, Federated States of Micronesia, and the Solomon Islands. Subnational international poverty rates in China are not available, since the World Bank does not have access to microdata. Data ranges from 2009 in Papua New Guinea to 2016 in Mongolia and Indonesia.

A broader view of poverty that includes monitoring poverty across regions and at higher poverty lines reveal there is still much work to be done in developing East Asia and Pacific. This broader view helps to enhance policy dialogue and craft policies that are more relevant and targeted. While eliminating remaining pockets of poverty must be the priority, higher standards should be used to reflect increasing aspirations and higher costs of living, and ensuring upward mobility (improving one’s lot in life) and economic security (being able to hold onto gains made).

I.A. Recent Developments

27

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

I.B. Outlook and Risks Global growth is expected to slow further in 2019, leading to weaker demand for exports. For the developing and East Asia and Pacific region, where many countries have benefited from trade and financial integration during the past two decades, this constitutes an acute risk to growth in the short term, and regional growth is expected to moderate. Risks to the outlook remain firmly tilted to the downside and, in some cases, have intensified. The risks stem largely from a softening of global demand, a faster-than-expected moderation in growth in China, unresolved trade tensions, and from possible disorderly financial market developments.

Regional growth is expected to moderate slightly in 2019 Global conditions are expected to be less supportive in 2019. Economic activity is projected to soften from 3.0 to 2.7 percent, affecting aggregate demand for the region (Box 1.B.1). Economic activity in advanced economies has been diverging. Growth in the United States was bolstered by fiscal stimulus, whereas activity in the Euro Area has been weaker than previously expected, owing to slowing net exports. International trade and investment have softened, trade tensions remain elevated, and some large emerging market and developing economies (EMDEs) have experienced substantial financial market pressures. Against this challenging backdrop, EMDE growth has stalled, with a sharply weaker than expected recovery in commodity exporters accompanied by a deceleration in commodity importers.

Box I.B.1. Global Outlook and Risks1 Global growth is expected to stabilize at 2.8 percent on average in 2020–21. The global economic growth rate is projected to slow to 2.7 percent in 2019, reflecting broad-based weakness at the start of the year, before stabilizing at 2.8 percent on average in 2020–21 (Figure BI.B.1.1). Growth in advanced economies is projected to moderate from 2.1 percent in 2018 to 1.7 percent in 2019 and ease further to 1.6 percent on average in 2020– 21, as capacity constraints become more apparent and labor markets tighten. Advanced economies are expected to move gradually closer to their relatively modest long-run potential growth rates, which remain constrained by aging populations and weak productivity trends. Growth among emerging markets and developing economies (EMDEs) is projected to slow to 4.2 percent in 2019 before recovering modestly in 2020–21. Weak EMDE growth in 2019 reflects the lingering effects of 2018 financial market stress on several large economies, a lackluster and notably softer-than-envisioned cyclical recovery in commodity exporters, and a further deceleration in commodity importers. The expected modest recovery of EMDE growth to 4.6 percent on average in 2020–21 is due to the projected dissipation of severe headwinds in a few large economies (e.g., Argentina, the Islamic Republic of Iran, and Turkey). Economic activity is forecast to remain robust in EMDE regions with large numbers of commodity importers, including South (continued) 1

28

This box was prepared by Ekaterine Vashakmadze.

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

(Box I.B.1 continued)

Asia, and East Asia, and the Pacific, though support from exports is expected to diminish. The cyclical upswing in regions with many commodity exporters, including Latin America and the Caribbean, and the Middle East and North Africa, is expected to plateau toward the end of the forecast horizon (Figure BI.B.1.2). The long-term drivers of EMDE growth are expected to continue weakening during the coming decade unless significant policy changes boost potential growth rates effectively. EMDEs face a subdued pace of capital accumulation, slowing productivity growth, and maturing demographic transitions. While demographic trends will continue to support growth in South Asia, aging populations and rising dependency ratios are expected to weaken growth in East Asia and Pacific (e.g., China and Thailand) and Europe and Central Asia (e.g., Poland and the Russian Federation). Figure BI.B.1.1. A ggregate GDP growth rates, estimated and projected

Figure BI.B.1.2. Regional GDP growth rates, estimated and projected

Percent

Percent

10

9

8

8 7

6

6

4

5

2

4 3

0

2 -2

1

-4

0 2007–08

JJWorld

2009

2010

▬▬Advanced economies

2011–17

2018e

2019–20f

EAP

2021f

▬▬Emerging and developing economies

Source: World Bank. Note: e = estimate, f = forecast; updated forecasts will be published in the June 2019 issue of the World Bank report, Global Economic Prospects.

JJ2012–17

SAS

ECA

JJ2018e

LAC

JJ2019f

MENA

JJ2020f

SSA

JJ2021f

Source: World Bank. Note: Lines denote long-run (1990–2018) average growth rates. e = estimate. f = forecast; updated forecasts will be published in the June 2019 issue of the World Bank report, Global Economic Prospects.

20

20

15

20

10

20

05

20

00

20

95

19

90

19

85

19

19

80

Global economic conditions are expected to become Figure BI.B.1.3. World commodity price forecasts less supportive of growth over the forecast period. Index 2010=100 130 Barring a renewed escalation of trade tensions, global 110 trade growth is currently projected to moderate toward 90 3.3 percent on average in 2019–21, due to easing 70 global investment growth, ongoing policy uncertainty, 50 and higher tariffs. This is somewhat stronger than 30 global GDP growth, but significantly below the average performance since 2000. Global financing conditions 10 are expected to remain volatile. Despite the recent ▬▬Energy ▬▬Metals ▬▬Agriculture recovery of EMDE markets from the 2018 correction Source: The World Bank. Note: Updated forecasts will be published in the June 2019 issue of the World Bank report, Global episode, there is still a considerable risk of “monetary Economic Prospects. shocks” associated with global policy uncertainty. Renewed financial market pressures could lead to a broad-based deterioration of the outlook for EMDEs. Financial market volatility will continue to have the strongest impact on countries with relatively liquid financial markets, large current account deficits, and/or economic ties to distressed economies, as well as those that are directly targeted by tariffs and sanctions. Oil prices are forecast to average $64/bbl in 2019 and $65/bbl in 2020, though, (continued)

I.B. Outlook and Risks

29

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

(Box I.B.1 continued)

uncertainty around these forecasts is high. Despite weaker demand prospects, metals prices are anticipated to stabilize in 2019 and 2020 due to modest supply growth and low inventory levels. Agricultural prices are expected to remain broadly flat over the next two years (Figure BI.B.1.3). Risks continue to be on the downside. There is considerable uncertainty around the outlook for the global economy and the balance of risks remains firmly on the downside. Although unlikely in the near term, the simultaneous occurrence of a sharper-than-expected slowdown in China, the Euro Area, and the United States— which together account for 50 percent of global GDP—could trigger a significant downturn in global activity. The re-escalation of trade tensions could be highly disruptive to global activity amid the presence of complex value chains. The risk of severe and broad-based financial stress adversely affecting the outlook for EMDEs remains high amid elevated debt levels in many countries. Policy uncertainty and geopolitical risks remain high and could negatively impact confidence and investment in both affected countries and globally. Policy uncertainty is particularly elevated in a number of European countries—including in the United Kingdom as it transitions out of the European Union, and in Italy where fiscal slippages have led to a market reassessment of country risk.

Developing East Asia and Pacific economies are not immune to these trends, and regional growth is expected to moderate from an estimated 6.3 percent in 2018 to 6 percent in 2019 and 2020, broadly unchanged from the October 2018 EAP Economic Update. Some tentative signs of softening economic activity in the region began to emerge in late 2018 and early 2019, following softening of economic activity in China. China’s growth moderated to 6.6 percent in 2018 and is projected to ease to 6.2 percent, on average, in 2019–20, as the economy continues its transformation toward a domestic-demand driven model. Consumption will remain the main driver of growth in China, while higher investor uncertainty and slower credit growth are expected to weigh on investment. Growth prospects in the rest of the region are projected to remain broadly stable, at 5.2 percent on average in 2019–20, supported by resilient domestic demand led both by consumer spending and government spending in a few select countries (Table I.B.1). Growth in Indonesia and Malaysia is projected to remain unchanged in 2019, while Thailand and Vietnam are projected to exhibit slightly lower growth rates in 2019. In Malaysia’s case, the government’s commitment to fiscal consolidation is expected to weigh on growth slightly in the near term. In the Philippines, the delay in approving the 2019 national government budget and the ban on construction of public works during the election period is expected to weigh on GDP growth in 2019. Nonetheless, growth is expected to recover in 2019 from 2018 given an expected acceleration in private consumption growth and momentum on public investment growth, assuming the budget is approved soon. Growth is expected to pick up in 2020. Growth is expected to remain robust in the smaller economies. Large infrastructure projects are expected to drive a pickup in growth for Lao PDR (major hydropower and other infrastructure projects, see World Bank 2019a) and Mongolia (accelerated development in the minerals sector, especially copper and coal, and in the meat industry). Cambodia’s growth is projected to remain robust over the forecast horizon, although at a slower pace than in 2018, mainly due to expectations of a weaker global economic environment. Expansionary fiscal policy in the lead-up to elections in 2020 is expected to boost growth in Myanmar in the short term, while recent structural reforms are expected to support growth in the medium term. Growth is expected to reach 5.1 percent in Papua New Guinea in 2019 as the economy recovers from a catastrophic earthquake that caused significant loss of life and major disruptions in the liquified and natural

30

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

gas (LNG) sector. A recovery in that sector is expected to drive growth in 2019. Growth in Fiji is projected to continue to rise, albeit tempered by a decline in public investment as expenditures on reconstruction in the aftermath of tropical cyclones decline. Growth in the Pacific Island Countries (PICs) is expected to remain resilient due to major infrastructure investments and construction projects. However, growth is expected to decline in Nauru, due to difficulties in adapting to the downscaling of operations of Australia’s Regional Processing Centre for asylum seekers and the depletion of phosphate reserves (Nauru’s major export). Table I.B.1. EAP economic outlook Change from October 2018 Updatea percentage points

Developing EAPd China Developing EAP excl. Chinad Developing ASEANd Indonesia Malaysia Philippines Thailand Vietnam Cambodia Lao PDR Myanmar Mongolia Fiji Papua New Guinea Solomon Islands Timor-Lesteb Assumptions about the external environment:c World Advanced economies Emerging and developing economies Crude oil (spot, US$/barrel) Non-energy commodities (index, 2010=100) Food (index, 2010=100)

2016

2017

2018

2019f

2020f

2018

2019

2020

6.4 6.7 4.9 5.0 5.0 4.2 6.9 3.3 6.2 7.0 7.0 5.9 1.4 0.7 2.6 3.3 5.1

6.5 6.8 5.4 5.4 5.1 5.9 6.7 3.9 6.8 7.0 6.9 6.8 5.4 3.0 2.8 3.0 -3.5

6.3 6.6 5.2 5.2 5.2 4.7 6.2 4.1 7.1 7.5 6.5 6.2 6.9 3.2 0.3 3.5 -0.7

6.0 6.2 5.2 5.2 5.2 4.7 6.4 3.8 6.6 7.0 6.6 6.5 7.2 3.4 5.1 2.9 3.9

6.0 6.2 5.2 5.3 5.3 4.6 6.5 3.9 6.5 6.9 6.7 6.6 6.9 3.3 3.1 2.8 4.6

0.0 0.1 -0.1 -0.2 0.0 -0.2 -0.3 -0.4 0.3 0.5 -0.2 0.0 1.0 -0.3 1.9 0.1 -1.5

0.0 0.0 -0.1 -0.1 0.0 0.0 -0.3 -0.1 0.0 0.2 -0.3 0.0 0.6 0.0 1.6 0.0 0.6

0.0 0.0 -0.1 0.0 0.0 0.0 -0.1 0.0 0.0 0.1 -0.2 -0.2 0.6 0.0 0.0 0.0 -0.3

2.6 1.7 4.1 43

3.1 2.3 4.5 53

3.0 2.1 4.3 68

2.7 1.7 4.2 64

2.8 1.6 4.6 65

0.0 -0.1 0.1 -3

-0.2 -0.3 -0.1 -9

0.0 0.0 0.0 -6

79

84

85

83

85

-1

-2

-1

90

90

90

88

89

-2

-5

-5

Source: World Bank data and staff estimates. Note: a) World Bank East Asia and Pacific Economic Update, October 2018 (World Bank 2018a). b) Nonoil GDP. c) Global growth and commodity price forecasts represent preliminary working assumptions. Myanmar data are fiscal year growth rates (2018 = FY2018/19). Changes from October 2018 are calculated with one decimal points precision and rounded to one decimal point. d) Estimate.

Domestic demand is expected to play an important role again in supporting growth outcomes ( Figure I.B.1). Private consumption is expected to remain the main driver of economic growth in most of the economies in the region. As investment growth eases in China, private consumption growth outcomes will be watched closely for signs of a fasterthan-expected growth moderation due to the spillover effects it may have on the rest of the region. Notwithstanding the support private consumption is projected to give to overall growth, growth is expected to moderate slightly, in line with the broader global economic moderation.

I.B. Outlook and Risks

31

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Figure I.B.1. Domestic demand will continue to drive growth over the forecast period Contribution of expenditure components to GDP growth among developing EAP countries (percentage points) Panel A. Including China

Panel B. Excluding China

7

7

6

6

5

5

4

4

3

3

2

2

1

1

0

0

-1

-1 2014

2015

2016

2017

JJGovernment consumption

JJPrivate consumption

JJNet exports

▬▬GDP

2018

2019

2020

JJGross capital formation

2014

2015

2016

2017

JJGovernment consumption

JJPrivate consumption

JJNet exports

▬▬GDP

2018

2019

2020

JJGross capital formation

Source: World Bank staff estimates.

Robust domestic demand is expected to continue to support poverty reduction in the region Growth is expected to remain resilient and poverty is expected to continue declining supported by strong domestic demand ( Table I.B.2). By 2020, the proportion and number of extreme poor (based on the international poverty line [IPL] of $1.90/day 2011 PPP) in the region will be relatively small and they will be concentrated in a few countries—Lao PDR, Papua New Guinea, and Timor-Leste—and in remote locations within more affluent countries. The policy challenge will be reaching these differentiated groups of extreme poor with public services and social assistance programs. Developing East Asia and Pacific is also a region that is sensitive to natural disasters, with floods and cyclones occurring regularly, events which disproportionally affect the extreme poor. Table I.B.2. Poverty in developing East Asia and Pacific is projected to continue falling 2018

2019

2020

2021

1.5 30

1.3 27

1.1 23

1.0 21

3.8 25

3.4 23

3.0 20

2.7 19

8.2 168

7.2 148

6.3 131

5.6 116

17.9 119

16.5 110

15.1 102

13.9 95

PPP $1.90 per-capita per-day poverty: Estimates and projections Developing EAP

Poverty rate (%) Number of poor (millions) Developing EAP excluding China

Poverty rate (%) Number of poor (millions) PPP$3.20 per-capita per-day poverty: Estimates and projections Developing EAP

Poverty rate (%) Number of poor (millions) Developing EAP excluding China

Poverty rate (%) Number of poor (millions)

32

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

Table I.B.2. Poverty in developing East Asia and Pacific is projected to continue falling (continued) 2018

2019

2020

2021

26.2 538

23.7 489

21.3 443

19.2 401

41.9 278

39.6 265

37.4 253

35.3 241

PPP$5.50 per-capita per-day poverty: Estimates and projections Developing EAP

Poverty rate (%) Number of poor (millions) Developing EAP excluding China

Poverty rate (%) Number of poor (millions)

Source: World Bank East Asia and Pacific Team for Statistical Development. Note: The most recent household income and expenditure surveys vary from 2006 in Kiribati to 2017 in Indonesia and Thailand. Estimates are extrapolated based on per capita GDP growth and historical estimates of the growth elasticity of poverty. PPP = purchasing power parity.

Risks to the outlook remain firmly tilted to the downside and in some cases have intensified The risks stemming from weakening global outlook have intensified and are expected to weigh on economic growth in developing East Asia and Pacific countries. In 2018, countries in the region managed to weather the deterioration of external conditions due to reasonably sound economic fundamentals and robust domestic demand. Sound fundamentals allowed countries in the region to take a standard approach to using policy to manage challenges, such as increased exchange rate volatility, widening current account deficits, and a moderation in economic activity. However, given that some risks have intensified, regional policymakers will have to focus on effectively utilizing and rebuilding the buffers that were so useful in weathering adverse conditions in early 2018. This is particularly the case given the considerable uncertainty around the outlook for the global economy, especially with ongoing indications that global demand is softening. Although unlikely in the near term, the simultaneous occurrence of a sharper-than-expected slowdown in China, the Euro Area, and the United States—which together account for 50 percent of global GDP—could trigger a significant downturn in global activity. A faster-than-expected moderation in growth in China would pose significant risks to other economies in the region. This is particularly the case for some of the smaller economies in the region that are highly dependent on commodity exports to China (Mongolia, Papua New Guinea, and the Solomon Islands), or on tourism and FDI (Cambodia and Palau). However, slower-than-expected growth in China would lead to spillovers to other regional economies too. Estimates suggest that a 1.0 percentage point slowdown in China’s growth could reduce growth in the region by around 0.5 of a percentage point, on average, after two years (World Bank 2018c). While China has introduced a series of measures to support growth and improve investors confidence, risks remain, including amplification of both internal and external adverse shocks originating in specific industries (Box I.B.2). The measures include fiscal incentives for households and businesses, higher infrastructure investment, higher liquidity provision by the central bank, and guidance to ease the financing constraints of the private sector and SMEs. Some of the fiscal incentives are temporary (e.g., VAT rate reductions, higher VAT rebates to exporters, tax deductions for R&D and equipment purchases) and some permanent (i.e., amendment to the Individual Tax Law that raised the minimum income threshold and introduced itemized deductions).

I.B. Outlook and Risks

33

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Box I.B.2. Propagation of macroeconomic shocks through input-output and geographic networks in China1 Macroeconomic shocks can spread through input-output and geographic networks, leading to sizeable macroeconomic fluctuations. Demand-side shocks are more likely to spread to input-supplying industries, for example companies who supply raw materials for further processing (referred to as upstream industries) (Acemoglu et al. 2016). By contrast, supply-side shocks tend to spread to industries that purchase other firms’ outputs, for example for further processing or sale to consumers (referred to as downstream industries). This box examines the impact of demand and supply shocks on output fluctuation in China through a network approach. Examining the impact of shocks through a network approach can be used to assess the potential impact on output fluctuations and provides another tool to make predictions about how various policies can affect the economic cycle. Figure BI.B.2.1. Network effects A. Downstream propagation Percent 25

4

20

3

15 2 10

0

m

fe

n-

g sin

JJNetwork effect

Mf

no

Fo

ls ica

all et

sin es

m es oc

Pr

Mf

g

no

n-

oc

ic

pe g

g Mf Pr

leu

em

tro

s)

et

ch

(lh

m

g rin

us

tu

rro

ac

fe

uf

g

an

sin

m

es

n-

oc

No

Pr

i rro nera ls us m g ele od p eta l ctr r s ica oces s le qu ing ip m e Mf Mf M g g r fg nt ge ub m ne be eta ra l p r, pl ls ur as po tic s s Mf e m g ac co h. m p Mf uter s g Mf tex til g e m Mf ed s g ic Mf P auto ines g roc m sp es ob ec si ial ng iles pu tim Pr rp in os ber tin em g ac an M h. d f g r Us eco pa eo pe rd r f w ed m as ed te ia re M sou Mf Mf fg b rce s g ev g c m ea hem erag s Mf urin ical es g ar g in fibe tic st r les rum s ar cu en t, ltu ts an re Ma nu M d sp , ed fa fg or u, ctu ap ts Mf re pa g of rel tra to ns ba po rta M cco tio fg f o n eq ods ui Ot Mf pme g h n Ma er m foo t tw nu ea fa anu ctu fa r c Re re o tur pa f f ing ir ur of n m itur et al e ite m s

0

m

1

als

5

JJWithin effect

B. Upstream propagation Percent 3

25 20

2

15 10

1

5

No nm Pr an oc ufa es sin ctur i g fe ng ( rro lh us s) Pr Mf me Mf oce g ch tals ssi g em Pr n oc on- ng p ica ls es m e t sin e r g talli oleu no cm m ni fe rro nera Mf Fo us m ls g ele od p eta ls ctr r ica oces sin le qu g ip m e Mf Mf M g g r fg nt ge ub m ne be eta ra l p r, pl ls ur as po tic s s Mf e m g ac co h. m p Mf uter s g Mf tex til g e m Mf ed s g ic Mf P auto ines g roc m sp es ob ec si ial ng iles pu tim Pr rp in os ber tin em g ac an M h. d f g r Us eco pa eo pe rd r f w ed m as ed te ia re M sou Mf Mf fg b rce s g ev g c m ea hem erag s Mf urin ical es g ar g in fibe tic st r les rum s ar cu en t, ltu ts an re Ma nu M d sp , ed fa fg or u, ctu ap ts Mf re pa g of rel tra to ns ba po rta M cco tio fg f o n eq ods ui Ot Mf pme g h n Ma er m foo t tw nu ea fa anu ctu fa r c Re re o tur pa f f ing ir ur of n m itur et al e ite m s

0

JJNetwork effect

0

JJWithin effect

Source: 2012 input-output table (5-digit sectors), National Bureau of Statistics of China. Notes: For each sector, bars show shares of input from within the sector and from the network (other sectors) weighted by size in the total economy.

The methodology can distinguish between the direct impact (‘own effect’) and the indirect impact (‘network effect). Network effects are constructed using input-output tables (similar applications can be found in, for example Acemoglu et al. 2016). Each entry in an input-output table corresponds to sales of inputs between (continued) 1

34

This box was prepared by Ergys Islamaj, Francesca de Nicola and Jinxin Wu.

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

(Box I.B.2 continued)

industries at a very disaggregated level. The network effect for a downstream industry will depend on the share of that industry’s sales to another (upstream) industry.2 This corresponds to the inputs (sales of the downstream sector) needed by the upstream sector to produce one dollar of output. Under standard theoretical assumptions, downstream propagation effects will directly depend on these input shares. Similarly, upstream propagation effects will be a function of sales of an upstream sector to a specific downstream one. The network (indirect) propagation channel in China is nontrivial and can amplify disturbances throughout the economy. For non-manufacturing sectors, downstream and upstream industries determine input costs in China as much as own effects (Figure BI.B.2.1).3 A closer look at manufacturing sectors indicates that shocks to those industries have the potential to amplify through network effects as well, with the largest network linkages in manufacturing of metals, food processing, chemicals, and electrical equipment. Both downstream and upstream network linkages are significant, suggesting that demand and supply shocks have a potentially sizeable impact on the economy. Shocks can propagate through sectoral networks, whose composition and strength vary spatially. Figure BI.B.2.2. Regional network effects A. Downstream propagation Percent 8 7 6 5 4 3 2 1

an

ng

ha

i

xia ng

Ni

ou

in Ha

u

izh Gu

g

ns Ga

an

ian

nn

nj Xi

in gq

Yu

Qi

Ch

on

gx

i

g

in Gu

Jil

jia ng

ilo He

In

ne

an

ng

i nx

Sh

an

xi

in

aa Sh

xi

nj

ng Jia

Tia

iji Be

go

ng

lia

n

Sh

rM

on

i

jia Fu

n

be Hu

i

na Hu

hu

ai an

gh

hu

An

an

g

Lia

Sic

on

in

i

n

be He

g

na He

g

an

on

eji

gd an

Gu

Zh

do

Sh

an

Jia

ng

su

ng

0

JJNetwork effect

JJWithin effect

B. Upstream propagation Percent 8 7 6 5 4 3 2 1

Jil in Gu an Ch gxi on gq in g Yu nn an Xi nj ian g Ga ns u Gu izh ou Ha in an Ni ng xia Qi ng ha i

g

ng

jia n

xi an ilo

Sh

aa

nx

i

in nj Tia

xi

a

ng iji

ng Jia

Sh He

ne In

Be

go li on

i

jia n Fu

rM

n

be Hu

i

na Hu

hu

gh an Sh

An

ai

g

an hu

Sic

in on

Lia

n

be i He

na He

g eji

an

ng gd o

an Gu

Zh

ng do an

Sh

Jia

ng su

0

JJNetwork effect

JJWithin effect

Source: China multi-regional input-output (MRIO) table 2012, Mi et al. (2018). Notes: For each sector, bars show shares of input from within the region and from the network (other regions) weighted by size in the total economy.

The transmission of shocks also occurs through regional networks. Analysis of geographical networks uses data from Mi et al. (2017) on input-output linkages across 30 industries and 30 regions in China. Again, the (continued) 2 3

Normalized by total costs of the downstream industry. Comparison with results from 2002 input-output table suggest that these results are similar across time.

I.B. Outlook and Risks

35

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

(Box I.B.2 continued)

network effect appears to be sizeable and can potentially play an important role in the propagation of shocks across sectors (Figure BI.B.2.2). The own and network effect are computed accounting for linkages internal and external to the region and depending on the sectoral composition of each region. The own effect may capture the spillovers of disturbances through local labor markets. For example, if a large employer in a given region shuts down, this will reduce employment and output of other local firms in other sectors that were serving the nowclosed company. The network effect would then capture the changes in demand that are indirectly attributable to the closure of the company. Both the local (own) propagation channels (inter-sector, intra-region) and the network channels (inter-sector, inter-region) are nontrivial and can potentially amplify sector and region-specific fluctuations. Network linkages appear to be economically Figure BI.B.2.3. Network effects and the economy significant and have the potential to propagate Percent 35 disturbances across China’s economy. The inter30 sectoral linkages in both downstream and upstream 25 networks account for about 30 percent of total 20 economic activity in China (Figure BI.B.2.3). For the 15 manufacturing sector, input costs account for about 10 20 percent of total economic activity. Intuitively, the 5 analysis presented here suggests that sector-specific 0 Downstream Upstream shocks will significantly affect economic activity in JJAll sectors JJManufacturing other sectors through input-output linkages. For Source: 2012 input-output table (5-digit sectors), National Bureau of Statistics of China. example, ongoing trade tensions may directly affect Note: Bars show network effects as a share of total economic activity. the steel industry but, through input-output linkages, the effects can propagate to the coal industry as well as others. The analysis of regional networks can indicate which region stands to lose most by such contractions. Acemoglu et al. (2016) find that the network effects for the United States are statistically and economically important.4 Overall, the significant size of these network effects suggests that policymakers should consider direct shocks as well as their indirect propagation through space and sectors, to more accurately estimate the potential economic impact. 4

A one standard deviation increase in imports from China will have a direct effect of reducing value-added growth by 3.5 percent in 10 years, and a network effect six times larger. The estimated effects on employment are of a similar size.

The trade tensions seen in the first half of 2018 evolved into disputes, primarily between the United States and China, and pose a significant risk for the region (Box I.B.3). This is mainly due to the uncertainty they bring to established trade relationships. The risks to regional economies (other than China) stem from their relatively high level of integration in regional and global value chains. Sentiment has improved over the past couple of months as both sides began negotiations to breach the impasse. In February 2019, reports indicated that the deadline for an agreement had been pushed back due to progress in negotiations. Negotiators from both sides met at the end of March to try to reach common ground. These announcements and reports allayed fears of an escalation of protectionist policies and the risks that these would potentially have had on already faltering global trade momentum. While United States and Chinarelated trade tensions have abated somewhat, risks of new sources of trade tensions have emerged recently with the United States intending to remove tariff exemptions on goods imported from India and Turkey.

36

PART I. RECENT DEVELOPMENTS AND OUTLOOK

MANAGING HEADWINDS

Box I.B.3. Do U.S. import tariffs on Chinese goods have bite? Preliminary estimates of the effects on U.S. imports1 Tariffs on Chinese imports to the United States increased during 2018, while both sides continue to work on an agreement to end trade tensions. The United States increased import tariffs by 25 percentage points on 1,097 products imported from China through two rounds of measures in July and August 2018, and a more sizeable third tranche, which came into effect on September 24, 2018 (Table BI.B.3.1).2 This box provides preliminary estimates of the short-term trade impact of these increases in U.S. tariffs on Chinese imports. Specifically, it studies the cumulative effects of tariffs on U.S. imports of goods subject to the tariffs, and imports from China versus from the rest of the world.3 Table BI.B.3.1. Value of U.S. imports from China targeted by tariff measures

1st tranche 2nd tranche 3rd tranche Total

Value of target imports in the first announcement ($ billion)

Value of target imports at effective date ($ billion)

32.3 (April 3) 13.8 (April 3) 197.2 (July 10)

32.3 (July 6) 13.7 (August 23) 188.9 (September 24) 234.8

Source: World Bank staff estimation on the basis of various USTR published documents (see footnote 3 for details) and United States import data from the United States Census Bureau.

The imposition of tariffs reduced U.S. imports from China. An increase in the tariff on Chinese imports by 10 percentage points reduces U.S. imports of those Chinese products by 14 percent on average. The estimate of the change in imports from China will be biased if importers increased their imports from China immediately after the announcement of the tariff increase but before implementation (Table BI.B.3.1).4 Such ‘front-loading’ of imports appears to have been significant. An announced tariff increase of 10 percentage points on Chinese goods induces an increase in U.S. imports of those goods from China by 9.5 percent more than from the rest of the world before implementation. In addition, the estimate will be biased if the imposition of a tariff on Chinese goods affects imports from the rest of the world (see below). However, neither excluding from the regression the observations between announcement and implementation, nor correcting for changes in U.S. imports from the rest of the world, changes the results significantly.5 Surprisingly, the rise in tariffs on imports from China reduced imports of the same products from other countries. An increase in the tariff on Chinese goods by 10 percentage points is associated with a reduction in other countries' imports of the same product to the United States by 7.2 percent, compared with non-affected products (the estimate compares the difference in pre- and post-tariff imports in the products affected by tariffs

(continued) 1 2 3

4 5

This box was prepared by Massimiliano Calì and Hazmi Ash Shidqi. Complete lists of goods published by United States Trade Representative (USTR): www.ustr.gov. The third tranche was subject to an initial increase in import tariffs by 10 percentage points, which was supposed to be followed by an increase to 25 percentage points by January 1, 2019. However, the two countries in December 2018 eventually reached an agreement for a postponement of the scheduled January 2019 tariff increase. The analysis uses monthly U.S. import data (at the HS 10-digit level) for January 2017 to December 2018 period. The approach is similar to that in Frazer and Van Biesebroeck (2010), in that the annual percentage change in monthly imports from China and the rest of the world are regressed on the tariff rate imposed by the United States on Chinese goods, on the interaction between the tariff and the post-implementation period, as well as on the interaction between each of these variables and a dummy for China while controlling for all time-varying factors for China and the rest of the world. Specifically, the baseline regression can be written as: ΔMitj = γtj + ρ1 τi + ρ2 τi diτ + ρ3 τi dC + ρ4 τi dC dτ + εitj (1), where ΔM is the 12-month difference in log of 1+ US import value in product i from country j (where j is China or Rest of the World); γtj is country-time effects, τi is the tariff rate imposed by the United States on Chinese goods, diτ is a dummy which takes the value 1 in the months after the implementation of the tariffs for each product, dC is a dummy for China and εitj is a i.i.d. error term. The estimated parameters ρ1, ρ2, ρ3 and ρ4, will capture the effects of tariffs on product i imports to the United States, as well as any effect that is specific to tariffs from China and to the time period during which the tariffs are implemented. Goldman Sachs (2018), using aggregate import data, speculate that this may have indeed been the case. Specifically, the estimated Chinese tariff elasticity of import from the world is used to estimate the extent to which U.S. imports from the rest of the world are impacted by the tariff. This allows us to purge the spillover effect on imports from other countries from the estimated Chinese import elasticity of the tariffs.

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(Box I.B.3 continued)

with the same difference for the non-covered products).6 This is lower than the elasticity for imports from China, but it still signals a large reduction in overall U.S. imports of the affected products. This implies that during this particular time of increased trade tensions not only imports of affected products from China but also imports of the same products from other countries suffered. This result is consistent with an increase in global uncertainty following trade tensions. The second half of 2018 corresponded to a period of increased uncertainty which was manifested in sharp declines in equity markets and increased bond yields (World Bank 2019d). A recent analysis using a global trade computable general equilibrium model suggests that this could indeed result in a drop in U.S. imports of affected products both from China and from other countries (World Bank 2018a). Importers in the United States may be postponing all of their purchases from abroad of affected products in hopes that trade tensions will ease, or production will relocate out of China. Alternatively, some of the production in China may have already relocated to the United States, which displaces both imports from China and from other countries.7 Finally, U.S. importers may be switching to other substitute products that may not be subject to tariffs. However, it is beyond the scope of this note to investigate such cross-product spillovers effects. The reduction in U.S. imports from China and other countries is estimated to be worth several billion dollars. Up to December 2018, the tariffs on Chinese goods are estimated to have reduced U.S. imports from China by US$16.6 billion and U.S. imports from the world by US$66.1 billion (Table BI.B.3.2).8 While very preliminary, these figures indicate that the size of the shock has been relatively large, and perhaps more abrupt than expected given the increase in uncertainty and possible lack of replacement to temper the tariff increase. Countries in the region appear to have been less affected by the tariff increases than countries in other regions: the tariff increase is associated with some rise in U.S. imports from Vietnam and perhaps the Philippines, and the impact is positive but not significantly different from zero for Indonesia and Malaysia.9 By contrast, the tariff increases on Chinese goods significantly reduced U.S. imports from the rest of the world. Table BI.B.3.2. E stimated effects of U.S. tariffs on U.S. imports from China and overall ($ million)

China World

Overall

First tranche Jul–Dec 2018

Second tranche Sep–Dec 2018

Third tranche Oct–Dec 2018

-16,600 -66,108

-6,637 -42,378

-2,022 -6,858

-7,940 -16,872

Source: Authors’ calculations on the United States Census Bureau (for imports) and USTR (for tariffs) data.

(continued) 6 7 8 9

38

More formally, the analysis utilizes a diff-in-diff estimation as follows: MitW = γt + ω1 τi + ω2 τi diτ + εit  where the elasticity of U.S. imports from the world with respect to the tariff is (ω1) ̂+ (ω2) ̂. A new survey by UBS (2019) provides evidence of manufacturing companies in China that have recently relocated their production to the United States. The estimated elasticities are multiplied by the applied import tariff rates and the values of U.S. imports in the affected products during the relevant months of 2017. These estimates are not directly comparable with the results in World Bank 2018a due to differences both in focus of study and methodology. That study focused on the change in the share of Malaysian products competing with Chinese products in U.S. imports, rather than the effects of tariffs on exports to the United States of all the products subject to tariffs.

PART I. RECENT DEVELOPMENTS AND OUTLOOK

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(Box I.B.3 continued)

While preliminary, these results point to a negative Figure BI.B.3.1. Short-run elasticity of U.S. tariffs on Chinese goods on U.S. imports from impact of the U.S. tariffs on imports from China Southeast Asia and from other countries. Exporters from China may Elasticity, 95 percent confidence intervals 0.6 not have adapted yet to the new tariff conditions— 0.4 perhaps waiting for a reversal of the tariff increase— 0.2 or may have moved production out of China in the 0 aftermath of the tariff hike. To the extent that this shortterm import decline is a sign of uncertainty around -0.2 the reconfiguration of global supply chains, the tariffs -0.4 could have negative repercussions across the global -0.6 -0.8 economy. That may provide a call for the parties to Vietnam Philippines Indonesia Malaysia Thailand RoW Authors’ calculations on the United States Census Bureau (for imports) and USTR (for tariffs) resolve the trade dispute rapidly to prevent the further Source: data. deterioration of business confidence. The opportunity Note: The box plots define 95 percent confidence intervals. to step up production and exports to replace exports from China to the U.S. market seems generally more difficult to exploit than initially envisaged, even in East Asia, an area that shares many characteristics with China (Calì 2018). That may suggest that other countries in the region may need to be more pro-active in attracting productive investments. This would include slashing trade and investment barriers that reduce the attractiveness of investing, producing, and trading from these countries.

A trade deal between the United States and China will alter the trade and financial landscape in the region and could trigger trade diversion. While a trade deal between the United States and China is still pending, various reports suggest that China has committed to increase its purchases of United States agricultural commodities, energy products, and manufactured goods over the next few years in an effort to decrease the bilateral current account deficit between the two countries.9 This implies that a successful trade deal could entail a combination of ramped-up production in the United States and global reconfiguration of trade to satisfy the terms of a deal. As a result, in the short term, the region’s developing economies may lose market share in China in the categories targeted for increased imports from the United States. The developing East Asia and Pacific region remains vulnerable to risks of disorderly financial market developments. Any unanticipated developments in financial markets could see the return of the financial market volatility experienced in 2018. Uncertainty about monetary policy trajectory could materialize into exchange rate volatility and potentially see a return of the depreciation seen last year. The pressure on central banks in the region is to keep a neutral stance and any moves to cut interest rates (especially given that the likelihood of a U.S. Federal Reserve interest rate cut has increased to 90 percent) would add more downward momentum to currencies at a time when many countries are grappling with pressures on widening current account deficits or narrowing surpluses. While the risks related to tightening financing conditions have eased, countries in the region are still faced with tighter conditions than in the beginning of 2018. While one financial market-related risk has abated, another potential source has emerged with a recent surge in safe-haven demand for government bonds. Yields on 10-year bonds in countries such as Australia and New Zealand have dipped to historical lows and have slipped to negative territory in Germany. In the United States, the yield curve has inverted with the yield on 10-year bonds falling to below yields offered on short-term bonds. Yields 9

Possible goods that the United States and China have discussed during negotiations include agricultural products (soybeans, meat, corn), energy (coal, oil), LPG (propane, butane, ethylene, propylene, butylene, butadiene, hydrocarbons), LNG, motor vehicles (passenger cars and parts), aerospace (large aircraft and parts), and high-tech electronic goods (semiconductors, circuits, telephones and cellphones, office machines and parts, LED lamps).

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

in the developing East Asia and Pacific region have not seen a commensurate upward spike that typically accompanies a surge in safe-haven demand but, given the region’s historical vulnerability to sudden reversals in capital flows, any sustained market pessimism could pose challenges for several regional economies. A severe adjustment in global financial markets would have potentially significant valuation effects for the PICs’ sovereign wealth funds. Severe adjustments would have adverse consequences for future fiscal sustainability in the Federated States of Micronesia, Kiribati, Nauru, Palau, the Republic of the Marshall Islands, and Tuvalu. Given that these funds often support critical government expenditures such as health services and education, and act as a fiscal buffer against external shocks, severe global financial markets disruptions could leave these economies in a vulnerable position. Another major source of risk to the PICs is commodity price volatility. Many PICs are heavily dependent on imported food and fuel, so any sharp movements upward would have negative consequences for trade balances in the region. Given that most PICs are vulnerable to natural disasters, an ongoing risk to their outlook is the advent of new natural disasters, especially since countries such as Fiji, Papua New Guinea, and Tonga are still recovering from recent disasters.10 If financial market disruptions translate into risks related to sharp exchange rate movements, these could create pressure on balance of payments, and fiscal and debt sustainability. Papua New Guinea could face pressure from exchange rate volatility linked to global commodity price and local investment cycles in its large extractive sector. Several PICs either use the U.S. or the Australian dollar as their national currencies, or have their national currencies pegged to a currency basket of their main trading partners. All PICs are highly import dependent, with manufactures imports from China and fuel representing a large share of their import bills, thus making them highly vulnerable to international currency fluctuations. PICs with significant assets (held in sovereign wealth funds), or debt denominated in U.S. dollars are also exposed to currency risks. Finally, PICs with large tourism sectors are also exposed to exchange rate volatility as it affects their price competitiveness (with China already being an important source market for Palau and gaining in importance in other Pacific tourism destinations). Developing East Asia and Pacific countries will need to ensure they have adequate fiscal space in the event of the downside risks materializing. Solid growth and a focus on collecting more and spending better have helped some countries in the region to keep debt burdens contained and fiscal balances broadly stable (Figure I.B.2 and Figure I.B.3). For many countries in the region, 2018 saw the widening of current account deficits, which resulted in pressure to maintain fiscal discipline. Policy focus in the near term will need to center on strengthening buffers, especially as a means of managing global headwinds. The government of Indonesia maintained fiscal discipline by ensuring its fiscal deficit in 2018 (1.8 percent of GDP) was well below the mandated ceiling (3 percent of GDP), and it is expected to remain well below this ceiling over 2019–20.11 Authorities in Malaysia are expected to renew fiscal consolidation efforts in 2019 after an expansionary stance in 2018 that coincided with presidential elections in the middle of the year. The focus in 2019 in Malaysia will be on rigorous expenditure rationalization, especially since revenue collections might be affected by consumption-related tax concessions. In other countries in the region, such as Cambodia, Myanmar, the Philippines, and Timor-Leste, the fiscal outlook is tempered by pressure related to fiscal sustainability in the longer term. For example, public servant wage bills are expected to increase significantly in Cambodia and personnel expenditure has already increased alongside infrastructure-related expenditure in the Philippines.

10 Papua New Guinea is recovering from a major earthquake in Hela Province in February 2018, Fiji is recovering from Tropical Cyclone Winston, and Tonga is recovering from Tropical Cyclone Gita. 11 The 1.8 percent of GDP figure for Indonesia is based preliminary estimates released by the Indonesian Ministry of Finance.

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PART I. RECENT DEVELOPMENTS AND OUTLOOK

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Figure I.B.2. F iscal deficits are expected to remain at similar levels to the recent past

Figure I.B.3. Government debt is expected to remain contained

General government fiscal balance (percent of GDP), average 2018–20

General government debt (percent of GDP)

10

90 80

8

70 60

6 50 4

KHM

MMR CHN FJI

40

LAO VNM MYS

30

PHL

THA 2

20

IDN

10

MNG

0 0

2

4

6

8

0 CHN

10

Average 2015–17

JJ2015

Source: World Bank staff estimates. Note: Data refer to general government fiscal deficit, except for Indonesia, where they refer to central government fiscal deficit, and Cambodia, where they refer to general government fiscal deficit before grants.

IDN

MYS

JJ2016

PHL

THA

JJ2017

VNM

JJ2018

KHM

LAO

JJ2019

MNG

JJ2020

Source: World Bank staff estimates. Note: Data refer to general debt, except for Indonesia, where data refer to central government debt. Data for China exclude significant off-budget debts for public investment accumulated since 2015.

PICs remain at high risk of debt distress due to thin capacity to carry debt, modest long-term economic growth prospects, and high vulnerability to natural disasters. Public debt in most PICs is lower than in most other regions of the world. The debt is mostly external except in Fiji and Papua New Guinea. Nonetheless, of the nine PICs for which the IMF and the World Bank publish debt sustainability analyses, six are rated as being at high risk of debt distress and three at moderate risk. The fact that most PICs are at an elevated risk of debt distress despite their relatively moderate debtto-GDP ratios is due to structural factors, including modest long-term economic growth prospects, high vulnerability to natural disasters, and thin capacity. Many PICs have recognized these structural debt vulnerabilities by adopting explicit debt ceilings and by committing to refraining from non-concessional borrowing. Figure I.B.4. Total debt levels are reasonably contained Panel A. Developing East Asia

Panel B. Pacific Island Countries

Percent of GDP

Percent of GDP

350

70

300

60

250

50

200

40

150

30

100

20

50

10

0

0 MNG

JJExternal debt

LAO

MYS

KHM

VNM

IDN

JJDomestic debt

THA

MMR

PHL

CHN

WSM

JJExternal debt

TUV

TON

VUT

RMI

NRU

FSM

PLW

KIR

FJI

PNG

SLB

JJDomestic debt

Source: Debt Sustainability Analysis. World Bank staff calculations.

Overall, total debt levels in the developing East Asia and Pacific region remain contained. Total debt is the highest in China and Mongolia (compared with GDP), but this does not signal a high risk of debt distress (Figure I.B.4). For Mongolia, the bulk of the external debt is inter-company borrowing in the mining sector. In many cases, such

I.B. Outlook and Risks

41

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

borrowing can be considered as FDI (when the contracting companies are affiliated). Also, as a result of the strong economic recovery and improved fiscal outcomes, the public debt ratio has started to decline in Mongolia. For China, more than 90 percent of the debt is domestic. The debt-to-GDP ratio in China has stabilized since 2016, led by the corporate sector. While Malaysia, Thailand, and Vietnam also have relatively high levels of total debt, the large majority is domestic. The debt-carrying capacity of these countries is high because of their high levels of GDP growth (Malaysia and Vietnam) and their deep financial markets, which facilitate access to borrowing at competitive interest rates and debt rollover (Malaysia and Thailand). Cambodia and Lao PDR may be at higher risk of debt distress because of the high share of external debt in their total debt, and their shallow financial markets.

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1.C. Policy Considerations In the context of moderating global growth and faltering global trade momentum, the priority for countries in developing East Asia and Pacific will be on ensuring a growth pattern that is sustainable and supported by macroeconomic fundamentals to buffer against future disruptions in the global economy. An important shortterm policy consideration involves rebuilding buffers that may have eroded in 2018. In the medium term, policy considerations will need to focus on closing critical gaps in physical, human and natural capital, improving private sector opportunities, boosting competitiveness, and ensuring social protection measures are adequate.

Policy considerations in the short term will need to address increasing global headwinds Countries in the region would benefit from some policy focus on rebuilding the buffers that were eroded in 2018 due to global economic developments. In the short term, countries could replenish international reserves that were drawn onto as central banks managed currency volatility in 2018. A pause in monetary policy stances should also provide some respite for regional economies that had to raise policy rates to defend depreciating currencies and mitigate adverse impacts on current account balances, especially as many regional currencies have recovered from the turbulence in 2018. Moreover, the larger regional economies’ real policy rates are well above their long-term averages. The notable exception to this trend is China, where the authorities have adopted a more accommodative stance to manage the moderation in economic growth. The PICs will need to strengthen fiscal buffers (Box I.C.1). Countries in the North Pacific (the Federated States of Micronesia, the Republic of the Marshall Islands, and Palau) all currently have fiscal surpluses, but sector grants provided by the United States under its Compacts of Free Association are expected to expire during the next few years, leaving them with potentially significant fiscal gaps if income from their trust funds is insufficient to compensate for the loss of these grants. Countries in the South Pacific (Samoa, Tonga, and Vanuatu) are also facing challenges in maintaining prudent fiscal policy stances in light of natural disaster-related reconstruction efforts and infrastructure gaps. Central Pacific countries are facing similar challenges with regards to maintaining fiscal discipline. Several PICs receive significant revenue from access fees to their fisheries under the Vessel Day Scheme under the Parties to the Nauru Agreement. However, these revenues are volatile from year to year and subject to longer cycle structural shifts due to changes in climatic conditions (El Niùo and climate change). Thus, maintaining adequate buffers to deal with this volatility is essential for these countries. High levels of debt and reliance on commodity exports may constrain government policies. Several regional economies have substantial debt denominated in U.S. dollars and have had to manage with currency depreciation over the course of 2018. Furthermore, many countries in the region are reliant on commodity-based revenue, which makes them highly susceptible to exogenous shocks. In Malaysia, for example, the relatively high level of government liabilities and increased reliance on oil-based revenue could constrain the flexibility of fiscal adjustment in response to future macroeconomic shocks. Timor-Leste’s reliance on its Petroleum Fund would need to be addressed, as its balance has shrunk due to unexpected withdrawals and lower petroleum-related revenues.

I.C. Policy Considerations

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Box I.C.1. Debt in the Pacific Island Countries1 Despite low levels of public debt, most Pacific Island Countries (PICs) are assessed as being at high risk of debt distress. In 2017, the average public debt-to-GDP ratio for the Pacific Islands stood at 38.1 percent, compared with 94.4 percent in East Asia and 49.8 percent in the Caribbean (IMF 2018a). And private nonguaranteed debt levels are not high in most PICs (Figure BI.C.1.1). Nevertheless, of the nine PICs for which the IMF and the World Bank publish debt sustainability analyses, six are rated as being at high risk of debt distress and three at moderate risk.2 These high debt distress ratings are due to structural factors, including modest long-term economic growth prospects, high vulnerability to natural disasters, high infrastructure and public services costs, and thin capacity for economic management. Figure BI.C.1.1. D ebt-to-GDP ratio for selected Pacific Island Countries

Figure BI.C.1.2. Economic growth in the Pacific: History and projections

Percent of GDP

Annual average growth rates, percent

70

4.0

60

3.5 3.0

50

2.5 40 2.0 30

1.5

20

1.0

10

0.5 0

JJPPG external debt (nominal)/GDP

JJPOPG domestic debt (nominal)/GDP

Source: IMF-World Bank Debt Sustainability Analysis, the latest year available. Note: Public and publicly guaranteed debt.

17 20

17

6

B SL

PN

G

20

01

16 20

I2 FJ

KI

R

15

16

20

20

W

FS

M

20 U NR

PL

7

16

6 RM

I2

01

01

16

T2 VU

20 N TO

V TU

W

SM

20

20

16

16

0

-0.5 PNG

SLB

VUT

JJHistorical 10-year average

RMI

WSM

FJI

KIR

TUV

TON

PLW

FSM

JJLong-term projection (2020–40)

Source: World Bank 2017b. Notes: Real GDP growth historical averages and projections based on IMF Article IV reports and IMFWB Debt Sustainability Analyses. Population data and projections from the UN.

The economic geography of the PICs severely constrains their long-term economic growth prospects and thus their capacity to take on and service debt. Small population sizes, extreme remoteness, geographic dispersion, and environmental fragility limit the range of activities in which these countries can be internationally competitive. Real per capita growth in most small PICs averaged below 2 percent over the period 2005–15 (Figure BI.C.1.2). A favorable international economic environment and policy reforms to take full advantage of economic opportunities inherent in tourism, fisheries, deep-sea mining, labor mobility, and ICT-related activities could boost per capita growth to 2 to 3 percent (World Bank 2017a). Nevertheless, growth projections of most debt sustainability analyses for the PICs appropriately reflect the historically low growth performance as the baseline. Although public investment needs are large, economic returns tend to be low. Required infrastructure, including adaptation measures to climate change, would require additional annual spending of about four percent of GDP (ADB 2017). The economic geography of the Pacific, with small populations dispersed over a large number of remote islands, results in high investment costs and low economic returns to infrastructure. Improved transport and ICT connectivity, improved water and sanitation systems, or increased access to electricity are (continued) 1 2

44

This box was prepared by Robert Utz. Kiribati, the Federated States of Micronesia (FSM), the Republic of Marshall Islands (RMI), Samoa, Tonga, and Tuvalu are assessed as being at high risk of debt distress. Papua New Guinea (PNG), the Solomon Islands, and Vanuatu are assessed as being at moderate risk of debt distress.

PART I. RECENT DEVELOPMENTS AND OUTLOOK

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(Box I.C.1 continued)

important for improved standards of living but often does not generate sufficient growth dividends and financial returns that could be used to service the debt incurred. Severe vulnerability to natural hazards and climate change not only hampers economic growth prospects, but post-disaster rehabilitation and reconstruction efforts often trigger episodes of rapid debt accumulation. Expected annual losses due to natural hazards—especially tropical cyclones, but also earthquakes, tsunamis, volcanic eruptions, and others—are among the highest in the world, estimated at 6.6 percent of GDP for Vanuatu and more than 2 percent for Fiji, FSM, and Tonga. The cost of recovery and rehabilitation efforts are high and have in many cases (for example, the 2012 tropical cyclone Evan in Samoa) triggered a rapid debt build-up when insufficient grant assistance was available. Weak debt-carrying capacity of most PICs contributes to the elevated levels of debt distress. All PICs except for Samoa and Vanuatu were assessed as having weak debt-carrying capacity, based on the World Bank’s annual assessment of countries’ policies and institutions (CPIA). The revised IMF/WB debt sustainability framework, which came into force in 2018, uses a composite indicator of five components (the CPIA, GDP growth, reserves, remittances, and global growth). This framework shows a stronger debt-carrying capacity for five of the nine PICs, so that future assessment could indicate lower levels of debt distress. While the capacity of most PICs to carry and service debt is extremely limited, their financing needs are structural and large. The levels of domestic revenue mobilization in most PICs are consistent with their level of development. However, the cost of public service delivery is significantly higher than in other countries due to the small size and geographic dispersion of the PICs, resulting in large structural fiscal deficits (World Bank 2016). Most countries are highly dependent on imports, not only for manufactured goods but also for food and fuel, while exports of goods and services are typically small. As a consequence, most of the PICs have structural, longterm external financing needs. Foreign aid in the form of grants and, for some countries, income from sovereign wealth funds, have been the primary source for filling the fiscal financing gaps. Overseas remittances often also make an important contribution to filling the balance of payments financing gaps. PICs and their main development partners have adopted policies that respond to these structural debt vulnerabilities. Many PICs have adopted explicit debt ceilings and have committed to refraining from nonconcessional borrowing. The major bilateral traditional development partners to the Pacific—Australia, Japan, New Zealand, and the United States—as well as the European Union, provide virtually all their development assistance in the form of grants. The World Bank and the Asian Development Bank’s financing terms also take the countries’ debt vulnerabilities into account. A significant share of external debt accumulation (from China) has been used for financing needs after natural disasters (Samoa) or domestic unrest (Tonga), when insufficient grant assistance was available for reconstruction (Fox and Dornan 2018). In recent years, China has significantly scaled up its engagement with PICs and reportedly put aside $2 billion for financial support to PICs and $4 billion for Papua New Guinea.

(continued)

I.C. Policy Considerations

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

(Box I.C.1 continued)

The World Bank and other development partners are supporting PICs in managing their high structural risk of debt distress. This includes the macro-fiscal dialogue for the adoption of sustainable fiscal and debt policies, often in the context of budget support engagements, such as in Fiji, Kiribati, Papua New Guinea, the Solomon Islands, Samoa, Tonga, and Tuvalu. Furthermore, the World Bank is providing technical assistance for several PICs for the design of medium-term debt strategies and regular training, typically jointly with the IMF, on the debt sustainability framework. Economic policies in PICs need to take into account the high potential for debt distress. The adoption of medium-term debt strategies and the pursuit of fiscal policies that recognize the PICs’ structural risk of debt distress and their very limited capacity to carry and service debt are essential. In practice, this will typically imply that the scope for debt financing—especially non-concessional, but in many cases also concessional—of public expenditure will be very limited for most PICs, especially the smaller ones. Considering that most PICs have extreme vulnerability to natural disasters and other external shocks, building and maintaining adequate fiscal buffers is equally important, especially as debt financing is in most cases not a feasible and fiscally sustainable response to an external shock. For development partners and other potential providers of external finance to the PICs, their structural risk of debt distress should be taken into account in decisions on the terms and volumes of financing provided.

Moderating global economic activity heightens the urgency associated with undertaking medium-term structural reforms Given the broader slowdown in the global economy, policymakers in the region will need to redouble their efforts to create an economic environment that supports sustainable growth, close critical gaps, such as human capital, while making suitable investments in physical and natural capital, and building resilience to climate change. In several of the larger regional economies, addressing significant capital gaps—both physical and human— will be critical to ensuring sustainable growth in the medium term. Sustaining medium-term growth and ensuring that gains from growth are shared broadly will require measures to spur productivity, particularly in services, and to increase the quantity and quality of capital, including human capital. Investing in human assets is particularly important in the developing East Asia and Pacific region given the prevalence of relatively high stunting rates (Box I.C.2). Stunting rates (for children under the age of five) in Cambodia, Indonesia, and Myanmar, are close to 30 percent and in Vietnam the rate is 25 percent. Stunting can result in lower productivity, lower life-time earnings, lost job opportunities, and lower potential economic growth. Investing in human capital, beginning with adequate nutrition in the first 1,000 days of a child’s life, is critical to ensuring the high-quality learning outcomes required for the developing East Asia and Pacific region to continue to transition to higher incomes. In addition to continuing to invest in human capital overall, there is a need to develop the skills required for succeeding in the 21st century economy, including higher-order cognitive, socioemotional, and technical skills (Mason and Shetty 2019).

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Box I.C.2. The unfinished agenda for investing in East Asia and Pacific’s people1 Human capital consists of the knowledge, skills, and health that people accumulate over their lives, enabling them to realize their potential as productive members of society. The World Bank Group’s Human Capital Project (HCP) is designed to help countries to focus sustained attention on human capital outcomes, which covers a broad range of issues (mobilizing resources, improving spending efficiency, strengthening regulation and governance, improving the investment climate, empowering women and girls, and raising public awareness and demand for better services). The HCP also highlights the benefits of coordinated action across sectors, such as health, education, social protection, agriculture, water and sanitation, roads, and power, among others. On average, countries with higher shares of social sector spending over GDP display better human capital outcomes, but improving the efficiency of spending is also key. The recently launched Human Capital Index (HCI) measures the human capital of the next generation, using three components.2 These are: (i) survival, measured by the under-five mortality rate (children born today need to survive until the process of human capital accumulation through formal education can begin); (ii) schooling, measured by the expected years of school adjusted for the amount of learning that takes place (the latter is indicated by countries’ relative performance on international student achievement tests);3 and (iii) health, measured by the rate of stunting for children under the age of five and the share of the population of 15-year-olds who will survive until the age of 60. The HCI reveals the productivity that a child born today can expect to achieve in view of the risks to poor health and poor education currently prevailing in the country where that child lives.

What is the state of human capital across East Asia and Pacific? Children born in developing East Asia and Pacific will be 53 percent (Table BI.C.2.1) as productive as they could be if they benefited from complete education and full health. This puts the region behind Latin America and the Caribbean (LAC) (HCI = 0.55) and Europe and Central Asia (ECA) (HCI = 0.63). Girls rank higher on each indicator than boys. The region’s comparatively low HCI reflects several issues. Many countries have a large learning gap (Figure BI.C.2.1). Student learning outcomes are in crisis in many countries, and lack of access to essential quality health services and social safety nets disproportionately affects the poorest and most disadvantaged. In addition, stunting remains high in several countries. Many countries across the region are experiencing a substantial learning gap (Figure BI.C.2.1). On average, children born in developing East Asia and Pacific are expected to complete almost 11.2 years of education by the age of 18. However, when adjusted for learning, they have only completed 7.4 years, suggesting a learning gap of 3.8 years. The highest learning gap in developing East Asia and Pacific is 4.59 years (in Vanuatu) and the smallest is 0.98 years (in Singapore). Even in Malaysia, which has the highest per capita income in the region, the learning gap is a high 3.1 years. (continued) 1 2 3

This box was prepared by Amer Hasan and Leslie K. Elder. For details on the HCI methodology, see Kray (2018). For details on the Harmonized Learning Outcomes (HLO) methodology, see Altinok et al. (2018).

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(Box I.C.2 continued)

Table BI.C.2.1. The Human Capital Index – a global overview EAP Male + Female

ECA Male + Female

LAC Male + Female

MENA Male + Female

SAR Male + Female

SSA Male + Female

0.97

0.99

0.98

0.98

0.96

0.93

11.24 409.63 7.43

12.45 463.80 9.26

11.86 405.08 7.69

9.46 381.60 6.05

10.39 364.21 6.19

8.10 374.42 4.94

0.83 0.76 0.53

0.86 0.88 0.63

0.86 0.87 0.55

0.87 0.80 0.49

0.85 0.68 0.46

0.73 0.68 0.40

Indicator HCI Component 1: Survival

Probability of Survival to Age 5 HCI Component 2: School

Expected Years of School Harmonized Test Scores Learning-Adjusted Years of School HCI Component 3: Health

Survival Rate from Age 15–60 Fraction of Children Under 5 Not Stunted Human Capital Index (HCI)

Source: World Development Indicators. Note: Unweighted averages of human capital index (HCI) for each region based on "World Bank client countries" only, where client countries are defined as “all countries that are either IBRD/Blend/IDA eligible as of FY19 classification”.

Figure BI.C.2.1. The learning gap Quality-adjusted expected years of school 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0

KOR SGP HKG JPN MKD NZL AUS CHN VNM MYS MNG THA PHL MMR TON KIR IDN KHM TUV LAO SLB TLS VUT PNG

0

1

2

3

4

5

6

7

8

9

Expected years of school QQEAP

QQOther countries

Source: World Development Indicators.

10

11

12

13

14

15

Improvements in learning have the potential to fuel growth. If Indonesia were to increase its human capital by 25 points in terms of PISA scores in the next 12 years, on a par with its historical evolution, this would add 0.08 of a percentage point to its annual long-term economic growth rate by 2027 and 0.23 of a percentage point by 2040. If Indonesia were to launch a more aggressive reform program aimed at increasing PISA scores by 100 points, bringing it close to the OECD average and Vietnam’s 2015 PISA score, higher education quality would add 0.30 of a percentage point to long-term growth by 2027 and 0.90 of a percentage point by 2040.

Stunting prevents children from achieving their full potential. In Papua New Guinea and Timor-Leste, as many as half the children under the age of five may not achieve their full potential because of stunting, or low height for age, which can affect cognitive development, school performance and adult earnings. If human capital is not nurtured equitably, countries run the risk of stagnating income levels, or of achieving growth that is not inclusive, sustainable, or adequately diversified. Larger budget allocations and more effective budget execution to support teacher training, modernization of curricula, early childhood education, improved health infrastructure, health worker training, and health commodities and equipment are all needed to improve long-term economic performance.

(continued)

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(Box I.C.2 continued)

How can developing East Asia and Pacific better invest in its people? Provide high-quality early childhood care and education. In Malaysia, improved provision of high-quality early childhood care and education programs would also enhance women’s access to the labor market and allow them to make more productive use of their human capital. Educational reform that emphasizes the development of both scientific and mathematical abilities and higher-order cognitive skills such as complex problem-solving, socio-behavioral skills, reasoning and self-efficacy is crucial to develop the complementary skills that workers need to benefit from the evolving technological context and to utilize the associated machines and equipment (World Bank 2018a). In Lao PDR, geographic location, ethnicity, and income levels impact access to preschool education. For example, 55 percent of urban children receive preschool education, compared with just 15 percent of rural children. Improve access and education for reproductive health. In the Philippines, access and education for reproductive health remain weak. One in three children under the age of five is stunted—a key outcome of malnutrition and poor health—and there has been no progress in over a decade. This is particularly surprising, given evidence that suggests efforts to reduce stunting in the Philippines return 66 pesos for every 1 peso of investment (World Bank 2018d). Address educational and health constraints to structural change. In Timor-Leste, for instance, both educational attainment and learning outcomes are low, repetition and drop-out rates are high, the net preschool education enrolment rate is only 20 percent, and the country’s 46 percent prevalence of under-five stunting is one of the worst levels in the world. Make the elimination of inequality a priority. While Lao PDR has succeeded in reducing poverty and improved service delivery in both the health and education sectors, substantial inequities characterize this progress (World Bank 2019a). Among the highly dispersed, rural ethnic-minority populations, health and education outcomes are persistently worse, with child stunting rates as high as 50 percent.

Improving private sector opportunities will play an important role in ensuring a more sustainable growth pattern. The pressure to improve the business environment is particularly acute given that the significant currency depreciations seen throughout the region in 2018 did not appear to have provided much of a competitiveness boost to exports. This points to a deeper set of challenges requiring structural reforms. Cambodia urgently needs to focus on improving the investment climate via a reduction in business costs for energy and logistics. Indonesia would need to review its investment regulatory framework, remove import restrictions, and strengthen its skills base and productive infrastructure to attract foreign investment and boost exports. This would also help reduce the current account deficit and fund it more sustainably. The Philippines’ restrictions on foreign equity limits could be eased to attract foreign direct investment and the process for gaining tax incentives streamlined to encourage domestic private investment (IMF, 2018b). Costs of doing business are very high in Myanmar too. Given that Myanmar also has significant gaps in several areas, the government will need to commit to mobilizing the private sector to contribute in a meaningful way. On that front, the Myanmar authorities have taken steps to allow foreign stakes in domestic banks and full operations by

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2020—a move that will provide more sources of financing and a potential boost to investment. The recent creation of a customs national single window (NSW) system will help to reduce transactions costs related to investment. One developing challenge for the region’s economies will be to reverse the ongoing productivity slowdown and boost competitiveness. Governments in the region will need to maintain their commitment to the openness that has served their countries well in the recent past, despite temptations to lean toward protectionism given the current global climate. Policy focus on reforming the services sector—which remains very restricted compared with the goods sector—will be essential to capitalize on the new opportunities that trade in services and technological developments offer (Mason and Shetty 2019). Re-orienting trade policy toward services trade, with a particular focus on removing barriers to entry and fostering competition, will also go a long way in boosting competitiveness and potentially reversing the slowdown in productivity in the region (Mason and Shetty 2019). Some countries in the region, such as Malaysia and Thailand, have already begun to place policy priority on changing the ownership structure of firms (from public to private, and national to international) but have stopped short of reducing barriers to entry (Mason and Shetty 2019). Leveling the playing field between state-owned enterprises (SOEs) and private sector firms will also play an important role in fostering an environment where innovation and higher productivity flourish. Giving private sector firms (including foreign firms) greater access to longer sources of domestic financing could help fill infrastructure gaps. In the same vein, removing preferential lending agreements to SOEs—in the form of imposed lending requirements and capping interest rates—could also lead to a more efficient allocation of capital. A key dimension to renew the growth prospects of the region is fostering more innovation. To take full advantage of the benefits from innovation, policy makers need to adopt a more comprehensive view of innovation that supports accumulation of knowledge and other forms of capital, fostering firms' capabilities and appropriate incentives to innovate, facilitating the transfer of knowledge between universities/ public research institutions and industry, and strengthening government capabilities to formulate and implement adequate and effective innovation policies.

Rebalancing China’s growth model will present challenges and opportunities for the region China’s efforts to manage the rebalancing of its economy to a more consumption-focused growth model faces both internal and external constraints. China’s scope for further monetary easing is limited by the risk of a faster renminbi depreciation due to the trade tensions, as well as by the authorities’ efforts to stabilize corporate debt levels. While there is room to increase government investment spending, there are two challenges associated with such policies. First, efforts to stimulate demand should not derail the government’s core objective of reducing risk in the financial system. Relaxing the financing constraints of local government financing vehicles would risk pushing off-track recent efforts to implement the 2014 Budget Reform and place local government finance on a sustainable path. Second, any new investments should go to areas with high return. Evidence suggests that the recent deterioration in the efficiency of China’s investment is mainly centered in infrastructure and housing. These challenges provide scope for increased government spending on social services that would better protect households from economic and health shocks, and would encourage them to save less and spend more—which could raise China’s growth potential (Box I.C.3).

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Box I.C.3. Fiscal spending to support growth in China1 In 2018, concerns over China’s slowing growth and the challenging external environment have once again brought attention to the role of fiscal policy in cushioning the economic downturn. Historically, China has effectively used public infrastructure investment to stimulate the economy. While public infrastructure investment has been effective in raising growth in the short run, in China it has increasingly come at the cost of inefficient allocation of resources and a growing burden of debt. On the other hand, as in other emerging market and developing economies (EMDEs), the direct contribution to growth of higher spending on social services could be somewhat lower in the short term. However, increases in the purchasing power of households, better protection against economic and health shocks, and more inclusive health and education services would encourage households to save less and spend more in the short term, while enhancing human capital (i.e., the productivity and skills of the labor force), and thus raise China’s growth potential. China’s government capital spending is extremely high by international standards. Government investment was about 15 percent of GDP in 2011–15, compared with 6.2 and 3.7 percent of GDP, on average, for uppermiddle-income and the OECD countries, respectively (Figure BI.C.3.1). This high capital spending rate has already brought the government capital stock per worker in China up to OECD levels (World Bank 2018b). Figure BI.C.3.1. G eneral government investment, 2011– 15 average

Figure BI.C.3.2. Capital output ratio by sector

Percent of GDP

Ratio of capital to GDP

25

3.5 3.0

20 2.5 15

CHN

2.0 1.5

10

1.0 5 0.5

US$ in logs GDP per capita Source: IMF (2017), WDI, World Bank staff calculations.

JJGovernment

JJBusiness

JJInfrastructure

15

14

20

13

10

12

20

11

05

10

20

9

00

8

20

7

95

6

19

5

90

4

19

3

85

2

19

1

19

0

80

0

0

JJHousing

Source: Herd (2017), NBS, World Bank staff calculations.

High public investment, mainly in infrastructure and housing, has contributed to resource misallocations and losses in productivity. Since 2007, the efficiency of China’s investment has declined, as indicated by the rapid rise in the capital-output ratio. The infrastructure and housing sectors have seen large increases in the capital-output ratio, while the capital-output ratio in the business sector has remained stable over time (Figure BI.C.3.2). In addition, rapid growth in public investment in recent years has contributed to heightened financial risks. In 2012–16, credit to the non-financial sector grew by twice the pace of GDP, reaching almost 250 percent of GDP in 2017. Local government financing vehicle debt rose from an estimated 31 percent of GDP in 2012 to (continued) 1

This box was prepared by Elitza Mileva and Luan Zhao.

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(Box I.C.3 continued)

50 percent in 2016. By 2016, infrastructure, construction, and housing accounted for more than 40 percent of new debt of the non-financial sector. While infrastructure investment is likely to remain an important policy lever, the government has significant room to shift fiscal resources toward social spending. Over time, China has made significant improvements in public service delivery, with education expenditure doubling and health spending more than tripling as a percentage of GDP since 2000. Basic education is now universal and secondary education is on track to become universal too. Pension coverage is also relatively high for a country at China’s income level. However, health, education, and social assistance (including housing) spending, at 1.9, 3.7, and 0.9 percent of GDP in 2016, respectively, are below average compared with the upper-middle-income countries and the OECD (Figure BI.C.3.3).

Figure BI.C.3.3. Selected general government expenditures Percent of GDP 10 9 8 7 6 5 4 3 2 1 0 Health

Education

QQChina

Pensions

Social assistance

OECD

JJUMIC

Source: China Health Statistical Yearbook, China Educational Finance Statistical Yearbook, Ministry of Finance, Ministry of Civil Affairs, Ministry of Housing and Urban-Rural Development, Ministry of Human Resources and Social Security, OECD, World Bank staff calculations. Note: 2016 data for China, 2015 for the OECD.

Furthermore, China still faces disparities in the provision of public services between rural and urban areas, and across provinces. Redistribution through intergovernmental transfers is progressive, with provinces with lower GDP per capita receiving higher transfers per capita (Wang and Herd 2013). Nevertheless, transfers still do not fully compensate for the increase in regional inequality. Public spending on health and education per capita is higher in richer provinces (Figures BI.C.3.4 and BI.C.3.5). While most eastern provinces are ranked in the top 20 percent globally on the Healthcare Access and Quality index, all western and central provinces are in the bottom 50 percent (GBD 2016 Healthcare Access and Quality Collaborators 2018). With respect to education, the number of students per teacher has steadily declined, but the ratio remains lower in wealthier provinces. Access to high-quality public services also varies considerably between rural and urban areas (World Bank 2018b). Figure BI.C.3.4. P ublic spending on health by province, 2016

Figure BI.C.3.5. Public spending on education by province, 2015

Government health spending per capita

Government education spending per capita

7.8

9.0

7.6

8.5

7.4

8.0

7.2 7.5 7.0 7.0

6.8

6.5

6.6

6.0

6.4 10.0

10.5

11.0

11.5

12.0

10.0

10.5

11.0

11.5

12.0

Provincial GDP per capita

Provincial GDP per capita

Source: China Health and Family Planning Statistical Yearbook (2018), NBS, World Bank staff calculations. Note: Tibet is an outlier and is excluded.

Source: China Educational Finance Statistical Yearbook (2016), NBS, World Bank staff calculations. Note: Beijing and Tibet are outliers and are excluded.

(continued)

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(Box I.C.3 continued)

Higher, better targeted, and more efficient social spending could be used to create jobs, support disposable incomes, and stimulate household consumption and GDP growth. In health care, measures could aim at reducing individual out-of-pocket expenditures which remain high for the poor and for rural residents. More resources could also go toward hiring and retaining health-care workers in rural areas and in provinces where access to health services is relatively more limited (World Bank 2018b). Care of the elderly is another area where higher spending is needed. Similarly, public funding for education could be raised in some areas, such as early childhood education, and in villages and provinces with limited resources. In social assistance, the Dibao program, the backbone welfare program that provides a minimum income guarantee, needs to be strengthened to meet the basic needs of the poor and low-income families (World Bank 2018b). In addition, pension coverage among rural, migrant, and urban informal sector workers is relatively low and benefits are often inadequate to pay living costs. Furthermore, strengthening the social security system would encourage households to save less and consume more. A central adjustment fund was created to pool funds from the provinces and redistribute them between regions. With a more centralized pension system, workers would be able to transfer pension rights across provinces. In 2017, the government announced the transfer of 10 percent of state-owned enterprise (SOE) equity into the social security funds (World Bank 2017c). To reduce the financing gap policymakers could allocate SOE dividends and provide new capital (by issuing government bonds) to the Social Security Fund. In addition to reducing household precautionary saving, a financially sustainable social security system is likely to require lower pension contributions from workers, further contributing to higher disposable incomes and spending. Finally, to improve public service provision, the authorities need to address several challenges related to China’s fiscal system. First, the level of decentralization for social (and other) spending would have to be appropriately adjusted, with pension and other insurance schemes becoming more centralized. Meanwhile, to improve access to, and the quality of, some public services, such as health and education, local governments would need more autonomy in determining levels of social spending, and poorer provinces would benefit from an even more progressive inter-governmental transfer system.

The region’s economies will face challenges and opportunities as China rebalances. For many of the developing East Asia and Pacific countries, China is their top trade partner. Reduced demand for some exports could create challenges for policy-makers in the rest of the region. However, China’s rebalancing could also create opportunities. For example, there could be a rise in China’s demand for imports for domestic consumption, relative to imported inputs into processing trade. This might mean higher demand for final goods and a different mix of intermediate imports. As China moves up regional and global value chains, opportunities will potentially be available for those countries that have a conducive domestic business environment. In recent years, countries in the region (such as Vietnam) and those outside (such as Bangladesh) have enjoyed such gains via growth in their textiles, clothing and footwear export sectors due to production processes moving away from China. Countries in the region also stand to benefit from an increasingly affluent middle class in China whose appetite for travel is rapidly increasing. Cambodia, Indonesia, Thailand, and several PICs have benefited from an increase in tourism exports. However, continued investment in infrastructure, improving logistics, and making investments in protecting natural capital and building climate change resilience will be critical to ensuring that services exports continue to increase.

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Enhance social protection measures that protect the poor The intensification of risks in the global and regional economies underscores the need to continue to strengthen social assistance and insurance programs to increase resilience to systemic shocks. To increase resilience and promote great economic security, governments in the region can focus on strengthening social insurance and assistance programs. An important aim for policy is not only to promote poverty reduction but to also help protect households from falling back into poverty or experiencing significant income losses in the face of shocks. The poorest households are also those least likely to have savings or effective coping strategies (and are more likely to be engaged in informal activities), and during downturns are likely to simply reduce their consumption. Developing East Asia and Pacific stands out as the region with the lowest benefits incidence of social assistance in the poorest quintile, at less than 2 percent.12 Most countries in developing East Asia and Pacific have some type of social programs for those in the formal sector or targeted poor segments of the population. However, targeting can become more difficult as countries’ living standards rise, as the number of poor become sparse and targeting programs more accurately becomes more challenging. In addition to better targeting, focusing on widening the resource envelope to increase overall spending is critical, as it is currently low compared with most regions in the world (Mason and Shetty 2009) (Figure I.C.1). Figure I.C.1. G overnment expenditure by type of social spending Simple averages across country groups, percent of GDP 35 30 25 20 15 10 5 0 Advanced Emerging economies Europe (31) (12)

JJEducation

LAC (18)

JJHealth

MENA (6)

SSA (41)

SAR (7)

Developing Developing East Asia ASEAN (9) (8)

JJSocial protection

Sources: World Bank World Development Indicators, Atlas of Social Protection Indicators of Resilience and Equity (ASPIRE), East Asia and Pacific Social Protection database, and Pensions databases; Organisation of Economic Co-operation and Development (OECD) Social Expenditure database; Betcherman and Moroz 2018; World Bank staff calculations. Note: Shares of social spending shown are simple averages across country groups. The number of countries in each group is displayed within parentheses. “Developing East Asia” includes the following: Cambodia, China, Indonesia, Lao PDR, Malaysia, Mongolia, Myanmar, the Philippines, Thailand, and Vietnam. GDP = gross domestic product.

12 ASPIRE database.

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Part I References

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Part II. Medium-Term Development Agenda

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II.A. Piecing Together the Poverty Puzzle in Developing East Asia and Pacific1 Piecing together the poverty puzzle means widening the ways in which we define and measure poverty, acknowledging that poverty is neither one-dimensional nor solely monetary in nature. Broader measures include two higher-value poverty lines to complement the $1.90 international poverty line—$3.20 and $5.50/day, which are typical of standards among lower-middle and upper-middle income countries. In 2018, the number of poor in developing East Asia and Pacific at the $5.5 poverty line is almost 18 times more than at the $1.90 line. Poverty exists in other forms that are not monetary; thus, a multi-dimensional poverty measure (MPM) is useful to assess deprivations in multiple aspects of life. In developing East Asia and Pacific, the share of poor according to a multidimensional definition that includes consumption, education, and access to basic utilities is about 50 percent higher than monetary poverty based on the $1.9 poverty line. As highlighted in this chapter, poverty is multi-faceted. A larger suite of poverty measures broadens our view and understanding of poverty in the developing East Asia and Pacific region.

Broader measures of poverty are important As countries have grown economically, the yardstick for measuring extreme poverty based on the International Poverty Line (IPL)—$1.90/day 2011 PPP—has gradually become less relevant to the developing East Asia and Pacific region, which is today comprised exclusively of middle-income countries.2 The more prosperous countries in the region, such as China, Malaysia, Mongolia, and Thailand have international poverty rates less than 1 percent. However, many citizens in these countries would not believe that poverty does not exist. Their conception of poverty and the standards of living they aspire to are much higher than what is benchmarked by the IPL. At the same time, poverty is a complex and multifaceted problem. In addition to monetary deprivation, individuals may suffer from lack of access to basic infrastructure, education, and other critical services. In line with these ideas, the World Bank has recently introduced new poverty measurements based on the recommendations of the Commission on Global Poverty, led by the late Professor Sir A. B. Atkinson, to consider complementary indicators to the core indicator of extreme poverty (World Bank 2017).3

ÌÌHigher poverty lines for everyone Given rising incomes and wealth over the past three decades, the IPL may now be too low to define whether someone is poor in developing East Asia and Pacific. Higher international poverty lines are needed that are better suited to tracking progress and matching aspirations in more developed countries (Box II.A.1). For people living in countries with higher overall income levels, there is value in monitoring progress with higher poverty lines that reflect the increasing costs of basic needs and services in a growing world.

1 2 3

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This chapter includes excerpts from Poverty and Shared Prosperity 2018: Piecing Together the Poverty Puzzle (2018 PSPR). Prepared by the East Asia and Pacific Team for Statistical Development (EAPTSD) and the East Asia and Pacific Poverty & Equity team. By GNI per capita, countries range from the lower middle-income countries, including Lao PDR, the Solomon Islands, and Papua New Guinea, to Malaysia which is nearly high-income. Some indicators introduced in the 2018 PSPR are not discussed in this report. For a full description of all new indicators, refer to the 2018 PSPR.

PART II. MEDIUM-TERM DEVELOPMENT AGENDA

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ÌÌPoverty is multidimensional Being poor encompasses not only a shortfall in income and consumption, but also low educational achievement, poor health and nutritional outcomes, lack of access to basic services, and an unsafe living environment (Box II.A.3). If poverty is to be tackled “in all its forms everywhere” as the Sustainable Development Goals (SDGs) call for, it is important to understand and measure poverty in all its manifestations. Multidimensional poverty is relevant to all countries. Even in countries where extreme monetary deprivation is rare, there continue to be significant concern over poverty more broadly defined. To truly end poverty, progress should also be monitored in ensuring access to services that are critical for well-being. A focus on the poorest countries in the region, for example Lao PDR, Papua New Guinea, the Solomon Islands, and Timor-Leste, can also be maintained with this broader view. By using these new measures in coordination with the existing measure of extreme poverty—both in those countries with high rates of extreme poverty and those that have nearly vanquished extreme poverty—we can better monitor poverty in all countries, in multiple aspects of life, and for all individuals in every household. Such measures can also help policymakers design more relevant and better targeted policies to combat poverty in its various dimensions.

Box II.A.1. Beyond the twin goals – Higher poverty lines In 2013, the World Bank Group set two overarching goals for the world: end extreme poverty by 2030 and promote the prosperity of the bottom 40 percent of the population in each country. As recommended by the Atkinson Report (World Bank 2017), complementary indicators were introduced in recognition that poverty is a complex phenomenon, arising out of multiple causes and manifesting in a multitude of ways. These new indicators were introduced in the 2018 Poverty & Shared Prosperity Report (World Bank 2018a); two are described below. When the $1.90/day 2011 PPP International Poverty Line (IPL) was constructed based on national poverty lines for the 15 poorest countries, 60 percent of the global population was living in low-income countries. As a result, the average value of the national poverty lines in these 15 countries was meaningful for the vast majority of the poor and a large portion of the world’s population. By 2013, however, only 8 percent of the global population was living in low-income countries (Fantom and Serajuddin 2016). Consequently, in many countries, the use of average assessments of basic needs in low-income countries is gradually becoming less relevant. The lower-middle and upper-middle-income class poverty lines are defined as follows: The lower-middle-income class (LMIC) poverty line: $3.20/day 2011 PPP The upper-middle-income class (UMIC) poverty line: $5.50/day 2011 PPP

(continued)

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(Box II.A.1 continued)

These lines, which are typical of standards among lower-middle-income and upper-middle-income countries respectively, are designed to complement, not replace, the IPL. To derive these two new global poverty lines, medians of the national poverty lines of countries in lower-middle-income and upper-middleincome class countries were calculated. Therefore, $3.20/day 2011 PPP is the median of national poverty lines from LMIC countries, and the $5.5/day 2011 PPP is the median of national poverty lines from UMIC countries (Table BII.A.1.1). Table BII.A.1.1. National poverty lines, circa 2011 Economy, income classification

Median

Low-income economy Lower-middle-income economy Upper-middle-income economy High-income economy

1.90 3.20 5.50 21.70

Source: Jolliffe and Prydz 2016. Note: Values are rounded to nearest 0.10. Economies are classified on the basis of official World Bank income classifications, which rely on measures of per capita gross national income. Estimates are based on national poverty lines in 126 economies. The selected poverty line for each economy is the one that is closest in time to 2011.

Higher standards fit for a growing region ÌÌHigher international poverty lines to match higher aspirations Monitoring poverty at higher poverty lines is increasingly important as countries grow richer. A poverty line that is too low can lead to an inaccurate assessment of an individual’s ability to function in society in a socially acceptable manner. Participation in society with dignity may require more goods in a richer country than in a poorer country. Social participation might thus be more closely related to the concept of meeting basic needs in the poorest of countries, but in richer countries, the ability to participate in society might be costlier. Figure II.A.1. D istribution of the population in developing East Asia and Pacific by consumption per capita, 2018

Figure II.A.2. Number of poor by poverty line – selected countries

Population, millions

Population, millions

1,200

400 350

1,000 300 800 250 200

600

150 400 100 200

50 0

0 $0–$1.9

$1.9–$3.2

$3.2–$5.5

$5.5–$15

$15<

China 2015

JJIPL ($1.9) Source: World Bank, East Asia and Pacific Team for Statistical Development. Note: The bars show the population in developing East Asia and Pacific living at different levels of household consumption. The extreme poor, living on less than the international poverty line ($1.90/day, 2011 PPP); The moderate poor, living on $1.90 to $3.20 / day (2011 PPP); the economically vulnerable, living on $3.20 to $5.50 a day (2011 PPP); the economically secure, living on $5.50 to $15 a day (2011 PPP); and the middle class, living on more than $15 a day (2011 PPP). For full definitions of economic classes, see Riding the Wave (World Bank 2018b).

62

Indonesia 2017

JJLMIC ($3.2)

Myanmar 2015

Vietnam 2016

JJUMIC ($5.5)

Source: World Bank, East Asia and Pacific Team for Statistical Development. Note: IPL: International poverty line ($1.9). LMIC: lower-middle-income class poverty line (LMIC) ($3.2). UMIC: upper-middle-income class poverty line ($5.5).

PART II. MEDIUM-TERM DEVELOPMENT AGENDA

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Where the poverty threshold is set makes a tremendous difference to who and how many people are considered poor. The estimated number of poor in developing East Asia and Pacific in 2018 at the international (IPL, $1.9), lower-middle-income class (LMIC, $3.2), and upper-middle-income class (UMIC, $5.5) poverty lines are 30, 168, and 538 million, respectively (Figure I.A.25 in Part I). Even though the UMIC poverty line is less than three times higher than the IPL, the number of UMIC poor is almost 18 times more than the number of extreme poor, because a much larger proportion of the population lives between $1.9/day and $5.5/day (Figure II.A.1). The largest differences in the number of poor by these classifications are in the region’s most populous countries. For example, 9.9 million Chinese were poor as measured by the IPL in 2015, compared with 373.1 million using the UMIC poverty line (Figure II.A.2). While developing East Asia and Pacific has been extremely successful at reducing poverty measured by the International, LMIC, and UMIC poverty lines, building middle-class societies may be more challenging for the region. The middle-class threshold, set at $15/day in the World Bank’s regional study “Riding the Wave” (World Bank 2018b), is much higher than the UMIC poverty line ($5.5/day). The majority of developing East Asia and Pacific, over one billion people, lives on between $5.5 and $15/day (Figure II.A.1). In 2018, 75.4 percent of developing East Asia and Pacific still live on less than $15/day (Figure II.A.3). When excluding China, about 83 percent live on less than $15/day. Outside of developing East Asia and Pacific’s wealthiest countries, the middle class is small in size or growing slowly. In the Philippines, the size of the middle class has hardly changed over the past decade (World Bank 2018c).

Figure II.A.3. Developing East Asia and Pacific poverty rates, by poverty line, 2002 and 2018 Poverty rate, percent 100 90 80 70 60 50 40 30 20 10 0 IPL ($1.9)

JJ2002

LMIC poverty line ($3.2) JJ2018

UMIC poverty line ($5.5)

Middle class poverty line ($15)

Source: World Bank, East Asia and Pacific Team for Statistical Development. Notes: The IPL is the World Bank’s first twin goal. The LMIC and UMIC poverty lines are described in Box 1 and in World Bank (2018a). The middle-class poverty line was derived for the East Asia and Pacific region and is described in World Bank (2018b). Other regions may have different choices of middle-class poverty lines.

Growth strategies that helped to eradicate extreme poverty in most of developing East Asia and Pacific will likely not be sufficient to also lift households into the middle class. Outward-oriented growth, basic human capital development, and sound economic governance have helped lift a billion people in East Asia and Pacific out of extreme poverty. However, these foundational policies will not guarantee that one billion people will also be lifted into the middle class. The East Asia and Pacific regional middle-class poverty line is almost eight times higher than the international poverty line. Countries and challenges are also evolving. Even as the size of the middle class is increasing, middle-class households can still be exposed to risks and fall back into poverty. This is a relevant concern as parts of the region experience uncertainties from trade tensions and slowing growth.

ÌÌNational poverty lines in East Asia and Pacific While the global poverty lines are useful for global monitoring and benchmarking, national poverty lines are still the most relevant for government policymaking. These lines are constructed based on the consumption patterns, prices, and circumstances of a particular country, which most accurately reflect the costs of basic needs and services.4 4

Most countries use one national poverty line, though others have poverty lines that vary by subnational region or household characteristics. Many Pacific Island countries have poverty lines that vary by region. Poverty lines in Thailand and Malaysia are the most disaggregated, varying by household composition and geography. Poverty lines are not the only tool used to measure well-being, with some countries adopting multiple dimensional poverty measures. In Tonga, relative deprivation is also measured via the consensual method (Gordon et al. 2018). The consensual deprivation approach is a measure of multidimensional poverty that takes into account what the general public constitutes as acceptable living standards (Mack 1985).

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National poverty lines tend to increase as countries grow wealthier, which is consistent with the notion that participation in society with dignity may require higher levels of consumption and income in a richer country than in a poorer country. Figure II.A.4 illustrates the national poverty lines in most of developing East Asia and Pacific countries, converted to 2011 PPP units so they are comparable to global poverty lines.5 Countries with similar GNI per capita may have different national poverty lines. Mongolia (2016) and Indonesia (2017) have similar GNI per capita, but Mongolia’s national poverty line is about double the value of Indonesia’s in 2011 PPP terms. The national poverty rate of Mongolia is 29.6 percent in 2016 compared with 10.6 in Indonesia in 2017.

Figure II.A.4. Countries with similar levels of GNI per capita can have very different poverty lines National poverty line (per person per day, 2011PPP) 7

THA 2013

6 5

MNG 2016 TON 2009

4

FSM 2013

FJI 2013 TUV 2010 WSM 2013

MYS 2012

VNM 2016

KIR 2006 VUT 2010

3

2 LAO 2012 PNG 1996

PHL 2015

IDN 2017 SLB 2013 TLS 2014

CHN 2017

1 0

Low income countries

Lower-middle income countries

0

2,000

Upper-middle income countries

4,000

6,000

8,000

10,000

12,000

GNI per day Source: World Bank, East Asia and Pacific Team for Statistical Development. Note: Income group thresholds in the figure are from classifications in 2019 based on GNI per capita. A country’s current income group may differ from what is displayed based on the year of the most recently available national poverty line statistic. For countries with multiple national poverty lines, a populationweighted average is taken. National poverty lines are converted to 2011 PPP per capita per day for comparability with international poverty lines. Horizontal lines in the figure refer to the International ($1.9), LMIC ($3.2), and UMIC ($5.5) poverty lines.

There are some cases, however, where national poverty lines appear much lower than expected based on GNI per capita. For instance, the two richest countries in developing East Asia and Pacific do not have the highest national poverty lines. Among developing East Asia and Pacific countries,  Malaysia is closest to transitioning to high-income status. Yet, Malaysia’s average national poverty line was $4.24/day 2011 PPP in 2012, similar in value to Samoa’s line in 2013. In comparison, the median value of national poverty lines among high-income countries around 2011 was $21.7/day 2011 PPP. The national poverty line in Lao PDR in 2012 was even slightly higher than China’s national poverty line in 2011 PPP terms, although its GNI per capita was about one-sixth China’s in 2017. China’s concept of basic needs has been referred to as the “two no-worries and three guarantees”. The three guarantees refer to non-monetary aspects that should be guaranteed by the state related to health, housing, and education. Thus, the national poverty line6 is viewed as the amount necessary to only cover the basic material costs of food and clothing or the “two no-worries”, while in other countries the poverty line is calculated based on minimum necessary expenditures on a broader definition of goods and services. This partly explains the lower value of China’s national poverty line relative to other countries in the region.

Non-monetary measures are important to tackle poverty in all its forms Monetary-based measures do not encompass all aspects of human well-being. One reason for this is that not all goods and services that matter to people are obtained exclusively through markets (Box II.A.2). Consequently, the prices necessary to cost these goods and services either do not exist (e.g., a clean environment or secure community) or do not accurately reflect their true consumption value (e.g., because they require large public investments to make them available, such as power) (World Bank 2017). Other core services at least partially provided through systems supported by direct government spending include health care and education. General government health expenditure accounts for more than half of total global health expenditure. Likewise, governments on average spend the equivalent of nearly

5 6

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The global poverty lines are the IPL ($1.9), LMIC ($3.2), and UMIC ($5.5). The IPL was originally derived based on the national poverty lines of the world’s poorest countries. The LMIC and UMIC are median values of national poverty lines in LMIC and UMIC countries in about 2011 (Jolliffe and Prydz 2016). China’s national poverty line of 2300 yuan per person per month was introduced in 2010 and since updated annually.

PART II. MEDIUM-TERM DEVELOPMENT AGENDA

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5 percent of the gross domestic product (GDP) of their economies on education. The presence of such goods renders the traditional monetary welfare measure incomplete with respect to a variety of core aspects of well-being.

Box II.A.2. Why look beyond monetary poverty? Consider the following hypothetical example: two families have the same income, say, $3.00 per person per day. However, only one family has access to adequate water, sanitation, and electricity, whereas the other lives in an area lacking the necessary infrastructure for basic services, such as a power grid or water mains. Members of this second family will still consume water and use energy for lighting and cooking, but they may have to spend hours per week fetching water from a well, or pay higher prices to obtain lower-quality water from a truck. For sanitation, they may use a private or communal latrine, without the convenience or hygiene benefits of a sewerage connection. And with no access to an electricity grid, the second family’s choice set for lighting and power options is severely reduced. Both households will spend some of their $3.00 per person per day to meet their energy and water needs. Because their choice sets (including the prices they face) are so different, the differences in their living standards arising from the access that the first family enjoys are not captured by a monetary measure of poverty alone. The first family clearly enjoys a higher standard of living than the second, but a welfare judgment that considers only their incomes will pronounce them equally well-off. This is an example of when public action—or lack thereof—can directly affect the well-being of households by expanding—or not—their choice sets in ways that incomes and prices fail to fully internalize. It is possible that, under a broader assessment of poverty, the second family might be considered poor or deprived, even though its daily income is above the international poverty line of $1.90 per day.

ÌÌMultidimensional poverty in East Asia and Pacific is 50 percent higher than monetary poverty Multidimensional poverty is higher than monetary poverty. This regularity arises from the construction of the Multidimensional Poverty Measure (MPM). The World Bank’s MPM includes the international poverty rate (the monetary dimension), and non-monetary dimensions in education and access to infrastructure (Box II.A.3). If a household is deprived in at least one dimension, then the members are considered multidimensionally poor. Anyone who is income poor is automatically also poor under the broader poverty concept. The difference between the different headcounts, therefore, hinges on those individuals among whom the deprivation is a result of a shortfall in the non-monetary dimensions of life despite their ability to command sufficient financial resources to cross the monetary poverty threshold. These households would be deemed non-poor under the narrower poverty concept on the basis of insufficiency in monetary resources, leaving policymakers with an unduly optimistic assessment of poverty from a multidimensional perspective.

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Box II.A.3. Beyond the twin goals - Multidimensional poverty measure Information on income or consumption is the traditional basis for the World Bank’s poverty estimates. However, in many settings, important aspects of well-being, such as access to quality health care or the ability to live in a secure community, are not captured by standard monetary measures. To address this concern, an established tradition of multidimensional poverty measurement measures and aggregates non-monetary dimensions of wellbeing into an index. The United Nations Development Programme’s Multidimensional Poverty Index (Global MPI), produced in conjunction with the Oxford Human Development Initiative, is a foremost example of such a multidimensional poverty measure (UNDP 2010). The World Bank’s Multidimensional Poverty Measure (MPM) complements the Global MPI by placing a monetary measure of well-being alongside non-monetary dimensions. By doing so, the MPM explores the share of the deprived population that is missed by a sole reliance on monetary poverty, as well as the extent to which monetary and non-monetary deprivations are jointly presented across different contexts. Table BII.A.3.1. Dimensions of well-being and indicators of deprivation Dimensions

Three dimensions (13 East Asia and Pacific countries)

Five dimensions (Indonesia only)

consumption or income less than $1.90 Monetary well-being Daily per person At least one school-aged child up to the age of grade 8 is not enrolled in school Education No adult in the household (ages of grade 9 or above) has completed primary education

Access to services

Health

Nutrition

Security

Daily consumption or income less than $1.90 per person At least one school-aged child up to the age of grade 8 is not enrolled in school No adult in the household (ages of grade 9 or above) has completed primary education The household lacks access to a basic-standard The household lacks access to limited-standard drinking water source (“at least limited” with an drinking water added criterion of being within a roundtrip time of 30 minutes) The household lacks access to basic-standard The household lacks access to limited-standard sanitation (“at least limited” with an added sanitation facilities criterion of being for the exclusive use of the household) The household has no access to electricity The household has no access to electricity Any woman aged 15–49 with a live birth in the last 36 months did not deliver at a facilitya Any child aged 12–59 months did not receive DPT3 vaccinationa Any child ages 0–59 months is stunted (HAZ < −2) Any woman ages 15–49 is undernourished (BMI < 18.5) The household has been subject to crime in the previous 12 months or lives in a community in which crime is prevalent The household has been affected by a natural disaster (including flooding, drought, earthquake) in the previous 12 months

Source: World Bank 2018a. Note: BMI < 18.5 = body mass index below 18.5 (underweight); DPT3 = diphtheria-pertussis-tetanus vaccine; HAZ < −2 = the height-for-age Z-score is below −2, that is, more than two standard deviations below the reference population mean. a) If the indicator is not applicable, for example, if the household includes no women who gave birth in the previous 36 months, the household is classified as deprived if the relevant deprivation rates in the subregion of residence are sufficiently high. Specifically, the deprivation threshold is set such that the share of individuals in non-applicable households that are classified as deprived equals the national share of deprived individuals in applicable households who actually experienced a recent birth or have a child under the age of six.

(continued)

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(Box II.A.3 continued)

Table BII.A.3.1 illustrates the individual dimensions considered in the World Bankâ&#x20AC;&#x2122;s MPM. (Readers are directed to read Chapter 4 of the 2018 PSPR for a technical discussion on the construction of the World Bankâ&#x20AC;&#x2122;s MPM.) This index includes monetary well-being, education, and access to basic services, including water and sanitation. An expanded MPM using five dimensions was constructed for Indonesia to illustrate the impact of including additional well-being indicators on poverty.

Average multidimensional poverty among a subset of 13 East Asia and Pacific countries is 7.5 percent, compared with a monetary poverty rate of 5.3 percent using the international poverty line (Figure II.A.5).7 High deprivation rates in education or access to infrastructure can exist in countries with low levels of monetary poverty. Monetary and non-monetary poverty are correlated, but not perfectly. Even in countries where the level of extreme poverty is below 1 percent, deprivations in nonmonetary aspects of life are still present, reflecting the multifaceted nature of poverty. For example, in Mongolia, the international poverty rate is virtually zero, but 9.6 and 12.8 percent of the population do not have access to limited-standard sanitation or drinking water, respectively (Figure II.A.6, see Box II.A.3 for definitions).

Figure II.A.5. Multi-dimensional poverty in 13 East Asia and Pacific countries vs 119 economies worldwide Percent 20 18 16 14 12 10 8 6 4 2 0 EAP

JJMonetary poverty

World

JJMultidimensional poverty

Source: World Bank, 2018a. Note: The East Asia and Pacific regional and world monetary poverty rates in the MPM calculations do not match previously discussed poverty rates because: (i) China lacks microeconomic data and is not included in the regional MPM average; (ii) surveys used for MPM and global poverty may differ; and (iii) MPM can be calculated for fewer countries than monetary poverty alone. MPM calculations are based on 13 East Asia and Pacific countries, while East Asia and the Pacific regional monetary poverty rates are based on 19. Globally, MPM is based on 119 countries, while monetary poverty rates are based on 164.

The improving state of education in East Asia and Pacific means that deprivations in education enrolment are typically lower than deprivations in education attainment ( Figure II.A.6). Education enrolment is measured as enrollment of school-aged children, while education attainment measures completed education of adults in the household. In the region, monetary poverty is less correlated with education deprivations than with access to infrastructure deprivations, partly because compulsory education is becoming the norm. Most children are obtaining education levels higher than their parents, which is measured by absolute education mobility. In developing East Asia and Pacific, absolute education mobility among the latest generation of adults (those born in the 1980s) is on par with the average for high-income economies and is significantly higher than the average for developing economies (Narayan and Yang 2018). However, other issues related to quality and equal access to a quality education are still concerns in some countries (Crawford et al. 2018). Deprivations in access to limited-standard sanitation and water are high in many countries. Populations in regions with low monetary poverty, such as East Asia and Pacific, Latin America and the Caribbean, and Middle East and North Africa, suffer a sanitation deprivation rate several times as high as that in the monetary dimension (World Bank 2018a). In developing East Asia and Pacific, the difference in monetary and non-monetary poverty can be related to cheap products and poor infrastructure. Low international monetary poverty in some developing East Asia and Pacific

7

The World Bankâ&#x20AC;&#x2122;s MPM was computed for 13 East Asia and Pacific countries, but monetary poverty alone can be calculated for 19. The MPM is calculated for fewer countries due to higher data requirements. In addition, surveys used to calculate the MPM are not necessarily the same as ones used to calculate monetary poverty. Notably, an MPM for China could not be calculated, which is why the East Asia and Pacific monetary poverty rate appears significantly different than mentioned in Part I and previous sections in Part II.A.

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countries is related to goods typically being cheaper than critical services, though at the same time infrastructure can be poor, resulting in deprivations in access to limited-standard sanitation and drinking water. Figure II.A.6. Deprivations in non-monetary dimensions – selected East Asia and Pacific countries Poverty or deprivation rate, percent 60

50

40

30

20

10

0 Indonesia 2016

JJEducation attainment

Lao PDR 2012

Myanmar 2015

JJEducation enrolment

Philippines 2015

Thailand 2013

JJElectricity

Vietnam 2014

JJSanitation

Mongolia 2016

Solomon Islands 2013

Timor-Leste 2014

JJWater

Source: World Bank, 2018a. Notes: See Box II.A.3 for definitions of deprivations.

ÌÌSubnational variation in non-monetary poverty is also pronounced In developing East Asia and Pacific, the difference in non-monetary poverty between urban and rural areas is higher than the difference in monetary poverty. The multi-dimensional poverty rate in rural areas is much higher than the monetary poverty rate, while in urban areas the monetary and multidimensional poverty rates are similar (Figure II.A.7). Deprivation rates in education and access to services are higher in rural areas; households that are not monetarily poor may lack adequate schooling or access to basic infrastructure services. Meanwhile, in urban areas of developing East Asia and Pacific, there exists better availability and access to public services. While not measured by the indicators of non-monetary poverty presented here, there also are important differences in the quality of public services between rural and urban areas. For example, it is well documented that education quality is still a problem, and in some countries rural areas have lower quality education (Crawford et al. 2018).

68

Figure II.A.7. Deprivations in non-monetary dimensions are higher in rural areas Percent 12

10

8

6

4

2

0 Rural

JJMonetary

Urban

JJMultidimensional

Source: World Bank 2018a. Note: Based on a set of 13 East Asia and Pacific countries. Monetary poverty is the international poverty rate based on the $1.9/day 2011 PPP poverty line. The multidimensional poverty measure is based on three dimensions.

PART II. MEDIUM-TERM DEVELOPMENT AGENDA

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Figure II.A.8. Non-monetary deprivations vary within countries Mongolia

Percent deprived in education attainment: No adult in the household (ages of grade 9 or above) has completed primary education

Vanuatu, Fiji, Tonga

Mongolia

Percent deprived in education enrolment: At least one school-aged child up to the age of grade 8 is not enrolled in school

Vanuatu, Fiji, Tonga

Mongolia

Vanuatu, Fiji, Tonga

Percent deprived in limited-standard drinking water.

Mongolia

Vanuatu, Fiji, Tonga

Percent deprived in limited-standard sanitation.

0–1.5 1.5–3.5 3.5–4 4–5.5 5.5–7 7–9 9–12 12–18 18–24 >24

0–0.5 0.5–1.5 1.5–2 2–3.5 3.5–4.5 4.5–5.5 5.5–8.5 8.5–12 12–16.5 >16.5

0–0.5 0.5–3.5 3.5–8 8–11.5 11.5–14 14–16.5 16.5–23 23–31 31–43 >43

0–0.5 0.5–2.5 2.5–5.5 5.5–10 10–12.5 12.5–17 17–24.5 24.5–36 36–61 >61

Source: World Bank, East Asia and Pacific Team for Statistical Development. Note: MPMs were not computed for some countries, including Cambodia, China, Kiribati, Samoa, and Tuvalu. Malaysia’s education enrolment data are not available.

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There is large variation in material deprivations across subnational regions. This is related to the previous observation that rural areas are more deprived of material aspects of well-being than urban areas. Deprivations in infrastructure can be associated with remoteness and geography. For example, deprivations are higher in the highlands of Vietnam, or smaller islands in the Philippines or Indonesia (Figure II.A.8). For targeted policymaking, measuring deprivations at even more disaggregated levels is useful. The government of Myanmar developed a Multidimensional Disadvantage Index (MDI) using census data at the township level (Box II.A.4). The MDI is a fundamental tool for the government of Myanmar to identify geographic areas most in need, and contributes to targeting public resources and aid flows toward those who need it the most and with interventions that matter the most.

ÌÌRecognizing more dimensions of poverty facilitates targeted policymaking Extending the definition of poverty can further deepen our understanding of it. The World Bank’s MPM is based on three dimensions (monetary, education, and access to infrastructure). As an exercise, a five-dimension MPM was computed for Indonesia that included elements of health care, nutrition, and security (see Box II.A.3 for definitions of the dimensions).8 In the case of Indonesia, including health and security in the MPM can shift the understanding of who is poor and where they are located. Accounting for the two extra dimensions of well-being reveal more potential poor. The proportion of people identified as poor under the expanded definition is higher than with the three-dimensional measure, suggesting that the share of individuals who are unnoticed by monetary poverty measures could be even higher. Specifically, acknowledging deprivations along these two dimensions reveals that a larger share of the poor lives in female-led households and shifts poverty back toward urban areas (Figure II.A.9). Unfortunately, the MPM in five dimensions requires data that are often not available in traditional household surveys. Measures developed by countries themselves are the most relevant for national policymaking and are able to take into account the most important challenges to daily life. Just as national poverty lines are more relevant than international poverty lines for national policymaking and planning, a country may also have different priorities for non-monetary aspects of life. Depending on the country, crime and security, access to high-speed internet, or clean water may have different relevance and importance. For example, the World Bank’s MPM was based on three dimensions (monetary, education, and access to infrastructure). Myanmar’s MDI is based on six dimensions: education, employment, health, water and sanitation, housing, and assets (Box II.A.4).

8

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Figure II.A.9. The headcount rate, by alternative poverty measures, Indonesia Share of population 70 60 50 40 30 20 10 0 Entire population

JJMonetary headcount

One adult female households

Urban households

JJMPM 3-dimensional headcount JJMPM-5 headcount

Source: World Bank 2018a; Indonesian Family Life Survey, 2014. Note: The figure shows the share of the population that is considered poor under three different definitions of poverty. Monetary poverty = individuals living on less than $1.90/day. Multidimensional poverty (three dimensions) = individuals deprived in at least 33 percent of the (weighted) indicators according to the multidimensional headcount measure; the dimensions considered are monetary poverty, educational attainment, and access to services. Multidimensional poverty (five dimensions) = individuals deprived in at least 20 percent of the (weighted) indicators according to the multidimensional headcount measure and considering all five dimensions. Each dimension in the three-dimension measure is weighted 0.33. Each dimension in the five-dimension measure is weighted 0.20. In the multidimensional measures, each indicator is weighted equally within dimensions.

Analysis presented for Indonesia on the five-dimension MPM utilizes different data than for calculation of monetary poverty and the three-dimension MPM. Some results will differ from analysis shown in previous sections.

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Box II.A.4. Multidimensional welfare in Myanmar Myanmar has recently developed its first multidimensional measure of welfare, unleashing new opportunities for evidence-based policymaking, especially at the subnational level. The recent report Multidimensional Welfare Analysis in Myanmar (World Bank and Ministry of Labour, Immigration and Population, Myanmar 2018), jointly produced by the Department of Population within the Ministry of Labour, Immigration and Population, and the World Bank in December 2018, introduced the “Multidimensional Disadvantage Index” (MDI). The MDI brings 14 non-monetary indicators from six domains (education, employment, health, water and sanitation, housing, and durable assets), selected from the 2014 Myanmar Population and Housing Census, into a single indicator of welfare. Using data from the census enabled development of a view of non-monetary welfare at the lowest administrative level—the township. The study considers a household to have a “disadvantage” if its members are unable to meet their basic minimum needs in a specific indicator. The MDI measures overlap in disadvantages across indicators. The higher the MDI value is, the greater the extent of multiple disadvantage among households living there.

Key findings Eighty-four percent of the population in Myanmar is disadvantaged in at least one indicator; multiple disadvantages affect many individuals. Only 16 percent of the population has no disadvantage, and 20 percent is disadvantaged on a single indicator. Worryingly, nearly half (47 percent) of the population is disadvantaged in at least three indicators and more than one-fifth (22 percent) in five or more indicators. The difference in the level and intensity of disadvantage is substantial across urban and rural areas, and across states and regions within Myanmar. The rural population is distinctly more likely to be severely disadvantaged relative to the urban population. The likelihood of disadvantage in five or more indicators (out of 14) for the rural population is five times higher than for the urban population (Figure BII.A.4.1). Multiple disadvantage is more pronounced in Rakhine State, where 60 percent of the population experience a disadvantage in five or more indicators, while in Yangon only 10 percent of individuals fall into this category. Figure BII.A.4.1. Percentage of individuals experiencing multiple disadvantages (number of indicators) Rural

Urban

Union

0

JJ0

10

JJ1

20

JJ2

30

JJ3

40

JJ4

JJ5

50

JJ6

60

JJ7

70

JJ8

80

JJ9

90

JJ10+

100

5+

(continued)

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(Box II.A.4 continued)

Myanmar’s Multidimensional Disadvantage Index (MDI-1) is estimated at 20.7. This can be interpreted as the average person in Myanmar being disadvantaged in 20.7 percent of weighted indicators.9 The rural MDI-1 (at 24.6) is more than twice as high as the urban MDI-1 (at 11.2). MDI-1 is the highest in Rakhine (39.2) and the lowest in Yangon (14). Among the most disadvantaged states and regions according to the measure are also Ayeyawady, Kayin, Tanintharyi, Chin and Shan. Mandalay, Kachin, and Nay Pyi Taw, instead, present a lower level of non-monetary disadvantage. There is no pattern across states and regions in term of which domain or indicator contributes most to the total MDI. Housing, and water and sanitation are the biggest domain contributors in Rakhine, but this is not the case in Chin, where asset ownership plays the biggest role in explaining the total MDI. In Shan, on the other hand, education and water and sanitation domains accounted for a half of the total MDI. Large disparities in welfare are also visible within states and regions, across townships (Figure BII.A.4.2). For instance, Kachin and Sagaing are relatively better-off states, but northern townships in both states have some of the most disadvantaged populations in the country. In contrast, Yangon has the lowest MDI in Myanmar, but rural townships at the outskirts of the urban center are as disadvantaged as some townships located in much more deprived Chin and Kachin States.

Policy implications The granular view of non-monetary welfare in Myanmar presented in this study has important implications for policy-making. First, by revealing the contribution of different domains or indicators to overall disadvantage, the study highlights the type of focus areas and interventions that need the most attention in each geographic location. Second, the MDI provides a picture of welfare at a highly disaggregated level—all the way down to the township. The MDI could thus become a fundamental tool to identify geographic areas most in need, and then contribute to targeting public resources and aid flows toward those who need it the most, with interventions that matter the most.

(continued) 9

72

The MDI-1 takes an average of the weighted sum of all indicators using the equal weights over domains and indicators (nested uniform weights). For further details about selected indicators, weighting and aggregation of the MDI, see “Multidimensional Welfare in Myanmar” (2018).

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(Box II.A.4 continued)

Figure BII.A.4.2. Multidimensial Index at state/region and township level a. State/Region level

b. Township level

< 10.0

5.6 - 10.0

10.1 - 14.4

10.1 - 14.4

14.5 - 17.0

14.5 - 17.0

17.1 - 18.5

17.1 - 18.5

18.6 - 20.5

18.6 - 20.5

20.6 - 22.6

20.6 - 22.6

22.7 - 24.6

22.7 - 24.6

Kachin 15.4

24.7 - 29.3

24.7 - 29.3

29.4 - 35.0

29.4 - 35.0

35.1 - 50.6

35.1 - 50.6

Sagaing 17.9

Chin 24.7 Mandalay 14.5

Rakhine 39.2

Shan 24

Magway 19.1 Nay Pyi Taw 15.9 Kayah 17.5 Bago 21.1

Ayeyawady Yangon 14 27.4

Kayin 27.3 Mon 20.7

Tanintharyi 26.7

Union: 20.7 Urban: 11.2 Rural: 24.6 Yangon

Note: Mapping colors are based on township-level MDI decile thresholds. Due to the limited number of enumerated population, three townships in Northern Rakhine (Maungtaw, Buthidaung, Yethedaung) are highlighted in gray.

Prepared by Ikuko Uochi and Giorgia Demarchi.

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Conclusion Our conceptualization of what poverty is in developing East Asia and Pacific should adapt as incomes and aspirations rise, and countries work on expanding their middle-class societies and transitioning to high-income status. A broader view of poverty, including higher poverty lines and multidimensional poverty measures, reveals there is still much work to be done in middle-income countries, even though extreme poverty is now less prevalent. This view helps to enhance policy dialogue and craft policies that are more relevant and targeted. In developing East Asia and Pacific, higher standards should be used to reflect increasing aspirations and costs of living, non-monetary poverty exists even where monetary poverty does not, and urban-rural poverty gaps are higher when also taking into account nonmonetary measures. To better inform policies, we must invest in data and encourage open data.

ÌÌBroader measures can enhance policy dialogue and recommend better-targeted policy A larger suite of global measures, grounded in tools that countries already use to monitor progress, can facilitate enhanced dialogue by offering a rich set of comparable instruments for countries to assess their performance. To facilitate relevant and targeted policies, new and existing indicators should be monitored in a more disaggregated manner, both geographically and at the individual level. When this is done, pockets of poor become noticed, even in relatively well-off countries. People in rural areas are more likely to be deprived in both infrastructure and education than those in urban areas. Developing East Asia and Pacific’s many mountainous regions and remote islands may exacerbate unequal access to services. A more granular view of non-monetary poverty has implications for policy by revealing the types of deprivations of overall disadvantage. Indicators of multidimensional poverty can also provide a disaggregated picture of welfare and help policymakers target public resources and interventions to where they are most needed.

ÌÌThe region requires higher standards to match higher aspirations East Asia and Pacific societies have not stopped focusing on poverty even if it has become much less apparent in its extreme forms. Most of the population of developing East Asia and Pacific now live in middle-income countries. Their conceptions of poverty and the standards of living they aspire to are much higher than what is benchmarked by the international poverty line. While eliminating remaining pockets of poverty must remain a priority, monitoring poverty at higher poverty lines is also becoming increasingly important to ensure appropriate policy focus on those living in countries with higher costs of living, and also rising aspirations. Higher standards refer not only to higher poverty lines to account for higher costs of living in wealthier societies but also to higher quality and more sophisticated public services. Aspirations are also multidimensional. As societies grow richer, populations will begin to expect, for example, high-quality education systems where children can learn skills to become competitive in a technology-driven economy. As compulsory education has become the norm, deprivations in education enrolment of children are low throughout the region. Nonetheless, 60 percent of students in developing East Asia and Pacific are in poorly performing school systems (Crawford et al. 2018).

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Material aspects that some would consider daily necessities may not be included in the World Bank’s MPM but are of interest to an aspiring middle class. For example, access to infrastructure as measured in the MPM does not take into account connectivity in terms of either high-speed roads or digital connections, which are important for economic development. To meet the demands for more sophisticated public services, governments will have to increase the tax base and limit tax competition.

ÌÌNon-monetary poverty exists even where monetary poverty is low The World Bank’s MPM shows that high levels of deprivations in non-monetary aspects of life co-exist with low levels of extreme poverty measured by the international poverty line, resulting in multidimensional poverty rates in developing East Asia and Pacific that are about 50 percent higher than monetary poverty rates. Deprivations in access to infrastructure and education exist even in countries where monetary poverty is much less apparent. Thus, low indicators of monetary poverty may leave policymakers with an unduly optimistic assessment of poverty from a multidimensional perspective. Large variation exists within countries. In particular, material deprivations are much higher in rural areas. While many countries in developing East Asia and Pacific have made good progress in tackling poverty, many sub-regions are still facing daunting poverty reduction challenges.

ÌÌData investments are critical Investments in data have helped provide a more comprehensive picture of poverty, but there is a need for continued and deeper investment in data. More and better welfare data are needed to compare poverty across time, for multiple dimensions, for all individuals, and particularly in low-income and conflict-affected areas. Ensuring that policies are relevant requires that investments are expanded in country systems and have capacity to measure and monitor welfare in a timely manner. More timely data are needed to understand the implications of recent events. Looming trade wars could have negative implications for household welfare. However, only a handful of countries have completed household surveys after 2017, and microdata are usually shared with a lag of at least one year. Some developing East Asia and Pacific countries are still data deprived; for example, the last household survey in Kiribati was conducted in 2006. Moreover, data collected by governments using public funds should be owned by the people. These data must also be open and accessible for all to analyze.

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II.B. Tackling the Food Safety Challenges of Middle-Income East Asia and Pacific10 For developing East Asia and Pacific countries, rapid demographic and dietary changes, among others, are contributing to wider exposure of populations to foodborne hazards, stretching if not overwhelming prevailing capacity to manage food safety risks. This has severe consequences, in terms of public health costs, productivity losses, and foregone commerce. For many countries in the region, these costs will likely rise without significant changes in policy and institutions. As the region continues to make progress in addressing traditional food security concerns, unsafe food and a lack of consumer trust in how food safety is managed may take on greater prominence as the region’s ‘new’ food security challenge. This chapter summarizes available estimates of the public health burden and economic costs of unsafe food in developing East Asia and Pacific, draws attention to the strengths and shortcomings of food safety capacity and incentives in the region, and outlines an agenda of smarter investment and regulatory oversight to enable developing East Asia and Pacific countries to anticipate emerging food safety challenges, better manage food safety risks and, in so doing, avoid potentially very large economic costs in the future. While most stakeholders recognize the need to strengthen food safety regulatory enforcement capacities in East Asia and Pacific, of equal importance are the facilitative and educational roles of government that induce investments and behavior changes by actors who share with government the goal and responsibility of safer food.

The region is devoting increased attention and resources to improving food safety ÌÌFood safety and food security The countries of East Asia and Pacific have made enormous strides in reducing hunger over the past quarter century, and measures are in place to address remaining gaps. Between 1990–92 and 2012–14, the share of the population of East Asia and Pacific consuming an inadequate level of calories fell from 23 to 11 percent, while for Southeast Asia the reduction was from 31 to 10 percent. While there remain sizeable pockets of undernutrition—both in lagging regions, as well as urban, centers—governments are deploying a wide range of policy instruments to improve staple food accessibility and affordability. With these gains in basic food availability and affordability, food policy in the region is now devoting increased attention and resources to improving dietary quality and nutritional outcomes. Throughout the region, poor or imbalanced diets contribute to persistently high rates of child stunting, widespread micro-nutrient deficiencies in both adult and child populations, and the rising incidence of overweight and obesity—and closely associated noncommunicable diseases. The region’s success in addressing this ‘triple burden of malnutrition’ will strongly impact its progress on human development and its future public health costs (FAO 2018). However, the East Asia and Pacific region can only fully realize its aspirations for food and nutritional security when the essential elements of a healthy diet are safe to eat. The available evidence, both anecdotal and scientific, points to a rising exposure of East Asia and Pacific populations to food safety hazards, a significant (and perhaps 10 This chapter was prepared by Steven Jaffee (World Bank) with inputs from Mateo Ambrosio and Spencer Henson. The overall approach and findings are based heavily on the World Bank 2019 publication The Safe Food Imperative: Accelerating Progress in Low- and Middle-Income Countries, by S. Jaffee, S. Henson, L. Unnevehr, D. Grace, and E. Cassou. More specific analysis was done of the indicators related to emerging Asia.

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rising) incidence of foodborne illness, and deepening consumer concerns about the contamination of local foods and the adequacy of prevailing governance structures, both public and private, to manage emerging risks. This issue will become more significant going forward as a dominant share of consumers become fully reliant on purchased foods and ingredients, and as East Asia and Pacific diets continue to evolve beyond rice and other staple grains. We can expect food safety to become a central dimension of national food security concern and strategy in much of East Asia and Pacific over the coming decade. Emerging food safety problems reflect growing strains on East Asia and Pacific food systems stemming from processes of urbanization and other demographic changes, dietary preference shifts (toward animal products, processed foods, and out-of-home eating), the intensification of agricultural production, and longer supply chains. These megatrends interact with intense competitive pressures, supplier and consumer knowledge gaps, and inadequate regulatory enforcement capacities. While the media tends to focus on cases of criminal behavior (i.e., food and feed adulteration), the region’s food safety problems are diverse, stemming from environmental hazards (i.e., contaminated soil and water), poor hygienic conditions and practices in farms, markets, and food facilities, the improper use of fertilizers, pesticides and antibiotics, and unsafe food-handling and preparation practices by vendors and consumers.

ÌÌFood safety and broader economic development In East Asia and Pacific, food safety is more than a public health issue; it is also a competitiveness issue. Several East Asia and Pacific countries have been expanding their exports of higher value foods, yet overseas regulators, importers, and consumers are concerned, among other things, with biological and chemical contamination of fish, pesticide residues in fruits and vegetables, and unlawful additives found in the processed foods exported from East Asia and Pacific countries. This has manifested itself in numerous product consignment rejections, price discounts, and/or difficulties in maintaining access to certain markets. At home, consumers are increasingly demanding information about product composition, safety and origins, and the production processes used. Some consumers are turning to imported products or other trusted brands, directly sourcing of foods from farmers, or deciding to avoid certain foods considered especially ‘risky’ (Ortega et al. 2012; Liu et al. 2013; Zhang et al. 2016). Ensuring the safety of food will have a profound effect on the success of efforts to alleviate poverty and promote shared prosperity in East Asia and Pacific. Food safety interacts with poverty in two critical ways: the poor as consumers of food and as agents in agri-food value chains. A growing body of evidence highlights the extent of food safety hazards in informal food markets, which are the main source of food for the poor, especially in urban areas. Where unsafe food disrupts markets or leads to consumer product avoidance, this can adversely affect the livelihoods of many people, including farmers, farm workers, operators of micro and small enterprises, and employees in larger commercial food companies. Improving food safety and building the capacity to do this will play an important role in achieving several SDGs, including those related to ending hunger, promoting good health and well-being, gender equality, clean water and sanitation, decent work and economic growth, and sustainable cities and communities. The economic burden of unsafe food, in both absolute and relative terms, varies across countries according to their level of economic development (Figure II.B.1). This can be construed as a food safety life-cycle. This is linked to the complex interplay of a range of factors that affect the incidence and potential exposure of populations to food safety

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hazards, the strength of incentives for actors in agri-food value chains to prevent or manage these hazards, and the costs of food safety missteps. Lower-middle income East Asia and Pacific countries fall within our category of ‘transitioning’ food systems where growing food safety challenges tend to strain or overwhelm existing capacity—typically translating into rising incidence and costs of unsafe food. Other East Asia and Pacific countries, such as China, Malaysia, and Thailand, fall into our category of ‘modernizing’ food systems where convergence occurs between food safety capacity and capacity needs. Developing East Asia and Pacific faces a special challenge and opportunity in relation to food safety. While OECD countries also encountered formidable food safety problems during their periods of urbanization and economic structural change, those processes took place over several decades, and institutional responses evolved and adjusted. Distinctive in developing East Asia and Pacific is the pace and magnitude of demographic, dietary, and food system change, as well as the complexity of the food governance problem. Uneven development and regional diversity mean that large countries do not have one food system but many, with different scales and modes of production coexisting. This complicates the approach to regulation and capacity development. The effectiveness of East Asia and Pacific countries in improving the incentives and capacities for food safety in the coming years will determine whether they will incur—or avoid—future economic costs amounting to billions of dollars per year associated with unsafe food.

Figure II.B.1. Food safety lifecycle: Relating the burden of unsafe food to levels of economic development Food safety economic burden Traditional

Transitioning

Lao PDR

Modernizing

Post-modern

Thailand

Indonesia Vietnam

China

Philippines

Malaysia

Cambodia

South Korea Singapore

Level of economic development Source: The Safe Food Imperative: Accelerating Progress in Low- and Middle-Income Countries.

The economic costs of safe food take multiple forms and have both short-and longterm dimensions ÌÌThe public health and economic costs of unsafe food Research is shedding new light on the global burden of foodborne disease (FBD). Until recently, data on the incidence of FBD and its associated costs were limited to high-income countries and regions. To address this gap, the World Health Organization’s (WHO) Foodborne Disease Burden Epidemiology Reference Group (FERG) spent nearly a decade gathering data and employing statistical models to estimate the burden of some 31 important foodborne hazards in 14 regions. The estimates are expressed in terms of disability-adjusted life years (DALYs) associated with illhealth and premature death.11 For 2010, the base year, the global burden of FBD was estimated at 600 million illnesses and 420,000 premature deaths. This aggregates to the equivalent of 33 million DALYs (Havelaar et al. 2015). For comparison, the estimated 2015 global burden of tuberculosis was 40 million DALYs and 66 million for malaria.

11 One DALY can be thought of as one lost year of a ‘healthy’ life. The sum of DALYs across a population is a measure of the burden of disease and can be thought of as a measurement of the gap between current health status and an ideal health situation where the entire population lives to an advanced age, free of disease and disability.

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The global burden of FBD is unequally distributed, with emerging Asia and Sub-Saharan Africa having the highest incidence (and death rates) of FBD. The WHO’s “South-east Asia” and “Western Pacific” regions combined to account for some 275 million foodborne illnesses and 225,000 FBD-related deaths per year. These represent 46 and 54 percent of the global totals, respectively. Epidemiological studies show that the most vulnerable people to foodborne disease are the young, old, malnourished, poor, pregnant and those who are immuno-compromised (Grace 2015). A disproportionate share of the burden falls on children under the age of five. Some 100 million children in Asia are estimated to fall ill from FBD each year. Within East Asia and Pacific, both the absolute and the relative public health burden of FBD differs significantly among countries. This can be seen in Table 1 where the burdens of different (types of) disease are expressed in terms of DALYs per 100,000 people. Several countries, including Indonesia, Lao PDR, Myanmar, and Thailand, have some of the world’s highest FBD burdens outside of Sub-Saharan Africa. At the same time, these countries continue to face high burdens from other diseases, especially tuberculosis and/or HIV/AIDs. In contrast, for Vietnam the estimated FBD burden is lower and on a par with that of these other diseases, while China’s progress in combating communicable diseases now raises the health significance of addressing food safety risks. Data from the WHO suggest some progress being made in East Asia and Pacific in combating the ‘big three’ diseases. Unfortunately, time series data are not available in relation to foodborne disease. The estimates for foodborne disease are considered to be highly conservative, as reliable data are not available in relation to certain pathogens and chemicals.12, 13 Table II.B.1. Comparative public health burden: Disability adjusted life years lost per 100,000 people Tuberculosis (2016) HIV/AIDS (2016) Malaria (2016) Food-borne disease (2010)

China

Indonesia

Lao PDR

Malaysia

148 67 1 272

1514 900 50 693

1820 337 36 933

146 10808 1 293

Myanmar The Philippines

1716 904 31 711

1063 25 3 293

Thailand

Vietnam

299 1205 3 685

414 440 1 390

Source: WHO Global Burden of Disease Statistics and Foodborne Disease Epidemiology Reference Group.

Animal products—including meat, fish and milk—and fruits and vegetables probably account for most FBD in most countries (Hoffmann et al. 2017). New research suggests that animal products account for 50 percent or more of the burden of FBD in several East Asia and Pacific countries, including Cambodia, China, Lao PDR, Papua New Guinea, the Philippines, and Vanuatu. This share is below 25 percent for several other countries, perhaps due to dietary restrictions (i.e., Indonesia and Malaysia) or other reasons for low per capita consumption of some animal products (i.e., Fiji and Myanmar) (Li et al. Forthcoming). Contamination in processed foods is generally not a major source of FBD, despite some high-profile individual cases in developed and developing countries (including the melamine case in China in 2008). While current estimates attribute very little of the global burden of FBD to cereals, the recent work by Gibb et al. 2018 on the incidence of heavy metals in foods may adjust this picture. The economic costs of unsafe food take multiple forms and have both short- and long-term dimensions, although valuing these costs is challenging because of data and methodological limitations. Examples include the public health costs and loss of productivity associated with FBD, disruptions to food markets when outbreaks of illness occur as consumers avoid implicated foods or shift to alternatives that are perceived to be safer, impediments to agri-food exports due to real or expected food safety problems, and the costs of complying with food safety regulations and standards in foreign markets. More indirect and harder-to-measure costs include the costs of prevention and those associated 12 Recent research (Gibb et al. 2018) has estimated the global burden of disease and premature death from heavy metals contamination in food. This will add significantly to earlier estimates which mostly covered microbiological pathogens. Heavy metals contamination is estimated to be a very significant problem in China and parts of South and Southeast Asia. 13 Foodborne illness reporting itself also tells us little, as the majority of people falling ill do not seek medical attention and illness symptoms are not always attributed to food sources. As a result, in most countries official national statistics on foodborne outbreaks and foodborne illnesses represent just the tip of the iceberg of the underlying problems and events.

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with wary consumers shifting from high-nutrient fresh produce to processed foods. For most low- and middle-income countries, reliable estimates of these costs and how they are distributed within society are lacking. A recent World Bank global study estimates that 'productivity losses' in emerging Asia attributed to unsafe food totaled some $63.1 billion in 2016.14 One can add to this an estimated cost of treating foodborne illnesses of $7 billion for these countries. Hence, even without taking into account the costs of market disruptions, product recalls, and consumer product avoidance, which are not possible to aggregate based upon available information, the domestic costs of unsafe food in emerging Asia may equal $70 billion. As a result of their enormous population size, ‘productivity loss’ estimates due to foodborne disease for emerging Asia are dominated by China and India (Figure II.B.2), although for several other countries the estimated losses exceed $500 million and, for both Indonesia and Thailand, may exceed $2.5 billion per year. Figure II.B.2. E stimated ‘productivity loss’ due to foodborne disease, 2016

Figure II.B.3. The relative economic cost of unsafe food: FBD 'productivity losses'/total food expenditures

$ billion

Percent, 2010

35 30 25 20 15 10 5 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0

6 ZAF

5 GHA NGA CIV

4

3

IDN IRN

BGD NPL COD PAK ETH

MYS BOL

SDN VNM

EGY

MAR PHL GCA

KHM UZB

CHN DZA ECU PER

TUN JOR

1 HND

GEO

UKR

COL

BRA

JAM

MEX

SLV TKM MKD

BIH

SRB BGR AZE BLR

CRI KAZ

ARG ROU

RUS

TUR

0 CHN IND

JJEAP

BDI

THA

LKA

SEN NER MWI

2

RCB

LSO IND MRT TCD

KEN

IDN

THA

PAK BGD PHL MYS VNM LKA MMR NPL

LAO

AFG KHM

0

2,000

JJSouth Asia

6,000

8,000

10,000

GNI per capita, 2010 QQSouth Asia and EAP

Source: Jaffee et al. 2019 based on FERG and World Development Indicators.

4,000

QQMENA

QQLAC

QQSSA

Source: Jaffee et al. 2019.

The estimated ‘productivity loss’ as a share of total national food expenditures in East Asia and Pacific varies greatly by country ( Figure II.B.3).15 Indonesia and Thailand have the highest ratios in the East Asia and Pacific region. The proportional economic burden for China and Malaysia appears to be lower, but remains higher than in countries from Latin America, Eastern Europe, and Central Asia with similar per capita income levels. The lower proportional costs for Cambodia, the Philippines, and Vietnam may indicate earlier stages of the food safety life-cycle (and the process of dietary transformation) rather than better-performing food safety systems. That is, their situations may grow decidedly worse (or better) depending upon future changes in dietary patterns, value-chain organization, and production practices, and the efficacy of current or future investments in food safety capacity. Beyond the burden of FBD, food safety is also critical for the agri-food trade performance of East Asia and Pacific countries, with important consequences for the performance of formal sector businesses, employment and incomes. Effectively competing in international agri-food trade may entail considerable compliance costs for the public and/or private sectors to meet the requirements of food safety regulations or standards in a given export market. 14 As estimated by national FBD DALYS multiplied by gross national income per capita. The total for emerging Asia is about two-thirds of the global total for low- and middle- income countries, as estimated by Jaffee et al. 2019. 15 This is illustrated for 2010 because reliable data on total food expenditures are not available for more recent years for some of the comparator (and especially low-income) countries in other regions.

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The magnitude of these costs is clearly an issue for export competitiveness. International experience suggests that (World Bank 2005; Beghin and Orden 2012): •• multiple factors influence compliance costs, including firm and industry size, the gap between prevailing food safety management capacity and that required for compliance with export market requirements, and levels of collective action between exporting firms; •• food safety challenges tend to re-enforce or accentuate the broader set of competitive strengths and weaknesses of industries and firms—in some cases, ‘trade losses’ attributed to (non-compliance with) more stringent standards are actually due to more entrenched and longer-term competitiveness issues within businesses and/ or sectors; and •• more stringent food safety regulations and standards can act as non-tariff barriers to trade, while they may also act as powerful catalysts for investments in improved food safety management systems, especially when the incentives for such investments are lacking in domestic markets. The most commonly observed impact on trade of food safety requirements is the rejection of consignments of agri-food products following border inspection in the destination export market. While data on border rejections have limitations, they do provide a picture of recurring issues with compliance with food safety requirements and how compliance issues vary across exporting countries, destination markets and/or over time. For example, UNIDO provides an analysis of food import rejections for the EU, the U.S., Japan, and Australia from 2002 to 2013 (UNIDO 2015). This and other analyses indicate that the vast majority of border rejections in industrialized country markets are accounted for by a small number of countries and for recurring reasons. Table II.B.2. Comparative rejection rates for high value foods entering the EU (2014–16) Interceptions per $100 million in EU imports

Fish & Fishery Products Country

East Asia and Pacific

South Asia

Other Peers

Vietnam Malaysia Thailand Indonesia Myanmar China Philippines Pakistan Sri Lanka India Bangladesh Maldives Peru Morocco Chile Ecuador Argentina Russia

Rate

5.1 4.4 2.1 1.8 0.9 0.8 0.7 7.4 6.6 2.3 0.5 0.4 1.2 1.1 1.0 0.6 0.6 0.2

Fresh Fruit and Vegetables Country

East Asia and Pacific

South Asia

Other Peers

Thailand Malaysia Vietnam China Indonesia Bangladesh India Sri Lanka Pakistan Turkey Brazil Morocco Chile Ecuador Mexico

Rate

18.5 8.9 2.1 1.1 0.4 48.4 7.9 6.4 3.4 2.9 0.7 0.3 0.2 0.1 0.1

Source: European Union Rapid Alert System for Food and Feed Portal and International Trade Center UNCTAD/WTO Data.

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Figure II.B.4. Developing East Asia and Pacific exports of high value foods $ billion 30

25

20

15

10

5

▬▬Fish

▬▬Processed meat, fish

▬▬Processed fruits, vegetables ▬▬Meat

▬▬Fresh vegetables

▬▬Fresh fruits

▬▬Nuts

▬▬Spices

20 17

20 15

20 13

20 11

20 09

20 07

20 05

20 03

0

20 01

While country- (and industry-) specific performance varies, the countries of East Asia and Pacific and emerging Asia more generally have accounted for a disproportionate share of regulatory interceptions in industrial country markets due to food safety violations. Table II.B.2 compares the rejection rates for fish products and for fresh fruit and vegetables entering the European Union—that is, the number of consignment interceptions due to food safety violations per $100 million worth of EU imports. Fish product exports are most commonly intercepted due to the presence of heavy metals in seafood or antibiotic residues in farmed fish, while violative pesticide residues are the most common cause of concern on imported fruits and vegetables. For fish and fishery products, several East Asia and Pacific (and South Asian) countries have rejection rates that are double or even quadruple those for leading peer countries from other regions. The performance gap is even wider for fresh fruit and vegetables.16

▬▬Dairy products

Source: International Trade Center UNCTAD/WTO Data.

While posing non-trivial costs to East Asia and Pacific export industries, food safety (compliance) challenges do not seem to have systematically weakened the competitiveness of East Asia and Pacific high value agro-food exports. China, Indonesia, Thailand, and Vietnam are all among the world’s top ten exporters of fishery products and have been increasing their global market share for leading commodities, especially shrimp and other farmed aquatic products. China, Thailand, and Vietnam have been experiencing sustained growth in trade in fresh and/or processed fruits and vegetables, although a growing proportion of this trade has been oriented to other middle-income countries. For the region as a whole, exports of high-value food safety-sensitive products grew from $22.6 billion in 2001 to $97.3 billion in 2017 (Figure II.B.4). While trade interceptions (and periodic threats of reduced market access) have high visibility and tend to mobilize action on the part of industry organizations and governments, the costs of unsafe (or improperly-labelled) export products and of measures to address the underlying problems are modest in comparison with the domestic costs of unsafe food in most East Asia and Pacific countries. A crude estimate of the trade-related costs would be equivalent to 3 percent of the value of high-value food exports, or just under $3 billion. This should be seen in relation to the $70 billion estimated earlier for annual productivity losses and costs of treatment for domestic foodborne illness.

ÌÌThe status of food safety capacity The safety of food is the result of the actions and inactions of many stakeholders, operating under diverse environmental, infrastructure, and socio-political conditions. These stakeholders include farmers, food handlers and distributors, food manufacturers, food service operators, consumers, regulators, scientists, educators, and the media.

16 Some of these interceptions involve small consignments or do not require the removal of the product from the market. However, high violation rates from specific countries often trigger more frequent consignment inspection/testing and site visits by risk-based regulatory authorities and/or demands for changes in supply chain oversight and practices in the source countries.

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Their behavior can be shaped by their awareness of food safety hazards; their technical, financial and other capabilities to apply effective mitigating practices; and prevailing rules, incentives and other motivators. Food safety capacity comes in many forms. First, it is embedded in human capital across all those who are involved in the handling or oversight of food. This may involve very basic knowledge, more specialized technical expertise, and/ or softer management, leadership, and communication skills. Second, it is embedded in the physical infrastructure that provides clean water and other basic services, houses food production, storage and distribution functions, and supports quality assurance services. A third type of capacity is embedded in management systems—within enterprises, regulatory agencies, laboratory testing entities, and, even, households. A fourth and somewhat less tangible type of capacity relates to institutional norms, including social cues, brand reputations, professional ethics, and the depth and breadth of a food safety culture. Motivations to invest in or otherwise strengthen capacities and to put them to use can be influenced by laws and their enforcement, social pressures, market signals, or other factors. The mix and strength of these motivators tends to vary at different stages of economic development; this is one of the determinants of the food safety lifecycle noted earlier. A review of the half dozen food control assessments carried out in recent years in South and Southeast Asia points to common patterns in terms of regulatory status, institutional capacity and coordination, and related matters in many countries: (FAO 2015a; 2015b; 2016): •• Countries lack a comprehensive national policy on food safety, resulting in a lack of prioritization of key problems and elements of food safety capacity. •• The lack of reliable data to assess the scale and distribution of many food safety problems. Research from different disciplines use different samples and methods that cannot be easily analyzed in an integrated way. Research tends not to link up with broader changes in the food system and therefore cannot inform forwardlooking policy making. •• Progress on food law modernization, although some laws do not cover the whole food chain and there has been less progress on the development of regulations to enable enforcement of the law. Countries have many standards, yet there is a lack of clarity on their voluntary versus mandatory nature. •• The absence of effective mechanisms for the accreditation and certification of businesses. Plus, food-processing and -handling enterprises are generally categorized based on size and market orientation rather than on risk considerations—so that the inspections of enterprises and facilities are not risk-based. •• The fragmentation of institutional responsibilities among lead agencies and ministries and between central and decentralized units with often weak coordination due to overlapping mandates or gaps. There is therefore a lack of coordination in monitoring hazards, risks, and illness outcomes. There are also fragmented systems for laboratory testing as labs do not function as a network and do not yield inferences on food safety. The assessments done by the World Organization of Animal Health on the performance of veterinary services (PVS) are also useful for gauging the status of official food safety capacities. The fundamental components of these assessments pertain to human, physical and financial resources; technical authority and capability; interaction with interested parties; and measures to ensure market access. The most recent version of the PVS assessment tool covers 38 critical competencies, with experts rating each capacity on a 1 to 5 scale with the former indicating little or no capacity, the latter a high level of competence or application of best international practice, and intermediate designations in between. A subset of these criteria is either directly associated with food safety of animal products or is likely to have a

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strong influence on how well food safety oversight is performed. Specifically, ratings for 18 such criteria—including two associated with funding adequacy, 12 associated with technical capacities and regulatory functions and four related to international market access—can be used to gauge and compare the status of official control systems for animal source food safety. Jaffee et al. (2019) combines the technical capacities and market access measures to construct an index of capacity. The PVS assessments point to significant variations in the status of animal source food safety systems across the region. Since 2010, assessments have been done in 13 developing East Asia and Pacific countries, and the results can be compared with 80 other (mostly low- and middle-income) countries from other regions. Only three East Asia and Pacific countries—Malaysia, and Philippines, and Thailand—have capacity index scores in the top one-third of this sample, while several countries—including Cambodia, Lao PDR, Mongolia, and Timor-Leste—have capacity index scores falling in the bottom one-third of the sample. However, it is instructive to gauge these capacities Figure II.B.5. Capacity and need for capacity for food safety systems for animal sourced foods in relation to current needs. Countries demonstrate Capacity index considerable differences in terms of the prominence 85 of animal products in local diet, national trade, and 75 importance of livestock in agricultural GDP. These and 65 other factors have been considered in constructing a 55 ‘capacity need index’ in relation to animal source foods. Figure II.B.5 thus maps animal source food safety capacity 45 and current capacity needs for East Asia and Pacific (and 35 South Asian) countries and plots these countries against 25 other low- and middle-income countries. In the bottom 15 left quadrant we see multiple countries whose capacities 15 25 35 45 55 65 75 85 95 are low but so too are their immediate needs. The latter Need index are likely to increase over time if urbanization and Source: Based upon data from OIE PVS Assessments, FAO, and World Development Indicators. income growth result in much higher consumption and expenditures on animal products. Countries in the bottom right quadrant appear to be most at risk, featuring a high need for capacity yet major gaps in this capacity. Mongolia is positioned here. The region has few members in the top right quadrant where high capacity need is being met by strong underlying capacity. Both Thailand and Malaysia appear to be borderline for this status. THA

MYS

PHL

FJI

BTN IDN

PNG

VNM

VUT

MMR

PAK

AFG

MNG

LAO

MDV

KHM

BGD

TLS

In most East Asia and Pacific countries, the capacities for food safety regulatory oversight tend to be stronger for exports than for the domestic market. This stems from a variety of factors, including the clarity of requirements for ‘competent authorities’ coming from external (and especially OECD country) trade partners, a more narrow or concentrated industry structure over which regulatory checks can be more readily made, the presence of better organized industry associations in some export industries, and a legacy of earlier investments made to improve the competitiveness of export industries and/or resolve specific food safety-related problems. This stronger capacity for export-oriented regulatory controls does not appear to be matched by similarly effective or risk-based controls on food imports. A 2016 survey of hundreds of food companies compared perceptions about how well food import controls follow World Trade Organization (WTO) guidelines and conceptions of good international

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practice in relation to pre-border, border, and post-border controls (APEC Business Council 2016). Countries were ranked in terms of the transparency and scientific basis for sanitary and phytosanitary measures, the clarity of institutional roles and responsibilities, the consistency and impartiality in the application of food import controls, how well standards were harmonized with international norms, and other matters. In this assessment, the middle-income countries of East Asia and Pacific were rated exceptionally poorly, both directly and compared with high-income countries and middle-income peers from Latin America. With available data, it is not possible to make any strong generalizations or comparisons in terms of food safety capacity in the private sector. Food industry structure varies enormously within the region, in terms of the size distribution and concentration levels in different segments of food manufacturing and the patterns of food distribution, including the relative significance of different forms of ‘modern retail’ (i.e., supermarkets, convenience stores, e-commerce operations) vs. traditional community markets. Levels and formats for out-of-home eating, each with their own challenges for managing food safety risks, also vary significantly among the countries of East Asia and Pacific, and emerging Asia more generally. Citing data or circumstances for one or even several countries would therefore not provide a representative picture. A few proxy indicators can be cited, although these relate primarily to companies or value chains with an export market orientation. For example, both China and the Philippines are among the top ten developing countries in terms of the area under cultivation of GlobalGap certified production of fruits and vegetables, while China and Vietnam are among the top ten countries for area under cultivation of certified organic production of fruits and vegetables. Still, the shares of the area under cultivation that meet these standards in East Asia and Pacific countries (16 and 31 percent, respectively) are lower than the region’s share of overall low- and middle-income country fruit and vegetable production.17 China, Indonesia, the Philippines, Thailand, and Vietnam are all among the top 15 developing countries in terms of the number of food manufacturing enterprises that remain registered with the U.S. Food and Drug Administration and are therefore eligible to export to the United States. East Asia and Pacific countries account for just under one-third of the total number of low- and middle-income country enterprises with such registration.18 Very significant challenges also remain in improving hygienic conditions and vendor practices in community markets and in relation to street foods. Survey and other evidence from many Asian cities point to low food safety awareness and/or high-risk behaviors in these segments of food distribution which service a large proportion of urban populations and the majority of the urban poor. Evidence from small-scale studies of street food and other informal vendors suggest worryingly high contamination levels. Among the common risk factors are (Sezgin and Sanher 2016; Alimi 2016): •• Inappropriate and unhygienic locations and surroundings, as vendors target high human-traffic areas that may be exposed to airborne chemicals in dust and vehicle exhaust fumes. •• Lack of knowledge on temperature control, which is especially problematic when delays between food preparation and consumption are long, along with low awareness of chemical and microbial contamination. •• Poor personal hygiene practices, either due to low knowledge or lack of nearby facilities.

17 East Asia and Pacific countries account for a significant share of the developing country area of certified GlobalGap and organics F&V production. However, this certified area still only accounts for a low proportion of the total area and production of F&V in these countries. For example, in China and Vietnam, the certified organics area represents only 0.45 and 0.80 percent, respectively, of the total planted area for F&V. 18 Comparable data on the food safety capacities or regulatory compliance of SMEs are not available. Depending upon the objectives of data disclosure, regulatory agencies seem to waiver between statistics pointing to (implausibly) high rates of compliance and communicating information about the (significant) number of companies that have been fined or closed down during regular or seasonally enhanced regulatory inspection campaigns. It is clear, however, that large numbers of SMEs in East Asia and Pacific will need to upgrade their facilities and food safety and supply chain management capacities to meet rising consumer demands and regulatory requirements in the coming years.

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•• Unsuitable methods of transportation of food and ingredients, especially inner-city movements of meat and animal carcasses by carts, motor bikes, and on bus rooftops. •• Poor design and construction of street food carts, especially the work surfaces, which inhibit cleanliness and thereby harbor microorganisms. •• Unclean places of preparation—including surfaces, equipment, and utensils—whether at the vending site or in the home, where condiments may be prepared ahead of time. •• Use of contaminated water and ice when noncontaminated sources are not available, as well as use of nondisposable plates, cups, and cutlery. •• Poor storage practices, including the disposal of leftovers and waste management (most street vendors do not have access to refrigeration).

The way forward A significant share of East Asia and Pacific food safety problems and the associated costs are avoidable if a concerted set of preventative measures are put in place. Some countries have invested little in food safety, either in the public or private domains. Foundational investments will be needed in people, infrastructure and institutions, together with interventions in some priority value chains. For other countries, the challenges are to improve the functionality of public regulatory delivery and technical services while mainstreaming safer food practices among farmers and food business operators of various sizes. There are no simple solutions and quick fixes to the myriad of food safety challenges faced in East Asia and Pacific. To the contrary, the effort requires a comprehensive approach to improving food safety awareness, practices, and governance, including addressing fragmented and often weakly coordinated institutional responsibilities, building up capacities for risk analysis and risk communications, enhancing systems for surveillance and food product traceability and recall, and moving from an end-product testing focus to one which places emphasis on supporting ‘good agricultural practices’ among farmers and upgrading private sector management systems. Increasing consumer awareness and improving consumer food storage, handling and preparation practices are also very important. As emphasized by the WHO, food safety is a shared responsibility—of food business operators, consumers and government entities. Operationalizing this concept effectively is a significant challenge in many East Asia and Pacific countries. Governments need to play effective vision-setting and convening roles, provide reliable information to other stakeholders, and effectively deploy a wide set of policy instruments, both carrots and sticks, to involve, incentivize, and leverage the actions of others. While practitioners once emphasized effective “official food control” systems, the most critical roles for government are now recognized to be facilitative ones that induce investments and behavior changes by actors who share with government the goal and responsibility of safer food.19 This inclusive concept of food safety management may require a paradigm shift in how East Asia and Pacific countries approach food safety regulation. The traditional model centers on enforcement through inspections of food facilities and product testing, and systems of legal and financial penalties for infractions. This strict authoritative model appears to appeal to the public, media, and therefore political decision makers. However, it is not altogether an effective model, particularly where smallholder farmers, micro and small enterprises, and informal food channels 19 The private sector, both as individual companies and through industry associations, can play a major role in advancing food safety science, applying emerging technologies, developing food safety human capital, providing quality assurance services, and promoting safer practices in primary production and food value chains.

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predominate, or where surveillance and inspectorate capacities are limited. A shared responsibility model implies a move from a regulator-regulated relationship toward efforts by governments to better incentivize and facilitate the delivery of safe production, processing, and distribution of food. The role of regulation then becomes one in which the absolute minimum food safety standard is applied, thereby leaving food business operators with some degree of flexibility in how they attain that standard, and for government to offer information and other resources and support to motivate and assist compliance. Governments in East Asia and Pacific need to invest more, and more smartly, in food safety. This means investing with clear purpose and tracking the impacts of interventions; investing in the foundational knowledge, human resources, and infrastructure for food safety systems; balancing attention to hardware and software; realizing synergies among investments and in the pursuit of goals (i.e., initiatives addressing both animal and human health, and both food safety and environmental health); and ensuring the sustainability of investments and outcomes. Not all investments that can reduce the burden of foodborne disease are ones typically regarded as “food safety” investments. Critical investments may address environmental health issues, such as those that increase access to potable water and improve sanitation or lessen environmental contaminants in soil, water, and air. Such measures reduce the propensity for cross contamination in food supply chains. Also important are investments in public health systems, including those that improve the quality of and access to medical treatment, which can reduce morbidity and mortality related to FBD. While improving food safety in East Asia and Pacific will require fundamental improvements in the scientific, statistical, and dimensions of food safety, Ministries of Finance and other central economic ministries also have major roles to play. It is recommended that such entities: (i) evaluate the benefits of public expenditures for food safety in light of the economic costs of unsafe food; (ii) emphasize forward-looking preventive measures to minimize future costs (avoidable losses) for, among other things, public health and market development; (iii) balance public expenditure and investment between “hardware” (laboratories, market places) and “software” (management systems, human capital, awareness-raising for behavioral change); and (iv) ensure that proposals for significant public investments or programs are justified using cost-benefit or cost-effectiveness analysis, and that alternative approaches, including regulatory measures and facilitating private investment, have been considered. Lead food safety agencies and pertinent technical ministries (i.e., agriculture, health, trade, and environment) should develop a unified food safety strategy that defines priorities and responsibilities, guides the coordination of measures by government and private entities, and establishes funding needs. They are also advised to: (i) adjust key performance indicators to focus more on food safety outcomes (magnitude of food safety risks, incidence of foodborne disease, standards-compliant trade) and less on noncompliant outcomes (infringements, value of fines collected, number of businesses closed); (ii) take measures to minimize hazard entry into the food supply from farms, especially measures that also have benefits for public health and environmental protection; (iii) direct attention to small and informal actors in the food system, with an emphasis on awareness-raising, adopting safer food handling practices, and improving physical operating conditions (that is, access to clean water and waste management facilities); (iv) remove policy, regulatory, or other barriers to private investments and services for food safety; (v) apply risk-based approaches to govern food trade, together with improved trade facilitation capabilities; (vi) provide consumers with the tools to become partners in food safety through their own actions and through incentivizing and motivating food suppliers; and (vii) incorporate the science of behavior change by redesigning training programs, information campaigns, and other interventions.

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Clearly, however, East Asia and Pacific countries face different mixes of food safety challenges, different food market structures, and different strengths and weaknesses in food safety capacity and incentives. Specific priorities and the appropriate sequencing of investments and initiatives need to be determined at the individual country level, and in very large countries, also at sub-national levels. The World Bankâ&#x20AC;&#x2122;s recent publication, The Safe Food Imperative, provides guidance to countries at different positions in the food safety life-cycle on ways to effectively position food safety in the national development dialogue, as well as likely priorities in relation to food safety risk assessment, risk management, and risk communications (and broader awareness raising) (Jaffee et al. 2019).

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Part II References Alimi, B. 2016. “Risk factors in street food practices in developing countries: A review.” Food Science and Human Wellness 5 (3): 141–48. APEC Business Advisory Council. 2016. “Non-tariff barriers in agriculture and food trade in APEC: Business perspectives on impacts and solutions.” University of Southern California, Los Angeles. Beghin, J., and D. Orden. 2012. “NTMs, Agricultural and Food Trade, and Competitiveness.” A Special Issue of The World Economy. City, Publisher. FAO (Food and Agriculture Organization). 2015a. “Assessment and Recommendations for Enhancements to Vietnam’s Legislative Framework, Structural and Institutional Arrangements, National Management Arrangements and Related Implementation Strategies. Hanoi.” Food and Agriculture Organization, Rome. ———. 2015b. “Assessment and Recommendations for Strengthening Inter-Ministerial Coordination in Myanmar.” Food and Agriculture Organization, Yangon. ———. 2016. “Review of Food Safety Control Systems in Sri Lanka.” Food and Agriculture Organization, Colombo. ———. 2018. “Dynamic Development, Shifting Demographics, and Changing Diets. FAO.” Food and Agriculture Organization, Bangkok. Gibb, H., A. Barchowsky, D. Bellinger, M. Bolger, C. Carringon, A. Havelaar, S. Oberoi, Y. Zang, K. O’Leary, and B. Devleesschauwer. 2018. “Estimates of the 2015 global and regional disease burden from four foodborne metals – arsenic, cadmium, lead and methylmercury.” Environmental Research. https://doi.org/10.1016/j. envres.2018.12.062 Gordon, David, Elhin Fahmy, Alba Lanau, Joanna Mack, Hector Najera, Shailen Nandy, and Marco Pomati. 2018. “The Advantages of the Consensual Approach to Poverty Measurement – Paper 5.” Presented at the Inaugural Meeting of the Pacific Statistics Methods Board, May 3–4, Aukland, New Zealand. https://sdd.spc.int/images/ documents/Meetings/Methods_Board/3-4_May_2018/Board_Paper_No._5_-_Consensual_Approach_to_ Poverty_Measurement.pdf. Grace, D. 2015. Food Safety in Developing Countries: An Overview. Hemel Hempstead, UK: Evidence on Demand. Havelaar, A., M. D. Kirk, P. R. Torgerson, H. J. Gibb, T. Hald, R. J. Lake, N. Praet, D. C. Bellinger, N. R. de Silva, N. Gargouri, N. Speybroeck, A. Cawthorne, C. Mathers, C. Stein, F. J. Angulo, and B. Devleesschauwer. 2015. “World Health Organization Global Estimates and Regional Comparisons of the Burden of Foodborne Disease in 2010.” PLOS Medicine 12 (2). Hoffmann, S., B. Devleesschauwer, W. Aspinall, R. Cooke, T. Corrigan, A. Havelaar, F. Angulo, H. Gibb, M. Kirk, R. Lake, N. Speybroeck, P. Torgerson, and T. Hald. 2017. “Attribution of global foodborne disease to specific foods: Findings from a World Health Organization structured expert elicitation.” PLoS ONE 12 (9): e0183641. Jaffee, S., S. Henson, L. Unnevehr, D. Grace, and E. Cassou. 2019. “The Safe Food Imperative: Accelerating Progress in Low- and Middle-Income Countries.” World Bank, Washington, DC. Jolliffe, Dean, and Espen Beer Prydz. 2016. “Estimating International Poverty Lines from Comparable National Thresholds.” The Journal of Economic Inequality 14 (2): 185–98. Li, M., A. Havelaar, S. Hoffmann, T. Hald, M. Kirk, and P. Torgerson, and B. Devleesschauwer. Forthcoming. “Global Disease Burden of Animal Sourced Foods, 2010.” CITY, PUBLISHER. Liu, Rongduo, Zuzanna Pieniak, and Wim Verbeke. 2013. “Consumers’ Attitudes and Behaviour towards Safe Food in China: A Review.” Food Control 33 (September): 93–104.

Part II References

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Mack, Joanna. 1985. “How poor is too poor? Defining poverty.” In Poor Britain, edited by Joanna Mack and Stewart Lansley. London: George Allen & Unwin. Narayan, Ambar, and Judy Yang. 2018. “Part 2.A. Intergenerational Mobility in East Asia and Pacific.” In East Asia and Pacific Economic Update October 2018, Navigating Uncertainty. Washington, DC: World Bank. ———. 2006b . Ortega, D. L., H. H. Wang, N. J. Oylink, L. Wu, and J. Bai. 2012. “Chinese Consumers’ Demand for Food Safety Attributes: A Push for Government and Industry Regulations.” American Journal of Agricultural Economics 94 (2): 489–495. Sezgin, A. C., and N. Şanlıer. 2016. “Street food consumption in terms of the food safety and health.” Journal of Human Sciences 13 (3): 4072–4083. UNDP (United Nations Development Programme). 2010. Human Development Report 2010: The Real Wealth of Nations. New York: Palgrave Macmillan. UNIDO (United Nations Industrial Development Organization). 2015. Meeting Standards, Winning Markets: Trade Standards Compliance. Vienna: United Nations Industrial Development Organization. World Bank. 2005. “Food Safety and Agricultural Health Standards: Challenges and Opportunities for Developing Country Exports.” World Bank, Washington, DC. ———. 2016. Poverty and Shared Prosperity 2016: Taking on Inequality. Washington, DC: World Bank. ———. 2017. Monitoring Global Poverty: Report of the Commission on Global Poverty. Atkinson Report. Washington, DC: World Bank. ———. 2018a. Poverty and Shared Prosperity 2018: Piecing together the poverty puzzle. World Bank, Washington, DC. ———. 2018b. Riding the Wave: an East Asian miracle for the 21st century. Washington, DC: World Bank. ———. 2018c. Making growth work for the poor: a poverty assessment for the Philippines. World Bank, Washington, DC. World Bank and Ministry of Labour, Immigration and Population, Myanmar. 2018. The 2014 Myanmar Population and Housing Census: Multidimensional Welfare in Myanmar. Washington, DC: World Bank Group. http://documents. worldbank.org/curated/en/593661543241844346/Main-Report. Zhang, Lei, Xu Yunan, Peter Oosterveer, and Arthur P. J. Mol. 2016. “Consumer Trust in Different Food Provisioning Schemes: Evidence from Beijing, China.” Journal of Cleaner Production, Special Volume: Transitions to Sustainable Consumption and Production in Cities 134 (October): 269–79.

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Part III. Country Summaries and Key Indicators

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CAMBODIA

Population, million GDP, current US$ billion GDP per capita, current US$ School enrolment rate, primary (% gross)a Life expectancy at birth, yearsa

Motor vehicles and steel imports rose by 50 percent and 48 percent, respectively, in 2018.

2018 16.3 24.1 1,477 110.2 69.0

Source: WDI, Macro Poverty Outlook, and official data. Notes: a. Most recent WDI value (2016).

Growth achieved a four-year high of 7.5 percent in 2018, compared to 7.0 percent in 2017. Driven primarily by garment and footwear exports that responded to strengthening demand in the US, the economy performed better than expected. Given solid export growth in lowskilled manufacturing products, continued poverty reduction is expected. However, risks have intensified due to heightened uncertainty over preferential access by Cambodia to EU markets under the EBA scheme and a potential sharp slowdown in the Chinese economy.

Recent Developments Economic growth accelerated last year, driven primarily by rapid increase in exports, while imports also expanded. Exports burgeoned as external demand rose, in particular, in the US market. Garment and footwear exports, which account for more than two-thirds of total merchandise exports, recorded a four-year high, growing by 17.6 percent in 2018, up from 8.3 percent in 2017 (figure 2). Upbeat market confidence has been met by a surge in imports.

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The current account deficit is estimated to have widened to 10.4 percent of GDP in 2018, from 9.7 percent of GDP in 2017, but remains fully financed by foreign direct investment. Burgeoning exports have been accompanied by strong FDI inflows, estimated to have peaked at 13.4 percent of GDP in 2018. Both have contributed to further accumulation of gross international reserves, which in 2018 reached US$10.1 billion or about 6 months of prospective imports. More than half of the inflows originated from China, and are directed towards construction (infrastructure, commercial and residential real estate), tourism and, to a lesser extent, to manufacturing and agriculture. The seaside provincial town of Sihanoukville continues to be the hot spot of the current construction boom, financed largely by FDI from China. Improved confidence in the banking system has resulted in rising foreign currency deposits, which grew at 26.5 percent in 2018, up from 23.6 percent in 2017. Bank credit to the private sector once again edged up, growing at 24.2 percent in 2018, compared to 19.6 percent in 2017. Bank lending to the construction, real estate and mortgage sectors continues to drive domestic credit expansion, contributing about a third of credit growth. This is followed by the wholesale and retail sector, which captured a 19 percent of credit. Inflation, meanwhile, has moderated. The easing of petroleum prices since the fourth quarter of 2018 more than offset the increase in food prices. As a result, inflation declined to 1.6 percent as of December 2018, from 2.2 percent in 2017. The Cambodian riel (CR) which is pegged to the US dollar due to high dollarization, has remained stable, at CR 4,018 per US dollar at the end of 2018, compared to CR 4,037 in 2017. Although good revenue performance continued, rapidly rising public payroll exerted pressures on the fiscal position. In 2018, the rising wage bill, together with an

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Cambodia

MANAGING HEADWINDS

initial boost in domestically financed capital spending, resulted in the widening of the fiscal deficit. The overall deficit (including grants) is estimated to have reached 3.4 percent of GDP in 2018, compared with 1.6 percent of GDP in 2017. Nonetheless, according to the 2018 World Bank/IMF Debt Sustainability Analysis, Cambodia’s debt distress level remains low, given the concessional profile of the debt.

Outlook After experiencing accelerated growth of 7.5 percent in 2018, the economy is expected to return to its long-term potential. As exports moderate in line with deceleration in global demand, real growth is projected to ease to 7 percent in 2019, while remaining near 7 percent in the short term. The robust economic growth is expected to result in continued poverty reduction. The longer-term outlook, however, depends on the country’s ability to absorb rising FDI inflows, while promoting domestic investment. In this regard, cheaper energy and logistics costs, availability of skilled workforce, and improved supply chain linkages will be essential to remain competitive.

Risks and Challenges In February, the European Union started the process that could lead to the potential suspension of Cambodia's preferential access under the Everything But Arms (EBA) scheme. The EU market currently accounts for more than a third of Cambodia’s key exports (including garments, footwear and bicycles). Therefore, losing EBA preferences, which currently provide Cambodia duty-free and quotafree access to the EU, would likely result in slower export growth. In addition, given Cambodia’s heavy reliance on capital inflows from China, a sharp slowdown in the Chinese economy could dampen growth prospects. Finally, the surge in capital inflows and credit, which has financed the construction and real estate boom, has also overextended the financial sector.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Cambodia

Against the backdrop of increasing uncertainty, it is important to minimize macroeconomic vulnerabilities. Needed measures include containing the increase in the public payroll, strengthening oversight capacity and crisis preparedness in the financial sector and considering further macroprudential measures such as limiting bank exposure to construction and real estate. It is also crucial for Cambodia to improve external competitiveness. Foreign investors confirm that low labor costs, high tax incentives and preferential access to key export markets are the reasons for their investment in Cambodia. With rapidly rising wages and risks of losing EBA trade preferences, it is critical that the country embarks on structural reforms, especially those that can help improve investment climate, and reduce cost of doing business, including introducing competitive energy prices and lowering logistic costs. The current cost of doing business also discourages domestic investment and entrepreneurship. Cambodia ranks 183rd out of 190 economies globally on ease of starting a business. Firms face cumbersome registration procedures and, in most cases, multiple licensing requirements from different agencies. Thus, many of them opt to remain informal, which constraints firms´ ability to link to global supply chains. Given Cambodia’s large FDI stock, it will be essential to improve productivity and capture knowledge spillovers, thus facilitating backward linkages with local firms.

93

2

5

1

0 -5 2014

JJAgriculture

2015

2016

JJGarment/footw. JJConstruction

JJOther services JJTaxes less subsidies

2017

2018

JJOther industries JJHotels, restaurants

Au g-

17

0

▬▬Total

▬▬US

c-1 8

10

De

15

3

Oc t-1 8

4

Au g-

20

18

5

Ju n-

25

r-1 8

6

Ap

30

Fe b

7

De

35

-1 8

y/y percent change

8

c-1 7

Figure 2. Garment and footwear exports

Percent

Oc t-1 7

Figure 1. Real GDP growth, contribution to real growth

18

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

▬▬EU incl. UK

▬▬GDP growth

Sources: Cambodian authorities.

CAMBODIA Selected Indicators Real GDP growth, at constant market prices Private Consumption Government Consumption Gross Fixed Capital Investment Exports, Goods and Services Imports, Goods and Services Real GDP growth, at constant factor prices Agriculture Industry Services Inflation (Consumer Price Index) Current Account Balance (% of GDP) Net Foreign Direct Investment (% of GDP) Fiscal Balance (% of GDP) Debt (% of GDP) Primary Balance (% of GDP)

Sources: Cambodian authorities.

2016

2017

2018e

2019f

2020f

2021f

7.0 6.9 5.7 10.1 8.6 8.6 6.9 1.3 10.9 6.8 3.5 -10.2 10.8 -1.4 29.1 -1.0

7.0 4.4 6.5 5.9 5.3 4.0 6.9 1.7 9.8 7.0 3.1 -9.7 10.8 -1.6 30.3 -1.2

7.5 6.5 1.1 1.7 5.3 4.1 7.6 1.4 11.7 7.1 3.2 -10.4 13.4 -3.4 30.6 -3.0

7.0 4.7 7.4 9.1 9.0 7.6 7.0 0.7 10.5 6.6 3.3 -9.4 10.4 -3.8 30.0 -3.3

6.9 4.5 6.4 8.4 8.6 7.1 6.9 0.8 9.3 7.3 3.0 -9.0 9.3 -3.2 30.1 -2.7

6.8 4.5 6.3 8.4 8.1 6.8 6.8 0.9 8.8 7.4 3.1 -9.1 9.2 -2.7 31.1 -2.2

Source: World Bank, Poverty & Equity and Macroeconomics, Trade & Investment Global Practices. Notes: e = estimate, f = forecast.

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PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Cambodia

MANAGING HEADWINDS

CENTRAL PACIFIC ISLANDS

2017 Population, million Kiribati Nauru Tuvalu GDP, current US$ billion Kiribati Nauru Tuvalu GDP per capita, current US$ Kiribati Nauru Tuvalu

0.12 0.01 0.01 0.19 0.11 0.04 1,594 8,344 3,550

Sources: WDI, World Bank staff estimates.

Economic activity and government revenues in the Central Pacific countries—Kiribati, Nauru and Tuvalu—are highly reliant on rents from a few key sources (fisheries, Tuvalu’s .tv internet domain, and Australia’s Regional Processing Centre for asylum-seekers located in Nauru). In the face of volatile revenues in Kiribati and Tuvalu, and an expected decline in revenues in Nauru, it is important for the Central Pacific countries to focus on expenditure quality and maintain fiscal discipline.

Recent Developments In Kiribati, economic growth has been above historical trend recently due to increasing donor-funded construction and record-high revenue from the country’s tuna fishery. Real GDP growth registered 5.1 percent in

2016 but moderated to 0.3 percent in 2017, following the completion of a major road investment. Inflation also dipped to 0.4 percent in 2017 following a reduction in electricity tariffs, but is forecast at 2.1 percent in 2018, in line with trading partners. Fishing license fees, investment income from the Revenue Equalisation Reserve Fund (RERF) and current transfers have more than offset Kiribati’s significant trade deficit (over 75 percent of GDP), leading to current account surpluses of 41.3 and 47.6 percent of GDP in 2016 and 2017 respectively, with a similar surplus projected for 2018. High fisheries revenues have allowed the government to run large budget surpluses (10 percent of GDP in 2018) while also significantly increasing recurrent spending (including a 30 percent pay rise for public servants in 2018) and making major capital investments. In late 2018 the government announced an ambitious expansion of the national airline at a cost of circa A$120m (47 percent of GDP) over 2018–2020. After doubling in size in the early part of the decade, Nauru’s small, undiversified economy has grown much more slowly in recent years, due to a slowdown in phosphate exports—with phosphate reserves now almost completely depleted—as well as a moderation in activity associated with Australia’s Regional Processing Centre (RPC) for asylum-seekers, which in recent years has been the main driver of economic activity. The economy is expected to have contracted by 3 percent in FY18 (from growth of 4 percent the previous year) with the RPC scaling down and refugees being resettled elsewhere. Inflation is expected to have eased to below 2 percent in line with declining activity and due to the improved functioning of the port after repairs in FY2016, though recent inflation data have not been produced. Government revenue has increased about five-fold (in real terms) since FY2012 due to RPC-related revenues and fishing license fees, as well as increased tax collection from the implementation of employment and services taxes and improvements in tax administration. However, government spending has also increased rapidly, particularly on the wage bill (in an effort to retain key public employees), but also on goods, services, and social

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Central Pacific Islands

95

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

benefits. Recent budget estimates indicate that surpluses of around 5 percent and 15 percent of GDP were realized in FY2017 and FY2018 respectively, and the government has continued to make contributions to the Nauru Trust Fund and to its cash buffers. The FY2019 budget projected a small surplus of about 0.1 percent of GDP, though a recent windfall deposit of fishing revenues (accruing from prior years) means a much larger surplus is now expected. Tuvalu’s economic growth continues to be driven by the public sector and donor-funded expenditures. In 2017, GDP growth was 3.2 percent, slightly up from 3.0 percent in 2016, supported by large infrastructure and housing projects ahead of regional summits. Inflation edged up to 4.4 percent as prices for transportation and imported food increased, reflecting in part higher oil prices. The current account remained in a surplus of 5 percent of GDP, as the trade deficit was more than offset by strong factor income and current transfers. Tuvalu maintained fiscal surpluses despite high expenditure in recent years thanks to revenue from fishing license fees and the “.tv” domain, and grants. The resulting post-grant surpluses have been used to replenish the Consolidated Investment Fund (CIF) and, more recently, to capitalize the Tuvalu Trust Fund and the newly established Tuvalu Survival Fund. In 2018, driven by one-off revenues, the budget surplus is expected to have reached AUD8.2 million, or 19 percent of GDP.

Outlook In Kiribati growth of around 2 percent is expected over the medium term as fishing revenues normalize from recent highs. Lower fishing revenues and large outlays for the national airline are expected to push the budget into deficit from 2019 onwards, with cash reserves drawn down to around the IMF-recommended minimum buffer of three months of recurrent spending over the medium term. Little to no economic growth is expected in Nauru in FY2019 as the RPC continues to scale down, and only modest growth averaging around 2 percent per annum is expected over the medium term. Work on the construction of a more reliable and climate-resilient port has recently

96

broken ground, with the US$80 million project likely to provide some support to overall economic activity over the next two to three years. In Tuvalu, ramping up construction is expected to drive growth to about 4 percent in 2018, and inflation is expected to moderate as oil price pressures ease. Declining fishing license fees and rising infrastructure-related imports are expected to deteriorate the current account. The government is expected to register a fiscal deficit of AUD1.4 million, or 2.9 percent of GDP, in 2019. The government’s projections show moderate surpluses for 2020 and beyond.

Risks and Challenges Kiribati is contending with a large deficit in essential services, with growing strain from internal migration, population growth and climate change. Increasing the quality of expenditure and strengthening the project selection process is vital to addressing these challenges and reducing poverty. In Nauru, growth remains dependent on the still uncertain outlook for the RPC and the extent to which donor support compensates for any revenue shortfalls and acts to stimulate domestic incomes and output. Fishing license fees have remained above 20 percent of GDP in recent years and are likely to remain an important source of revenue, though the central case is for continued declines in RPC-related revenue, highlighting the importance of continued fiscal discipline and increased efforts to diversify the economy. Given its size and geographical constraints, Tuvalu’s economy is highly volatile and dependent on external flows. In the absence of an independent monetary policy, fiscal policy remains the only tool to respond to shocks. Given the potential for a tightening in available resources, improving the quality of expenditure, containing the deficit and strengthening fiscal buffers will be important. It will also be important for the government to consolidate the budget while protecting high-priority expenditure on infrastructure and the social sector, while ensuring constant or growing real balances in Tuvalu’s trust funds.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Central Pacific Islands

MANAGING HEADWINDS

Figure 1. Sources of domestic revenue - projections to 2020

Figure 2. Sovereign wealth fund balances - projections to 2020

Percent of GDP

Fund balance, A$ millions (lines)

120

1,200

100

1,000

80

800

60

600

Per capita value, A$, in thousands (bars) 25

20

15

10

40

400

20

5

200

Nauru

JJRegional processing centre

f 20

f

0

20

18

19

20

17

20

16

20

15

20

20

f

f

20 20

18

19

20

17

20

16

20

15

20

20

f

f

20 20

18

Kiribati

JJFishing license fees

19

20

17

20

16

20

20

20

15

0 0

Tuvalu

JJ.TV domain

JJOther revenue

Sources: Country authorities, and World Bank and IMF staff estimates and projections. Nauru data in June years; Kiribati and Tuvalu in calendar years.

2015

JJKiribati

2016

2017

JJNauru

2018

2019f

2020f

JJTuvalu

Sources: Country authorities, and World Bank and IMF staff estimates and projections. Nauru data in June years; Kiribati and Tuvalu in calendar years.

CENTRAL PACIFIC ISLANDS S elected Indicators Real GDP growth, at constant market prices Kiribati Nauru Tuvalu

2015

2016

2017

2018f

2019f

2020f

10.4(r) 2.8 9.1

5.1(r) 10.4 3.0

0.3 (p) 4.0 3.2

2.3 -3.0 4.3

2.3 0.5 4.1

2.3 1.5 4.4

Sources: Country authorities and World Bank and IMF staff estimates. Notes: 2017 estimates are not yet available for Kiribati. Nauru data are based on the year ended June; Kiribati and Tuvalu are calendar years.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Central Pacific Islands

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

CHINA

Population, million GDP, current US$ billion GDP per capita, current US$ International poverty rate ($1.9)a Lower middle-income poverty rate ($3.2)a Upper middle-income poverty rate ($5.5)a School enrolment, primary (% gross)b Life expectancy at birth, yearsb

the year end, resulting in a negative growth contribution from net exports. Investment growth decreased slightly owing to weaker state sector capital spending, while private investment rebounded. As the economy continued to rebalance, services grew by 7.6 percent in 2018, while industry expanded by 5.8 percent.

2018 1,388.7 12,989.4 9,353 0.7 7.0 27.2 100.9 76.3

Source: WDI, Macro Poverty Outlook, and official data. Notes: a. Most recent value (2015), 2011 PPPs. b. Most recent WDI value (2016).

GDP growth slowed to 6.6 percent yoy in 2018 from 6.8 percent in 2017. This moderation reflects China’s economic rebalancing, as well as tighter domestic credit and less favorable external conditions. Growth is projected to slow to 6.2 percent in 2019-20. Poverty will continue to decline, with the extreme poverty rate reaching 0.2 percent by 2020–21. In the context of heightened trade tensions, reforms to further improve the investment climate have become crucial.

Recent Developments GDP growth slowed to 6.4 percent yoy in the fourth quarter, bringing annual growth to 6.6 percent in 2018, down from 6.8 percent in 2017. Consumption remains the primary driver of economic activity, contributing 5.0 percentage points (pp) to growth. Robust domestic demand supported imports, while new US trade tariffs and a slowing global economy weighed on exports towards

98

Growth in real disposable income per capita moderated to 6.5 percent in 2018, from 7.3 percent in the previous year. Rural household incomes continue to rise faster than urban ones—6.6 percent versus 5.6 percent in 2018. Nevertheless, income growth in rural areas has not been sufficiently high to narrow the urban-rural gap in recent years. The ratio of rural-urban per capita income has remained stable since 2014. The Gini coefficient, a measure of overall income inequality, declined to 0.462 in 2015 and has since risen to 0.467 in 2017. The growth slowdown has so far been partly due to tighter domestic credit conditions. Growth in total credit to the non-financial sector grew by 11.2 percent in 2018, down from 13.7 percent growth in 2017. While bank loan growth remained stable, regulatory tightening reduced nonbank lending. Furthermore, the demand for credit may have fallen due to more uncertain economic prospects. Signs of weaker trade growth appeared in the fourth quarter of 2018. The US dollar value of goods exports and imports declined from 11.8 and 37.3 percent yoy in the first nine months of 2018 to an average of 4.4 and 4.8 percent yoy in October-December, respectively. Both China’s goods exports to the US and goods imports from the US slowed significantly. Heightened trade tensions and uncertainty also resulted in higher financial market volatility. After two quarters of net capital inflows, US$109 billion of net outflows were recorded in the second half of 2018. Foreign investors reduced sharply bond and stock purchases and lowered FDI somewhat. The Shanghai Composite Index lost 24.6 percent and the Renminbi depreciated by 5.4 percent against the US dollar in 2018. Financial markets reversed some of these losses in early 2019.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: China

MANAGING HEADWINDS

In response to weakening growth and a challenging external environment, the government introduced several targeted, but so far limited, stimulus measures. Peopleâ&#x20AC;&#x2122;s Bank of China gradually shifted towards a looser monetary policy stance. It reduced the reserves that banks are required to maintain at the central bank four times since 2018. Some of the new liquidity measures are targeted at supporting lending to small and medium enterprises (SMEs) and private firms. In addition to some monetary easing, the authorities provided some fiscal support. New tax incentives aimed to increase household spending, support SMEs and exporters, and boost business spending on research and development and new equipment. The issuance of local government bonds was accelerated in the third quarter to bolster infrastructure spending. The consolidated fiscal deficit reached 4.3 percent of GDP in 2018, compared with 3.7 percent in 2017. However, strong measures to reduce off-budget borrowing by local governments are likely to have tightened the overall stance of general government. For example, infrastructure investment, which is often financed off-budget, contracted in 2018.

Outlook Growth is forecast to moderate to 6.2 percent in 2019â&#x20AC;&#x201C;20, and further to 6.0 percent in 2021. Higher uncertainty and slower credit growth are expected to continue to weigh on investment. Although a further increase in US tariffs on imports from China has been delayed for now, a deceleration in global demand growth will negatively affect net exports. Poverty rates are expected to continue to decline. The international poverty line poverty rate is forecasted to fall from 0.3 percent of the population in 2018 to 0.2 in 2021. Thus, China is well on track to meet the national goal of eliminating extreme poverty by 2020. The poverty rate for people living on less than $5.5/day is projected to decline from 27.2 percent in 2015 to 11.5 percent by 2021.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: China

Risks and Challenges The risks to the outlook remain high. There is considerable uncertainty with respect to the outcome of the China-US trade negotiations. In addition, recent data have indicated that global growth, in particular in advanced countries, may be weaker than previously expected. To cushion the growth slowdown, in March 2019 China announced new reductions in the value added and social security tax rates and a higher limit to local government on-budget borrowing. If stronger fiscal stimulus becomes necessary, the government could increase spending on health care, education, and social protection. Improving public services and better targeting the poor and vulnerable would create jobs, boost household disposable incomes and consumption, and help address the challenges of unequal opportunities (e.g., disparities in the quality of education and health care across provinces and between rural and urban areas). However, the effectiveness of any tax incentives in raising investment will also depend on business confidence. To increase opportunities and lower costs, the authorities would need to deepen structural reforms. Building on the business climate reforms introduced in 2018, enforcing fair competition and financial discipline, and enhancing government to business services would lower costs and encourage more investments. Removing ambiguities in Chinaâ&#x20AC;&#x2122;s intellectual property (IP) policy and better enforcing IP rights would encourage firms to develop frontier technology in China or transfer such technology to China. A new foreign investment law is set to address some of these concerns, but its impact would depend on how the law is interpreted and implemented by government officials and the courts. China could also commit to further shorten the negative investment list and limit it to industries involving national security. Over the medium term, such policies would contribute to productivity-led, higher-quality growth.

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Figure 1. R eal GDP growth, contribution to real growth

Figure 2. Poverty estimates and projections

Percent, percentage points

Percent

8

30

7 25 6 5

20

4 15 3 2

10

1 5 0 -1

20 21 f

20 20 f

20 19

20 18

20 17

20 16

20 15

20 14

20 13

20 12

0 2015

2016

2017

JJPrivate consumption

JJGovernment consumption

JJGross capital formation

▬▬International poverty rate

JJNet exports

JJStatistical discrepancy

▬▬GDP

▬▬Upper middle-income poverty rate

Sources: National Bureau of Statistics; World Bank staff estimates.

CHINA Selected Indicators Real GDP growth, at constant market prices Private Consumption Government Consumption Gross Fixed Capital Investment Exports, Goods and Services Imports, Goods and Services Real GDP growth, at constant factor prices Agriculture Industry Services Inflation (Consumer Price Index) Current Account Balance (% of GDP) Net Foreign Direct Investment (% of GDP) Fiscal Balance (% of GDP)a Debt (% of GDP) Primary Balance (% of GDP) International poverty rate ($1.9 in 2011 PPP)b Lower middle-income poverty rate ($3.2 in 2011 PPP)b Upper middle-income poverty rate ($5.5 in 2011 PPP)b

2018

2019

2020

2021

▬▬Lower middle-income poverty rate

Sources: World Bank staff estimates using tabulated data from China NBS.

2016

2017

2018e

2019f

2020f

2021f

6.7 8.6 8.8 6.8 1.8 5.7 6.7 3.3 6.3 7.7 2.0 1.8 -0.4 -3.3 36.9 -2.3 0.6 5.9 24.7

6.8 6.4 9.5 5.2 8.9 6.6 6.8 4.0 5.9 7.9 1.6 1.4 0.5 -3.7 37.2 -2.5 0.4 4.6 21.5

6.6 8.6 8.5 5.1 4.2 6.4 6.6 3.5 5.8 7.6 2.1 0.4 0.8 -4.3 38.6 -3.1 0.3 3.6 18.7

6.2 8.0 8.2 5.0 3.5 5.8 6.2 3.3 5.5 7.3 2.1 -0.1 0.5 -4.3 40.0 -3.0 0.3 2.7 16.1

6.2 7.8 8.1 4.9 3.3 5.5 6.2 3.3 5.4 7.1 2.0 -0.3 0.5 -4.0 41.0 -2.6 0.2 2.0 13.6

6.0 7.6 7.9 4.8 3.3 5.5 6.0 3.3 5.2 7.0 2.0 -0.5 0.5 -3.7 41.7 -2.1 0.2 1.5 11.5

Source: World Bank, Poverty & Equity and Macroeconomics, Trade & Investment Global Practices. Notes: e = estimate, f = forecast. a) The adjusted fiscal balance adds up the public finance budget, the government fund budget, the state capital management fund budget and the social security fund budget. b) 2015 is actual based on group data provided by China NBS, 2016 onwards are projections using neutral distribution with pass through 0.72.

100

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: China

MANAGING HEADWINDS

FIJI

Population, million GDP, current US$ billion GDP per capita, current US$ Basic Needs Poverty Ratea International poverty rate ($1.9)a Lower middle-income poverty rate ($3.2)a School enrolment, primary (% gross)a Life expectancy at birth, yearsa

as the main source of livelihood for nearly half of Fijians, while its contribution to the economy is low at around 8 percent. Services is the largest sector, representing 70 percent of the economy and providing employment for nearly forty percent of Fijians. Tourism remains a critical industry with combined direct and indirect contribution to GDP estimated to be more than 30 percent.

2018 0.9 5.3 5,807 28.1 1.4 14.1 105.3 70.3

Sources: WDI, Macro Poverty Outlook, and official data. Notes: a. Fiji Bureau of Statistics. Based on income-based National Poverty Line in 2013–14. Most recent WDI value (2016).

Inflation slightly increased to 5.1 percent in January 2019 year to year, reflecting higher prices for fuel, alcohol and tobacco. The recent increase in inflation is largely attributed to supply side shocks, especially natural disasters. Fiji’s monetary policy has been accommodative and the RBF’s Overnight Policy Rate has remained unchanged at 0.5 percent since 2011. Domestic credit to the private sector tightened, growing 7.1 percent in 2018, due to a slowdown in lending to businesses. The Fijian dollar has remained broadly stable against a basket of currencies of its main trading partners. According to the Reserve Bank of Fiji (RBF), the REER increased by 4.2 percent in 2018 mainly due to higher domestic inflation relative to its trading partners.

Despite the negative impact by Tropical Cyclones Keni and Josie that hit Fiji in April 2018, Fiji’s economy proved resilient, growing 3.2 percent in 2018. GDP growth is projected to be 3.4 percent in 2019. Fiji’s fiscal policy was expansionary over the last few years. As Fiji’s external environment weakens and Fiji remains exposed to frequent and costly natural disasters, building fiscal space through expenditure-based fiscal consolidation remains the key policy priority. Reforms focusing on a more supportive environment for private sector development could help Fiji reach 4–5 percent growth, as envisaged in its National Development Plan (NDP).

The fiscal deficit in FY2017/18 is estimated at 4.5 percent of GDP due to a rollover of capital expenditure, increases in the wage bill and social welfare. The deficit in FY2016/17 was 2.2 percent of GDP, which was much lower than the 7.3 percent of GDP projected because of delays in reconstruction due to bad weather, supply shortages, and the difficulty of delivering materials to maritime and remote areas. Government debt slightly increased to 48 percent of GDP, owing to additional borrowing for post-Winston reconstruction. In the lead-up to COP23, the government issued a Green Bond denominated in local currency with support and guidance from the World Bank and IFC.

Recent Developments

The current account deficit widened to 6.2 percent of GDP in 2017 from 3.2 percent of GDP in 2016. The deficit reflected a large shortfall on the merchandise trade account as import demand for raw materials and capital equipment continued to be strong while reconstruction activities gathered pace. A large surplus in the services

Despite the negative impact by Tropical Cyclones Keni and Josie that hit Fiji in April 2018, GDP growth is estimated to be 3.2 percent in 2018, supported by consumption and public-sector investment. The agricultural sector remains

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Fiji

101

EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

account (relating to tourism and transport) and continued strength in remittances partially offset the deficit in the goods account. The FDI inflows were more than sufficient to finance the deficit in 2017, although the preliminary figures show that it declined in 2018 leading to a drawdown of reserves. Foreign reserves were at US$1.0 billion at endDecember 2018, which was sufficient to cover 4.5 months of retained imports.

rise to 50.4 percent of GDP in FY2019/20. The current account deficit is estimated to be at 5.9 percent of GDP in 2018 due to a decline in investment income outflows, an increase in remittances, and a larger trade deficit relative to 2017.

Using the international poverty line of US$1.90 (2011 PPP US$ per person per day), Fiji’s extreme poverty rate in 2013/2014 was estimated at 1.4 percent, which is one of the lowest in the Pacific. Inequality in Fiji is also among the lowest in the East Asia and Pacific, with the Gini index estimated at 36.7 in 2013/2014. However, using the US$5.50 Upper Middle-Income Class Poverty Line, which reflects living standards across all upper middle-income countries, the incidence of poverty was at 48.6 percent.

Potential upside risks include lower-than-expected import commodity prices and stronger-than-expected tourism. Downside risks include another natural disaster and a sharp slowdown in China, which could hit Fiji’s main export and tourism source markets such as Australia, New Zealand, and Japan. Risks on the domestic front include further delays to fiscal consolidation and slowing down of the reform agenda.

Outlook GDP growth is projected to be 3.4 percent in 2019. Inflation is expected to decline to 3.5 percent as supply disruptions ease. The government’s budget for FY2018/19 indicates a continuation of expansionary expenditure policy on the back of a sizeable jump in projected revenue. The increase on the revenue front is expected to be due to tightening compliance and broadening the tax base while maintaining low tax rates. There is also a 50 percent increase in dividends from profit making SOEs, such as Fiji Airports, Energy Fiji and Fiji Ports Corporation. The expenditure front shows an across the board increase in the budget. The government’s planned deficit is 3.5 percent of GDP, although this includes the budgeted receipts from the sale of government assets of about 3.4 percent. Over the medium term, the government is planning to reduce the deficit gradually to 3.0 percent in FY2019/20 and 2.5 percent of GDP in FY2020/21. This gradual decline is expected to be achieved through a combination of the normalization of capital spending, continued effort in revenue mobilization, and greater control of recurrent spending. The ratio of public debt to GDP is projected to

102

Risks and Challenges

Fiji is exposed to frequent natural disasters, causing an average loss of 2–5 percent of GDP. The disasters and rising expenditures have eroded Fiji’s fiscal space in the last five years. Therefore, it is important for the government to start rebuilding fiscal space to respond to future shocks. While continuing to pursue ambitious social and investment programs, the government’s focus has been greater revenue mobilization, robust management of public debt, greater accountability through internal audit, and more frequent and comprehensive public financial reporting. Going forward, expenditure measures, such as rationalizing capital expenditure while protecting essential public investment and not increasing current expenditure in real terms, are needed to achieve the government’s medium-term fiscal targets. The reform agenda includes building climate resilience and creating a more supportive environment for private-sector-led growth. Attracting more FDI and expanding the role of the private sector in the economy will require modernizing the legal and regulatory framework.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Fiji

MANAGING HEADWINDS

Figure 1. Real GDP growth and total investment

Figure 2. Fiscal balance and public debt

Percent

Percent

10

30

8

25

Percent of GDP

Percent of GDP 51

0

50 -1 49

6 20 -2

4

48

15 2

47

-3 10

46

0

21

19

20

17

13

11

15

20

20

20

20

09

20

07

03

05

20

20

20

20

20

19

19

19

▬▬GDP growth

01

0

99

-4

97

5

95

-2

▬▬Total investment, rhs

Source: World Development Indicators and IMF World Economic Outlook.

FIJI Selected Indicators Real GDP growth, at constant market prices Agriculture Industry Services Inflation (Consumer Price Index) Current Account Balance (% of GDP) Net Foreign Direct Investment (% of GDP) Fiscal Balance (% of GDP)

-4 45 44

-5 2015

2016

2017

2018

2019

2020

▬▬Public debt, rhs

JJFiscal balance

Sources: Ministry of Economy, and IMF and World Bank staff estimates.

2016

2017

2018e

2019f

2020f

2021f

0.7 -7.2 3.3 1.2 3.9 -3.2 8.7 -1.4

3.0 3.0 2.1 3.2 3.4 -6.2 7.7 -2.1

3.2 1.8 3.2 3.4 4.1 -5.9 4.1 -4.4

3.4 2.5 3.2 3.6 3.5 -5.0 5.2 -3.6

3.3 2.3 3.1 3.5 3.0 -4.3 4.5 -3.3

3.3 2.3 3.1 3.5 3.0 -3.7 5.4 -3.0

Source: World Bank, Poverty & Equity and Macroeconomics, Trade & Investment Global Practices. Notes: e = estimate, f = forecast.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Fiji

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

INDONESIA

Population, million GDP, current US$ billion GDP per capita, current US$ International poverty rate ($1.9)a Lower middle-income poverty rate ($3.2)a Upper middle-income poverty rate ($5.5)a Gini indexa School enrolment, primary (% gross)b Life expectancy at birth, yearsb

contraction in net exports (Figure 1). Lower consumer price inflation and robust labor market conditions continued to support private consumption. In contrast, investment growth eased, partly due to a maturing investment cycle, which has been driven by infrastructure projects, many of which are being concluded, and the mining sector, which faces declining prices. After little change in Q3, inventories saw a solid accumulation in Q4. Growth of government consumption slowed in part because of the frontloading of social spending to Q3.

2018 266.8 1,041.2 3903 5.7 27.3 58.9 37.9 103.5 69.2

In line with weaker global trade, both total exports and imports growth were halved in Q4, compared to Q3. Nonetheless, imports still grew nearly twice as fast as exports, leading to a drag on output growth, although this was significantly smaller than in Q3. On the production side, most sectors saw slower growth, except for agriculture and financial services sectors. Consequently, gross valueadded rose by 4.9 percent in Q4, slightly less than the 5.0 percent in Q3.

Recent Developments

With strengthening domestic private consumption and still-robust investment, coupled with weakening external conditions and poor export performance, the current account deficit widened to 3.0 percent of GDP in 2018 from 1.6 percent of GDP in 2017. Although Indonesia faced larger portfolio capital outflows in 2018 compared to the taper tantrum in 2013, renewed investor appetite for Indonesian assets since October led to a jump in portfolio inflows to US$ 10.4 billion in Q4, swelling the capital account. As a result, international reserves rebounded from the lows in September 2018, reaching USD 123.2 billion in January 2019 (September 2018: USD 114.8 billion). Because of renewed capital inflows, the Rupiah recovered from a trough of IDR 15,237 per USD on October 30 to around 14,000 to the greenback for the most part of this year.

Despite less favorable external conditions, the Indonesian economy grew at a steady pace of 5.2 percent yoy in Q4 2018. For 2018 as a whole, the economy expanded by 5.2 percent, up from 5.1 percent in 2017. Growth in Q4 was driven by an uptick in private consumption and a smaller

Despite inflation being near its two-year low in Q4, Bank Indonesia continued its tightening cycle through November. With the three-25 basis point hikes during the second half of the year, the cumulative increase in the policy rate was 175 basis points in 2018. The sustained

Sources: WDI, Macro Poverty Outlook, and official data. Notes: a. Most recent value (2017), 2011 PPPs. b. Most recent WDI value (2016).

After a challenging 10 months of financial volatility, sound economic fundamentals and a coordinated policy framework brought respite to Indonesia in Q4 with capital flows returning and the Rupiah rebounding. Economic growth also persisted at a robust pace, inflation remained low, labor market conditions strengthened, but the current account deficit continued to widen. The economic outlook continues to be positive on projected strong domestic demand. Global trade tensions and possible renewed global financial volatility pose substantial risks.

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PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Indonesia

MANAGING HEADWINDS

policy tightening was in response to external conditions and reflected the Government’s focus in maintaining external stability. Consistent with the Government’s focus on maintaining macro stability, Indonesia’s fiscal position strengthened in 2018. Revenues surged 18.7 percent in 2018, after growing by 12.3 percent in 2017 thanks to ongoing reforms, better compliance and improved commodity prices. Expenditures also grew, but less than revenues (10.3 percent; 2017: 7.9 percent). Consequently, the fiscal deficit shrank to 1.8 percent of GDP, the lowest in six years and smaller than the budgeted deficit of 2.2 percent of GDP. Strong labor markets supported household incomes and consumption. The economy added 3 million workers in the year to August 2018, and the employment rate reached a two-decade high of 63.7 percent. Meanwhile, the unemployment rate fell to a 20-year low of 5.3 percent. The share of formal jobs also reached its highest rate since 2000 at 43.2 percent. In line with low inflation rates, strong labor market conditions and recent expansions in social assistance programs, the poverty rate fell from 10.1 percent in September 2017 to 9.7 percent in September 2018. In absolute terms, the number of poor declined by 1.9 million. The poverty gap also fell from 1.8 percent in September 2017 to 1.6 percent in September 2018.

Outlook Real GDP growth is projected to be flat at 5.2 percent yoy in 2019, as domestic demand remains robust. Private consumption is forecast to strengthen slightly on continued low inflation, increased social spending and a robust labor market. Although investment is expected to decelerate from the fast pace recorded in 2018, it will remain robust, as firms that had remained on the sidelines due to the elections make new investments. Likewise, Government consumption is forecast to remain firm as continued

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Indonesia

reforms and revenue growth creates space for additional spending even as deficits remain contained. The extreme poverty rate declined by 0.8 percentage point from 2017 to 4.9 percent in 2018, lifting over 2 million people out of extreme poverty (Figure 2). Extreme poverty is expected to continue falling in the medium term, but the rate of the reduction will slow. More specifically, the extreme poverty rate is projected to fall to 4.2 percent in 2019, 3.6 percent in 2020 and 3.0 percent in 2021.

Risks and Challenges Downside risks to Indonesia’s growth outlook remain substantial. Global trade tensions appear to have subsided but could return if ongoing negotiations are not successful. The possible further escalation and broadening of trade disputes continues to pose significant risks to Indonesia through a weaker external sector and dampened commodity prices. At the same time, risks remain elevated due to possible renewed financial market volatility affecting emerging market economies, including Indonesia. Indonesia remained resilient amid the volatility in 2018, largely because of its sound macroeconomic fundamentals and adequate buffers that allowed for a coordinated monetary, fiscal and exchange rate policy framework. It is important for Indonesia to maintain its sound macroeconomic policies and seize the current opportunity to rebuild foreign reserves to maintain sizable buffers. Moreover, implementing structural reforms that boost exports and FDI will reduce the structural account deficit. At the same time, income inequality remains a key policy challenge. Although the Gini coefficient fell in 2018, the improvement was not uniform. Across the urban-rural split, inequality decreased substantially in urban areas, but remained almost the same in rural areas. This suggests that growth has not been equitably distributed, and that the poor and vulnerable are at risk of being left behind.

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Figure 1. Real GDP growth, contribution to real growth

Figure 2. Poverty rate, actual and projected

Percent, percentage points

Percent

8

100 90

6

80 70

4

60 2

50 40

0 30 20

-2

10

JJPrivate consumption

JJGovernment consumption

JJStatistical discrepancy* JJChange in inventories

JJInvestment

JJNet exports

▬▬GDP

Sources: National Statistics Agency (BPS); World Bank staff calculations.

INDONESIA Selected Indicators Real GDP growth, at constant market prices Private Consumption Government Consumption Gross Fixed Capital Investment Exports, Goods and Services Imports, Goods and Services Real GDP growth, at constant factor prices Agriculture Industry Services Inflation (Consumer Price Index) Current Account Balance (% of GDP) Net Foreign Direct Investment (% of GDP) Fiscal Balance (% of GDP) Debt (% of GDP) Primary Balance (% of GDP) International poverty rate ($1.9 in 2011 PPP)a,b Lower middle-income poverty rate ($3.2 in 2011 PPP)a,b Upper middle-income poverty rate ($5.5 in 2011 PPP)a,b

▬▬PPP US$1.90 poverty rate

20 20

18 20

16 20

14 20

12 20

10 20

08 20

06 20

04 20

02

0

20

c-1 8 De

18 Ju n-

c-1 7 De

17 Ju n-

c-1 6 De

16 Ju n-

De

c-1 5

-4

▬▬PPP US$3.20 poverty rate

▬▬PPP US$5.50 poverty rate Sources: National Statistics Agency (BPS); World Bank staff calculations.

2016

2017

2018e

2019f

2020f

2021f

5.0 5.0 -0.1 4.5 -1.7 -2.4 4.6 3.4 3.8 5.7 3.5 -1.8 1.7 -2.5 28.0 -1.0 6.5 31.1 62.8

5.1 5.0 2.1 6.2 8.9 8.1 4.8 3.9 4.1 5.7 3.8 -1.6 1.8 -2.5 29.4 -0.9 5.7 27.3 58.9

5.2 5.1 4.8 6.7 6.5 12.0 5.0 3.9 4.3 5.8 3.2 -3.0 1.3 -1.8 29.8 0.0 4.9 25.3 57.4

5.2 5.2 5.2 6.5 6.0 8.0 5.2 3.1 4.1 6.8 3.2 -3.0 1.7 -1.9 29.5 -0.2 4.2 23.5 56.0

5.3 5.2 5.4 6.7 6.4 8.2 5.3 3.7 4.4 6.5 3.2 -2.8 1.8 -2.0 29.2 -0.4 3.6 21.7 54.6

5.3 5.2 5.4 6.8 6.8 8.3 5.3 3.6 4.2 6.8 3.2 -2.5 1.8 -2.0 28.8 -0.4 3.0 20.0 53.1

Source: World Bank, Poverty & Equity and Macroeconomics, Trade & Investment Global Practices. Notes: e = estimate, f = forecast. a) Calculations based on EAPPOV harmonization, using 2011-SUSENAS, 2015-SUSENAS, and 2017-SUSENAS. Actual data: 2017. Nowcast: 2018. Forecast are from 2019 to 2021. b) Projection using annualized elasticity (2011–2015) with pass-through = 1 based on GDP per capita in constant LCU.

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PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Indonesia

MANAGING HEADWINDS

LAO PDR

Population, million GDP, current US$ billion GDP per capita, current US$ International poverty rate ($1.9)a Lower middle-income poverty rate ($3.2)a Upper middle-income poverty rate ($5.5)a Gini indexa School enrolment, primary (% gross)b Life expectancy at birth, yearsb

slowdown in agriculture production is expected to stall poverty reduction since the sector remains the key source of employment among the poor and the vulnerable people; (ii) the weak performance of the mining sector despite higher commodity prices; and (iii) continued fiscal consolidation through tightening of public investment. These downside factors offset the gains from the industry sector driven by the expansion of construction activities and electricity exports, coupled with robust growth in wholesale and retail trade.

2018 7.0 17.9 2,577 22.7 58.7 85.0 36.4 110.5 66.7

Source: WDI, Macro Poverty Outlook, and official data. Notes: a. Most recent value (2012), 2011 PPPs. b. Most recent WDI value (2016).

The Lao PDR economy continues to be characterized by robust growth despite recent moderation. Although growth is expected to be supported by strong infrastructure investment and export performance, the outlook is subject to downside risks associated with the heightened global economic and geopolitical uncertainty, continued fiscal consolidation, and limited buffers against adverse external shocks.

Recent Developments Although decelerating from 6.9 percent the previous year, economic growth in 2018 is estimated to remain robust at 6.5 percent. The slowdown has been due to a combination of the following factors: (i) the severe floods that hit the country during Julyâ&#x20AC;&#x201C;September 2018, which adversely affected agricultural production and damaged infrastructure in several provinces. The anticipated

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Lao PDR

Notwithstanding the impact of the floods, tighter control of spending contributed to narrowing the fiscal deficit to 4.7 percent of GDP in 2018. In 2018, the main factor was the rationalization of public spending through tighter control of the public wage bill and downward adjustment of non-wage current spending and postponement of some new public investment. These measures offset higher interest payments. Total revenue rose by 4 percent in nominal term in 2018 as the improvement in excise tax and non-tax revenues offset the decline of grants and other taxes. Meanwhile, fiscal consolidation is estimated to have slowed the accumulation of public debt in 2018, though not enough to reverse the rising debt-to-GDP ratio, which increased from 60.1 to 60.6 percent of GDP between 2017 and 2018. The current account deficit is estimated to have narrowed in 2018, with the support of higher net exports. Key drivers of export growth were: electricity, due to more generation; and minerals, due to relatively higher metal prices despite flat output; and the manufacturing of electronic parts for export. These helped compensate for the decline in agricultural exports due to the impact of floods, and lower agriculture commodity prices such as rubber. Additionally, import compression due to a moderation in the import of consumption goods despite higher oil imports, contributed to the current account deficit declining to 11 percent in 2018 from 12.1 percent in 2017. However, foreign direct investment (FDI) inflows and external borrowing remained inadequate to finance the entire current account deficit. This, together with repayments of debt obligations, contributed to a reduction in international reserves.

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Reserves were recorded at US$812 million in October 2018. At that level, the reserve buffer is expected to remain relatively thin covering 1.1 months of total imports in 2018 compared to 1.5 months in 2017.

account deficit is expected to be largely financed by the investment inflows on these projects. Post-2020, with winding down of these projects, growth is expected to slightly moderate.

Increased pressure on the local currency led to a 2 percent nominal depreciation of the kip against the U.S. dollar in 2018. This followed the regional trend of a general strengthening of the U.S. dollar against emerging market economies’ currencies and increased flexibility of the exchange rate within the band.

Further, the medium-term fiscal framework envisages a fiscal consolidation path that aims to stabilize and eventually put public debt on a more sustainable path. The budget deficit is expected to decline over the medium term to around 3 percent by 2021 following revenue improvement and expenditure rationalization. The reduction in the fiscal deficit coupled with the implementation of Public Debt Management Law and strategy is expected to reduce the public debt-to-GDP ratio during 2019–21.

The depreciation of the kip against the currencies of major trading partners, together with higher food and fuel prices contributed to higher inflation in 2018. Headline inflation rate has edged upward, similar to regional trends, to an estimated 2.0 percent in 2018, up from 0.8 percent the previous year. Notwithstanding the higher inflation rate, the policy interest rate remained unchanged in 2018 as credit growth continued to slow. Fiscal tightening is correlated with lower economic activity which in turn led to slower credit growth. The banking sector remains well capitalized, but the sector still faces relatively low profitability and a high percentage of nonperforming loans compared to some regional peers. Return on assets and equity has improved to 0.7 percent and 9.4 percent in Q3 2018 from 0.5 percent and 7.7 percent, respectively. However, these levels still remained below regional peers.

Outlook In the near term, growth is expected to remain robust. Growth in 2019–20 is expected to remain robust on the back of large hydropower projects expected to begin commercial operation during 2019–20 and continued infrastructure investment. The current account deficit is expected to remain elevated in the medium term driven by large imports by mega infrastructure projects such as the Lao PDR section of the railway, to support their investment and construction. Similar to historical trends, the current

108

Risks and Challenges The risks to the outlook continue to weigh on the downside. Domestically, notwithstanding the efforts undertaken by the government, the level of fiscal deficit and public debt remain elevated. The fiscal conditions could deteriorate further if there is limited progress on domestic revenue mobilization, increased expenditure on infrastructure projects, rise in debt service payments, and greater disaster relief spending owing to weather-related shocks. In addition, key downside risks to growth include a delay in the construction and operation of other pipeline power projects following the breakdown of the saddle dam of the Xe-Pian Xe-Namnoy project, which triggered tighter supervision to ensure safety. The flooding and saddle dam breach highlighted the vulnerability of households in Lao PDR to extreme weather events, putting an impetus on strengthening climate resilience in infrastructure projects. External risks include escalating and prolonged trade protectionism, heightened global and regional geopolitical uncertainty, and continued tightening of global financing conditions that could lead to disorderly financial market movements and adversely impact global demand and commodity prices.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Lao PDR

MANAGING HEADWINDS

Figure 1. Real GDP growth, contribution to real growth

Figure 2. Actual and projected poverty rates and real GDP per capita

Percent, percentage points

Poverty rate, percent

8

Real GDP per capita, LCU constant, millions

100

25

90

7

20

80 6 70 5

15

60

4

50

3

40

10

30 2 5

20 1

10

0

0

JJAgriculture

JJIndustry

JJNet taxes on production

▬▬GDP

JJServices

Source: National statistics office and World Bank staff estimates.

LAO PDR Selected Indicators Real GDP growth, at constant market prices Real GDP growth, at constant factor prices Agriculture Industry Services Inflation (Consumer Price Index) Current Account Balance (% of GDP) Fiscal Balance (% of GDP) Debt (% of GDP) Primary Balance (% of GDP) International poverty rate ($1.9 in 2011 PPP)a,b Lower middle-income poverty rate ($3.2 in 2011 PPP)a,b Upper middle-income poverty rate ($5.5 in 2011 PPP)a,b

▬▬International poverty rate

▬▬Lower middle-income poverty rate

▬▬Upper middle-income poverty rate

▬▬Real GDP per capita, rhs

20 20

18 20

16 20

14 20

12 20

10 20

08 20

06 20

04 20

02 20

20 20 f

20 19 f

20 18 e

20 17

20 16

20 15

20 14

20 13

0

Sources: National statistics office and World Bank staff estimates.

2016

2017

2018e

2019f

2020f

2021f

7.0 7.0 2.8 12.0 4.7 1.6 -12.4 -4.7 58.5 -3.5 20.0 54.0 82.3

6.9 6.8 2.9 11.6 4.4 0.8 -12.1 -5.3 60.1 -3.9 19.4 53.0 81.7

6.5 6.5 2.1 9.6 5.5 2.0 -11.0 -4.6 60.6 -2.9 18.9 52.2 81.2

6.6 6.6 2.7 8.8 6.1 2.1 -12.1 -4.3 60.3 -2.4 18.4 51.3 80.6

6.7 6.7 2.8 8.8 6.1 2.5 -11.8 -3.6 59.5 -1.8 17.9 50.4 80.1

6.6 6.6 3.2 8.1 6.3 2.3 -11.1 -3.0 58.3 -1.3 17.4 49.5 79.5

Source: World Bank, Poverty & Equity and Macroeconomics, Trade & Investment Global Practices. Notes: e = estimate, f = forecast. a) Calculations based on EAPPOV harmonization, using 2007-LECS and 2012-LECS. Actual data: 2012. Nowcast: 2013–2018. Forecast are from 2019 to 2021. b) Projection using annualized elasticity (2007–2012) with pass-through = 1 based on GDP per capita in constant LCU.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Lao PDR

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

MALAYSIA

Population, million GDP, current US$ billion GDP per capita, current US$ International poverty rate ($1.9)a Lower middle-income poverty rate ($3.2)a Upper middle-income poverty rate ($5.5)a Gini indexa School enrolment, primary (% gross)b Life expectancy at birth, yearsb

June and August. Special payments to civil servants and pensioners lent additional support to private consumption. Private investment in the second half of 2018 was supported by capital spending in manufacturing and services, although the momentum slowed towards the end of the year.

2018 32.0 353.9 11,046 0.0 0.2 2.7 41.0 103.5 75.3

Source: WDI, Macro Poverty Outlook, and official data. Notes: a. Most recent value (2015), 2011 PPPs. b. Most recent WDI value (2016).

Malaysiaâ&#x20AC;&#x2122;s economic growth expanded at 4.4 and 4.7 percent in the last two quarters of 2018. Overall, growth moderated to 4.7 percent in 2018. While private consumption remained resilient, weaker export growth and lower public sector investment weighed down growth. The economy is forecast to grow by 4.7 percent in 2019, with risks emanating from uncertainty in the external environment and increased fiscal reliance on oil-related proceeds. Monetary poverty is low and is projected to decline further.

Recent Developments In the second half of 2018, Malaysiaâ&#x20AC;&#x2122;s GDP growth remained at a moderate pace, expanding by 4.4 and 4.7 percent in the third and fourth quarters, respectively. Growth continued to be anchored by private consumption, supported by households frontloading their purchases during the consumption tax holiday period between

110

Growth, however, continued to be weighed down by lower public investment expenditure. Public sector investment contracted by 5.5 and 4.9 percent in the third and fourth quarters, respectively, as capital outlays by public corporations declined, with several infrastructure projects nearing completion and the deferment and cancellation of several major infrastructure projects. Meanwhile, public consumption expanded at a slower pace. On the external front, export growth moderated in the second half of 2018 due to slower growth of manufacturing exports (except for semiconductor products), and a continued decline in agriculture exports. This contributed to a moderation in the current account surplus to 2.0 percent of GDP during the period. Financial markets experienced some volatility during the period, as investor sentiment was affected mainly by expectations for a faster pace of monetary policy normalization in advanced economies, as well as uncertainty over global growth and trade, leading to portfolio outflows. Nevertheless, these outflows were mitigated by resident inflows. In Q4 2018, the ringgit appreciated marginally by 0.05 percent against the US dollar, while the equity market declined by 5.7 percent. Labor market conditions remained stable throughout the second half of 2018. The labor force participation rate was marginally higher at 68.5 percent in Q4 2018, while the unemployment rate remained low at 3.3 percent. Manufacturing wages grew strongly at 9.8 percent in Q4 2018, significantly outpacing wage growth in the services sector. Headline inflation continued to moderate to 0.4 percent in the second half of 2018, mainly due to the zerorization of the Goods and Services Tax (GST) and the shift to the Sales and Services Tax (SST), which is levied on a smaller share of consumption items compared to the GST. In addition,

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Malaysia

MANAGING HEADWINDS

the decline in inflation was partly attributable to the fixing of domestic fuel prices at levels lower than those in the same period in 2017. Core inflation, excluding the impact of consumption tax policy changes, remained broadly stable at 1.5 percent during the period. The government raised its fiscal deficit target for 2018 from 2.8 percent of GDP to 3.7 percent. The pace of fiscal consolidation deviated from past expectations. Operating expenditure was higher in 2018 following larger subsidy outlays, pension payments and debt service payments for the year. Meanwhile, the shortfall in revenue following the removal of the GST was partially offset by higher petroleum-related proceeds.

Outlook Malaysia’s GDP is expected to grow at a moderate rate of 4.7 percent in 2019. Private consumption will continue to be the main driver of growth, albeit expanding at a more measured pace. Household spending will be buoyed by stable labor market conditions and income support measures such as the Cost of Living Aid (Bantuan Sara Hidup). Gross fixed capital formation is expected to increase slightly, driven by the private sector, while public investment is expected to remain subdued in the near term. The external sector may be negatively affected by heightened uncertainty surrounding the global environment, particularly the possible escalation of USChina trade tensions. The fiscal deficit is expected to narrow to 3.4 percent of GDP in 2019 and subsequently to 3.0 percent in 2020. Near-term fiscal consolidation efforts are expected to be achieved primarily through rigorous expenditure rationalization, with broad-based declines (in percentage of GDP) projected across major components of operating and economic development outlays. Monetary poverty is expected to continue its downward trend in 2019, with a projected decline to 1.4 percent based on the upper middle-income countries (UMIC)

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Malaysia

poverty line of USD5.5 (2011 PPP) per person per day. Several initiatives for low-income households, including the national B40 Health Protection Fund, a B40 insurance scheme and affordable housing initiatives are in the pipeline to improve both monetary and non-monetary wellbeing. Malaysia’s economy is projected to expand at 4.6 percent in 2020, and the country is expected to achieve highincome country status by 2024.

Risks and Challenges Risks to growth are increasingly weighed to the downside. On the external front, given Malaysia’s high degree of trade and financial integration, ongoing uncertainties surrounding the US-China trade tensions and shifts in global financial market sentiment pose downside risks to Malaysia’s economy in the near term. On the domestic front, the relatively high levels of government liabilities and increased dependency on oil-related proceeds could potentially constrain the flexibility of fiscal adjustment against future macroeconomic shocks. In the private sector, the relatively high level of household debt remains a source of macro-financial stability risk and acts as a constraint on household spending. The principal challenge to more rapid and inclusive economic growth lies in increasing labor productivity, which in turn depends on stronger human capital development. Malaysia’s score on the Human Capital Index (HCI) is 0.62, which is about as expected compared to other UMICs but well below that of its aspirational comparators. Malaysia performs well on the child survival and years of schooling components of the HCI but does poorly relative to its economic peers in child nutrition and the quality of education. Key priorities are thus enhancing learning outcomes, reducing child undernutrition and strengthening social protection systems to enable households to both invest in and protect human capital.

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Figure 1. Real GDP growth, contribution to real growth

Figure 2. Actual and projected poverty rates and real private consumption per capita

Percent, percentage point contribution

Percent

10

Constant LCU, thousands

18

30

16

8

25 14

6 20

12 4

10 15

2

8

0

6

10

4

-2

5 2 0

20 20

18 20

16 20

14 20

12 20

10 20

08

0

20

Q4 -2 01 3 Q2 -2 01 4 Q4 -2 01 4 Q2 -2 01 5 Q4 -2 01 5 Q2 -2 01 6 Q4 -2 01 6 Q2 -2 01 7 Q4 -2 01 7 Q2 -2 01 8 Q4 -2 01 8

-4

JJPrivate consumption

JJFixed investment

JJGovernment consumption

▬▬International poverty rate

▬▬Lower middle-income poverty rate

JJNet exports

JJChange in inventory

▬▬Real GDP growth

▬▬Upper middle-income poverty rate

▬▬Real private consumption per capita, rhs

Sources: Department of Statistics Malaysia and World Bank staff calculations.

MALAYSIA Selected Indicators Real GDP growth, at constant market prices Private Consumption Government Consumption Gross Fixed Capital Investment Exports, Goods and Services Imports, Goods and Services Real GDP growth, at constant factor prices Agriculture Industry Services Inflation (Consumer Price Index) Current Account Balance (% of GDP) Net Foreign Direct Investment (% of GDP) Fiscal Balance (% of GDP) Debt (% of GDP) Primary Balance (% of GDP) International poverty rate ($1.9 in 2011 PPP)a,b Lower middle-income poverty rate ($3.2 in 2011 PPP)a,b Upper middle-income poverty rate ($5.5 in 2011 PPP)a,b

Sources: Department of Statistics Malaysia and World Bank staff Calculations.

2016

2017

2018e

2019f

2020f

2021f

4.2 6.0 0.9 2.7 1.3 1.3 4.2 -5.2 4.3 5.7 2.1 2.4 1.1 -3.1 52.7 -1.0 0.0 0.2 2.3

5.9 7.0 5.4 6.2 9.4 10.9 5.8 7.2 4.8 6.4 3.8 3.0 1.2 -3.0 50.7 -0.9 0.0 0.2 1.9

4.7 8.1 3.3 1.4 1.5 0.1 5.0 -0.4 3.5 6.9 1.0 2.3 0.8 -3.7 51.8 -1.5 0.0 0.1 1.6

4.7 6.5 1.6 2.5 2.2 1.9 4.7 1.6 3.6 5.9 1.5 1.9 0.7 -3.4 51.5 -1.3 0.0 0.1 1.4

4.6 6.2 1.7 3.2 2.2 2.1 4.6 1.8 3.9 5.5 2.1 1.6 0.5 -3.0 51.4 -0.9 0.0 0.1 1.2

4.6 6.0 1.8 3.8 2.1 2.2 4.6 2.1 4.1 5.3 2.2 1.4 0.3 -2.7 51.0 -0.6 0.0 0.1 1.0

Source: World Bank, Poverty & Equity and Macroeconomics, Trade & Investment Global Practices. Notes: e = estimate, f = forecast. a) Calculations based on EAPPOV harmonization, using 2011-HIS and 2015-HIS. Actual data: 2015. Nowcast: 2016–2018. Forecast are from 2019 to 2021. b) Projection using point-topoint elasticity (2011–2015) with pass-through = 1 based on private consumption per capita in constant LCU.

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PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Malaysia

MANAGING HEADWINDS

MONGOLIA

Population, million GDP, current US$ billion GDP per capita, current US$ National Official Poverty Ratea Gini indexa School enrolment, primary (% gross)b Life expectancy at birth, yearsc

2018 3.2 12.1 3,762.1 29.6 32.0 104.5 69.3

Source: National Statistical Office of Mongolia (NSO), World Bank, WDI, and Macro Poverty Outlook. Notes: a. Most recent value (2016). b. Most recent WDI value (2017). c. Most recent WDI value (2016).

Mongolia’s economic performance exceeded expectations in 2018 as real GDP grew by 6.9 percent supported by robust mineral exports, and strong foreign direct investment. Growth outlook remains positive in 2019 and beyond, mainly driven by private consumption, and investment in mining and manufacturing. Given the positive economic outlook, poverty is expected to decline. Risks to the outlook include political uncertainty, commodity price shocks, cross-border logistical bottlenecks, and slower implementation of banking sector reforms and money laundering concerns.

Recent Developments The strong growth momentum continued in 2018, as real GDP rose to 6.9 percent from 5.4 percent in 2017 and 1.4 percent in 2016. This robust economic recovery was largely supported by a strong coal sector (in both of price and volume), improved private investment, and improved market sentiments following implementation

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Mongolia

of government’s Economic Recovery Program (ERP). Private consumption recovered strongly in 2018 following contraction in the previous two years, largely on back of positive developments in the labor market (e.g., decline in the unemployment rate). Meanwhile, inflation accelerated to 8.1 percent in 2018 (close to the central bank target of 8 percent), driven by rising food and oil prices and strong domestic demand. A loose monetary stance also led to high credit growth, which fueled inflation. Bank credit (corporate and consumer loans) accelerated sharply (26.5 percent) in 2018 from around 10 percent in 2017. Nevertheless, the average real household income grew by 8.8 percent in 2018. Consequently, poverty rate is likely to have leveled down in 2018. The fiscal stance improved significantly in 2018, supported by steady implementation of fiscal consolidation reforms, improved economic performance and budget spending discipline. The under-execution in capital spending also played a role. Overall fiscal balance turned around from a record high deficit of 17.3 percent of GDP in 2016 to a surplus of 2.6 percent in 2018—the first budget surplus of the last 8 years. Substantial improvements in the fiscal balance led to a reduction in government debt in 2018. Moreover, the government successfully honored instalment payments due on its sovereign debts in 2018. However, external sector pressures intensified, driven by a rapid growth in imports (goods and services) and bank credit. As a result, the current account deficit surged from 10.5 percent of GDP in 2017 to 16.3 percent. High imports growth continued in 2018, mainly supported by a surge in investment. Strong FDI inflow in 2018 was not enough to offset the substantial worsening of the current account balance, resulting in a slight deterioration in the balance of payments (BoP). However, gross international reserves rose substantially in 2018 to US$3.5 billion (4.7 months of imports), mainly explained by a bond issuance (US$500 million) by Development Bank of Mongolia in October 2018. Meanwhile, a tugrug did not depreciate by much in 2018 (about 9 percent against the US$ and 3.4 percent against the Chinese RMB) compared to peers among commodity dependent economies in the region.

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With Mongolia’s inflation higher compared to trading partners’ (China and Russia), the appreciation of the real effective exchange rate by 5 percent in 2018 may have affected the export competitiveness of the non-mining sector.

likely ease as the disbursement of donors’ support and further FDI inflows materialize. Gross international reserves are expected to continue to improve to 5.2 months of imports in 2019 from 4.7 months in 2018. In this context, BoM should encourage greater flexibility of the exchange rate through limited interventions.

Outlook

The robust medium-term macro outlook is expected to contribute to poverty reduction.

Supported by a strong domestic demand, sustained FDI flows, and relatively robust commodity exports, economic growth is projected to further improve to 7.2 percent in 2019 from 6.9 percent in 2018, and to stabilize around 6.7 percent in 2020–21. Private investment supported by FDI and domestic credit will remain a key driver for growth in the medium-term, especially in mining, manufacturing, and transport services. Inflation is likely to remain elevated in 2019 mainly due to strong domestic demand, before declining gradually in 2020–21, below the central bank medium term target of 8 percent. Private consumption is also projected to further improve over the medium-term following improvement in labor market conditions, despite efforts by the central bank to cool off the strong economy. The base case assumes that the Bank of Mongolia (BoM) is likely to gradually tighten monetary policy to contain inflation amid rising imports and banking sector credit. In addition, BoM should monitor effective implementation of the bank recapitalization process. Agriculture sector growth is projected to exceed 4 percent in the medium term. Meanwhile, industry would grow by about 7.3 percent in 2019-21, as substantial developments are expected in mining. Services sector growth would continue to be supported through strong linkages between mining and transport. The base case also suggests that fiscal deficit would average about 1 percent of GDP in 2019–21 from a surplus of 2.6 percent in 2018. Meanwhile, this deficit will be consistent with a debt level lower than what is planned in the ERP. Investment related imports are expected to decelerate in 2020–21, thereby reducing current account balance pressures. Foreign exchange market pressures will

114

Risks and Challenges There are substantial risks to the outlook. These risks include political uncertainty exacerbated by the 2020 elections; effects of an escalating trade war between China and USA on global commodity markets; climate shocks (drought/ flooding, harsh winter); revived bottlenecks at the China border; and slow implementation of the recapitalization in the banking sector and anti-money laundering issues. Growing political uncertainty could induce a sudden relaxation of the government’s commitment to full implementation of its adjustment program, thereby affecting market sentiments and FDI flows. However, a strong commitment of policymakers to key policy reforms could mitigate this risk. Mongolia’s growth prospects could be adversely affected by an escalating trade war on global demand and its impact on the price of key exporting commodities (including copper). Weather related shocks and resumption of non-trade barriers at the border with China will likely affect Mongolia’s coal exports. Inability to recapitalize the banking sector adequately could create instability and delay the disbursement of official support. Mongolia’s limited progress on addressing money laundering issues is an additional risk, given its potential effect on FDI, and the financial sector. An emerging upside risk to the outlook is the recent decision by China to limit coal imports from Australia.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Mongolia

MANAGING HEADWINDS

Figure 1. Real GDP growth, contribution to real growth

Figure 2. Poverty rate (official poverty line): 2010–16

Percent, percentage points

Percent of total population

40

50 45

30

40 20

35 30

10

25 0 20 -10

15

-20

10 5

JJFinal consumption

JJGross capital formation

JJNet exports

Q3 -2 01 8

Q1 -2 01 8

Q3 -2 01 7

Q1 -2 01 7

Q3 -2 01 6

Q1 -2 01 6

Q3 -2 01 5

Q1 -2 01 5

Q3 -2 01 4

Q1 -2 01 4

-30

▬▬GDP

Source: National Statistics Office.

MONGOLIA Selected Indicators Real GDP growth, at constant market prices Private Consumption Government Consumption Gross Fixed Capital Investment Exports, Goods and Services Imports, Goods and Services Real GDP growth, at constant factor prices Agriculture Industry Services Inflation (Private Consumption Deflator) Current Account Balance (% of GDP) Net Foreign Direct Investment (% of GDP) Fiscal Balance (% of GDP) Debt (% of GDP) Primary Balance (% of GDP)

0 2010

JJNational average

2011

2012

JJUrban

2014

2016

JJRural

Source: National Statistics Office.

2016

2017

2018e

2019f

2020f

2021f

1.4 -2.6 10.7 0.5 13.8 12.7 1.5 6.2 -0.4 1.8 0.9 -6.3 1.2 -17.3 86.5 -13.5

5.4 -0.3 0.1 35.8 13.6 24.8 5.4 1.8 0.4 11.5 6.4 -10.5 11.6 -1.9 84.2 2.3

6.9 3.9 0.5 20.5 15.3 21.4 6.9 4.5 6.2 8.2 8.1 -16.3 15.8 2.6 71.5 6.1

7.2 6.2 6.0 33.5 1.2 8.3 7.2 4.0 5.9 9.3 8.3 -16.5 16.8 -1.5 65.9 0.9

6.9 6.8 4.7 15.0 1.0 3.7 6.9 4.5 7.2 7.3 8.1 -13.1 13.0 -1.4 59.8 0.4

6.5 7.6 5.8 9.3 7.6 8.2 6.5 4.7 8.8 5.1 7.2 -10.0 12.0 -0.1 56.6 1.5

Source: World Bank, Poverty & Equity and Macroeconomics, Trade & Investment Global Practices. Notes: e = estimate; f = forecast.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Mongolia

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

MYANMAR

Population, million GDP, current US$ billion GDP per capita, current US$ International poverty rate ($1.9)a Lower middle-income poverty rate ($3.2)a Upper middle-income poverty rate ($5.5)a School enrolment, primary (% gross)b Life expectancy at birth, yearsb

2018 53.9 66.6 1,237 6.2 29.5 67.2 109.5 66.6

the first half of 2018/19, notably in the manufacturing sector, with the headline Purchasing Manager Index (PMI) declining to a two year low of 48 (denoting contraction) in October 2018. Within services, transport services were particularly impacted by an increase in domestic fuel prices from July to December 2018. Agricultural output is projected to remain stable in 2018/19 despite severe floods in mid-2018. Paddy production in 2018/19 is forecast to increase modestly along with rice prices, which could potentially benefit poor farming households. The trade deficit is expected to narrow in 2018/19 with acceleration in exports, particularly garments, and deceleration of imports, particularly capital goods imports consistent with the estimated slowdown in private investment in the first half of 2018/19. There are signs that growth momentum has picked up since December 2018, with the PMI improving to 52.5 in December 2018 (denoting expansion) with production likely supported by easing cost pressures.

Recent Developments

After significant volatility in the first half of 2018/19, inflation has moderated and the Kyat/USD exchange rate has stabilized. The Kyat depreciated by 20 percent against the USD between April and November 2018, becoming the worst performing currency in the region. Depreciation, along with higher crude oil prices, drove higher domestic fuel prices feeding into inflation, which rose to a two year high of 8.8 percent in October 2018. Inflation has since moderated to 6.8 percent in January (YoY) supported by a reduction in global crude oil prices feeding into lower domestic fuel prices. Depreciation pressure has also eased since December, allowing the central bank to gradually replenish foreign exchange reserves. While recent external developments support stability, pressure on prices and exchange rates is likely to remain a concern in the medium term.

Growth is projected to slow to 6.2 percent in 2018/19 down from 6.8 percent in 2017/18. Weaker industrial performance and a slowdown in transport related services and tourism related activities are the likely drivers of the slowdown in growth momentum. Exchange rate volatility and cost pressures impacted industrial performance in

Economic reform momentum has increased in the last quarter of 2018/19, motivated to attract foreign investments and boost growth prospects. The Government of Myanmar has accelerated structural reforms in recent months, particularly in the financial sector. The Central Bank of Myanmar (CBM) has allowed foreign banks to

Source: WDI, Macro Poverty Outlook, and official data. Notes: a. Most recent value (2015), 2011 PPPs. b. Most recent WDI value (2016).

Growth is projected to slow to 6.2 percent in 2018/19 from 6.8 percent in 2017/18 with weaker industrial performance linked to exchange rate volatility and rising cost pressures. Growth is expected to pick up in the medium term to 6.5 percent in 2019/20 supported by public investment leading up to elections in 2020, and private investment supported by significant reform announcements and macro stability. Risks remain elevated from the spillovers of the Rakhine crisis, political instability and spillovers from global deterioration in trade environment.

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PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Myanmar

MANAGING HEADWINDS

lend directly to local businesses, which is expected to provide greater access to finance and deepen the local foreign exchange market. In January, the government also liberalized the insurance sector, opening it to foreign ownership. Additionally, the Central Bank in January permitted commercial banks to raise the regulated lending rate from 13 percent to 16 percent on uncollateralized lending, which allows more credit options for lenders and borrowers. Notable reforms in other sectors include the launch of the Myanmar Project Bank, the first prioritized public investment program for Myanmar; condominium ownership and the creation of a Customs National Single Window System.

Outlook Myanmarâ&#x20AC;&#x2122;s growth prospects are projected to improve in the medium term. Growth is projected to increase to 6.5 percent in 2019/20 driven by recent structural reforms which could attract further domestic and foreign direct investments and an expansionary fiscal stance leading up to elections in 2020, providing a boost to public investments. The positive trend in reducing poverty is expected to continue. Rapid growth led to a one-third decline in poverty rate between 2005 and 2015 (from 48 to 32 percent), based on the national poverty line. Strong growth is expected to have further decreased poverty in recent years, although limited agricultural growth suggests that poor agricultural households continue to see slower progress. The expected pick-up in manufacturing and construction, if sustained, could further accelerate poverty declines in urban areas, through low-skill employment opportunities for members of poor households. Declining inflation would also support poverty reduction.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Myanmar

Risks and Challenges Domestic risks are tilted to the downside. The crisis in Rakhine state remains a macro concern. The negative spillovers from the violence and forced displacement of most of the Muslim minority has been compounded by recent flare up in violence involving the Arakan Army. The indirect economic impacts of the crisis may intensify, with further slowdown in tourism revenues, which still account for 2.7 percent of GDP in direct revenues in addition to significant indirect economic benefits. Exports face a downside risk from the possible revocation of benefits under the Generalized System of Preferences (GSP) by the European Union (EU). This may particularly impact garment exports, which accounted for a quarter of overall export growth in Myanmar last year. An unexpected tightening of global financial conditions or deterioration in the global trade environment could put renewed pressure on exchange rate and prices. Global and regional growth, and trade flows, are at risk of slowing further amidst continued policy uncertainty and geopolitical tensions. Regional currencies, including the kyat, may come under further pressure triggered by fasterthan-expected monetary policy normalization in advanced economies.

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Figure 1. Real GDP growth, contribution to real growth

Figure 2. Actual and projected poverty rates and real GDP per capita

Percent, percentage point

Percent

Constant LCU, hundred-thousands

9

80

16

8

70

14

60

12

50

10

40

8

30

6

20

4

10

2

7 6 5 4 3 2 1

0

0

JJAgriculture

JJIndustry

JJServices

20 21 f

20 20 f

20 19 f

20 18 e

20 17

20 16

20 15

20 14

20 13

0

▬▬Real GDP growth

Sources: Ministry of Planning and Finance, and World Bank staff estimates.

MYANMAR Selected Indicators Real GDP growth, at constant market prices Real GDP growth, at constant factor prices Agriculture Industry Services Inflation (Consumer Price Index) Current Account Balance (% of GDP) Fiscal Balance (% of GDP) Primary Balance (% of GDP) International poverty rate ($1.9 in 2011 PPP)a,b Lower middle-income poverty rate ($3.2 in 2011 PPP)a,b Upper middle-income poverty rate ($5.5 in 2011 PPP)a,b

2015

2016

2017

2018

2019

2020

▬▬International poverty rate

▬▬Lower middle-income poverty rate

▬▬Upper middle-income poverty rate

▬▬Real GDP per capita, rhs

2021

Sources: Central Statistical Organization and Wakhema exchange rate centre.

2016

2017

2018e

2019f

2020f

2021f

5.9 5.9 -0.5 8.9 8.2 7.0 -2.8 -2.5 -1.1 5.9 28.7 66.4

6.8 6.8 1.3 9.4 8.4 5.4 -5.8 -3.1 -1.3 5.7 27.6 65.1

6.2 6.2 1.2 8.2 7.6 6.5 -2.0 -4.0 -2.0 5.3 26.8 64.1

6.5 6.5 2.0 8.0 8.0 7.0 -2.5 -4.3 -2.5 5.1 25.5 63.1

6.6 6.6 2.4 7.5 8.2 6.0 -3.0 -4.5 -2.8 4.8 24.4 62.0

6.8 6.8 2.4 8.0 8.2 6.0 -3.5 -4.5 -2.6 4.5 23.4 60.9

Source: World Bank, Poverty & Equity and Macroeconomics, Trade & Investment Global Practices. Notes: e = estimate, f = forecast. a) Calculations based on EAPPOV harmonization, using 2015-MPLCS. Actual data: 2015. Nowcast: 2016–2018. Forecast are from 2019 to 2021. b) Projection using neutral distribution (2015) with pass-through = 0.3 based on GDP per capita in constant LCU.

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MANAGING HEADWINDS

NORTH PACIFIC ISLANDS

2017 Population, million Federated States of Micronesia Republic of the Marshall Islands Palau GDP, US$ billion Federated States of Micronesia Republic of the Marshall Islands Palau GDP per capita, current US$ Federated States of Micronesia Republic of the Marshall Islands Palau

0.10 0.05 0.02 0.36 0.21 0.29 3,535 3,821 16,147

Sources: WDI, World Bank staff estimates.

Growth in the Federated States of Micronesia and Republic of the Marshall Islands is projected to have remained firm in FY2018 supported by donor-funded construction, while a recovery in the tourism sector is expected to have driven a rebound in growth in Palau. While high fishing revenues have bolstered fiscal balances, substantial fiscal risks remain, including due to the scheduled expiry of Compact Sector Grants (grants from the U.S. Government for the infrastructure, health and education sectors) in 2023.

Recent Developments The economy of the Federated States of Micronesia (FSM) is expected to have grown by 1.4 percent in FY2018, a fourth consecutive year of positive growth, and the longest period of sustained economic expansion

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: North Pacific Islands

since 2003. Nevertheless, output is only slightly higher than it was in 2003, highlighting the economy’s uneven performance over the past 15 years. Growth in FY2018 was likely driven by higher production in the fisheries sector and increased construction activity related to infrastructure projects. The sluggish growth performance over recent years has weighed on formal sector employment, which— according to the latest available data (2017)—was around 15,600 employees; 3 percent below its FY2011 level. This is likely to have exacerbated basic needs poverty in turn, since consumption welfare tends to be lower for those who are economically inactive or engaged in informal activities. The latest estimates indicate that 41.2 percent of the population were unable to afford the cost of basic needs in 2013/14. Consumer prices were flat in FY2017 and are expected to have been low in FY2018, due to lower domestic fuel prices and a stronger US dollar (the official currency of the FSM) holding down prices for some imports. After traditionally registering large deficits, the current account is projected to have registered its fourth consecutive surplus in FY2018, reflecting higher fishing licence receipts and grant inflows related to the Compact of Free Association with the United States. FSM’s fiscal performance has improved significantly in recent years, resulting in large fiscal surpluses of 7–15 percent of GDP during FY2014–FY2017. While general tax revenue (excluding irregular captive insurance industry payments) has remained steady at around 12 percent of GDP, which is low relative to other countries in the Pacific, non-tax revenue (excluding grants) have more than doubled as a percent of GDP since 2011 to over 24 percent of GDP, reflecting higher fishing license fees resulting from the introduction of the Vessel Day Scheme (a regional agreement that establishes the minimum price of a vessel day and limits the total number of vessel days sold). Another sizeable fiscal surplus was projected for FY2018. The government has prudently transferred fiscal surpluses to the FSM Trust Fund aimed at mitigating external shocks and potential future revenue shortfalls from the scheduled end of Compact grants from 2024. Nevertheless, further transfers of fiscal surpluses will be needed to build adequate fiscal buffers, as the combined

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

corpus of the nation’s two trust funds (the Compact Trust Fund and the FSM Trust Fund) are projected to be less than sufficient to deliver an annual investment income that can fully replace the expiring grants. The central government retains cash reserves of around USD 64 million (5 months of general government current spending). With no central bank or foreign exchange reserves, these serve as a means to absorb short-term liquidity shocks. Economic growth in the Republic of Marshall Islands (RMI) is expected to have remained firm in FY2018 at 2.5 percent, driven by continued strong fisheries activity and public infrastructure investment, following strong growth of 4.5 percent in FY2017. The current account has remained in surplus in recent years, with foreign grants and higher fishing license receipts more than offsetting a fall in exports and an increase in service imports. Consumer price were flat in FY2017 and are expected to have remained low in FY2018, following falls in FY2016 and FY2015, when the stronger US dollar (the official currency of the RMI) put downward pressure on food and transport prices. The combination of stronger economic growth (assuming it is equitable across the income distribution), public infrastructure investment, and low food price inflation are likely to have accelerated poverty reduction, though the extent of this is not known due to lack of data on household incomes and expenditures in the RMI. High fishing license fees underpinned small fiscal surplus over the four years FY2014 to FY2017, a trend which is expected to have continued in FY2018. However, larger fiscal surpluses will be required to build adequate buffers to sustain government spending following the scheduled end of Compact grants from 2024, as current projections indicate that the corpus of the RMI Trust Fund will not be sufficiently large to generate an annual income stream that can fully replace the expiring grants. In addition, government cash reserves are expected to have remained low (the most recent data indicate that reserves were around USD 13.6 million at the end of 2017, equivalent to around 1 month of recurrent spending), although the

120

steady flow of external grants has shielded the RMI from liquidity squeezes. The Palauan economy is projected to have rebounded in FY2018 as tourism activity recovered with the entry of new hotels, and construction picked up. This follows a 3.6 percent contraction in FY2017 as the government implemented its structural reform of the tourism sector away from a high-volume model and towards a highquality model of sustainable ecotourism development. Following explosive growth in tourist arrivals of over 52 percent between FY2013 and FY2015—driven by a 10-fold increase in Chinese tourists—authorities clamped down on package tourism and charter flights, as part of a new ‘Pristine Paradise Palau’ strategy to target the luxury tourism market and protect the environment. The result was a 28 percent fall in tourist arrivals from FY2015 to FY2017, although this was partially offset by a 15 percent increase in spending per tourist. Lower overall tourism receipts, combined with higher imports for transport and fuel, also weakened the external position, with the current account deficit reaching 18 percent of GDP in FY2017. Despite slowing growth, the economy continued to create jobs (up 4.1 percent in FY2017—the latest available data), meaning formal employment has increased by 20 percent since FY2012. Consumer prices rose by 0.9 percent in FY2017 and are expected to have risen only marginally in FY2018, as the stronger US dollar (the official currency of Palau) held down local prices for food and transport services. The combination of strong formal employment growth and low food price inflation is likely to have reduced the poverty risk for many Palauan households. Palau’s fiscal position has strengthened in recent years, with FY2017 registering a fiscal surplus (including grants) of 4.6 percent of GDP, the seventh consecutive annual surplus, underpinned by increased revenues from fishing license fees. These were partially offset by increased capital transfers to state governments, higher contributions to public sector pensions, and an increase in the public payroll. The government has retained a healthy cash balance, with reserves estimated to increase from around 3 months of government spending in FY2015 to about

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: North Pacific Islands

MANAGING HEADWINDS

In FY2019 growth is expected to register 0.9 percent and 2.3 percent, respectively, in the FSM and RMI, driven by continued infrastructure investment. In Palau, the rebound in growth is expected to continue, driven by increased tourism activity and ongoing tourism-related

construction. Overall, the outlook for the North Pacific countries is subject to substantial risks due to their reliance on grants, tourism, and commodity imports. A slow-down in key trading partners, a further U.S. dollar appreciation, and natural disasters could impact negatively on tourism activity. Higher commodity prices could make food and fuel imports costlier and inflation higher. These countries will have to rely on fiscal and structural policies should the above-mentioned risks materialize. Global financial sector volatility could also affect returns on the various trust funds and their ability to provide fiscal space for priority spending or respond to future shocks, given the limited space for additional debt and the lack of monetary policy levers.

Figure 1. Former sector employment

Figure 2. Overall fiscal balance

Index, 2007=100

Percent of GDP

6 months of spending by FY2021. However, the Compact Trust Fund remains below its pre-Global Financial Crisis level as a percent of GDP. Greater fiscal consolidation and revenue mobilization is necessary to ensure long-term fiscal sustainability.

Outlook and Risks

110

15

105 10 100 5 95 0 90

85 2007

▬▬PLW

-5 2008

2009

2010

▬▬RMI

2011

2012

2013

2014

2015

2016

2017

▬▬FSM

Sources: National sources via EconMap.

NORTH PACIFIC ISLANDS Selected Indicators Real GDP growth, at constant market prices Republic of the Marshall Islands Federated States of Micronesia Palau

2007

2008

▬▬PLW

2009

2010

2011

2012

▬▬RMI

2013

2014

2015

2016

2017

▬▬FSM

Sources: National sources via EconMap and latest available joint World Bank and IMF DSAs.

2015

2016

2017e

2018f

2019f

2020f

-0.4 4.9 10.1

1.9 -0.1 0.1

3.6 2.0 -3.7

2.5 1.4 5.0

2.3 0.9 4.0

2.2 0.7 3.0

Sources: EconMAP; IMF and World Bank MTI Global Practice. Notes: e = estimate; f = forecast.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: North Pacific Islands

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

PAPUA NEW GUINEA

Population, million GDP, current US$, billion GDP per capita, current US$ Poverty rate ($1.90/day 2011 PPP terms)a National poverty ratea Gini coefficienta Life expectancy at birth, yearsb

extractive economy. Preliminary estimates suggest that real GDP growth slowed from 2.8 percent in 2017 to 0.3 percent in 2018. This latest estimate stands in contrast with a pre-earthquake growth projection of 2.5 percent for 2018. The earthquake also had far-reaching effects on many communities in the highlands area. The disaster is estimated to have claimed more than 100 lives, affected more than half a million people, and caused extensive damage to basic infrastructure.

2018 8.4 22.3 2,645 38.0 39.9 41.9 65.5

Source: WDI, Macro Poverty Outlook, and official data. Notes: a. Most recent value (2009/10). b. Most recent WDI value (2016).

Real GDP growth is estimated to have slowed to 0.3 percent in 2018, adversely affected by a 7.5 magnitude earthquake that struck the country in the beginning of the year. In the post-earthquake period, economic growth is expected to bounce back in 2019 and then converge to its potential growth rate over the medium term. The anticipated investment in new resource projects and further concentration of exports around energy commodities raise the importance of increased government’s efforts for economic diversification.

The current account surplus expanded in 2018, underpinned by strong performance in international trade. Over the past two years, a recovery in global commodity prices has driven double-digit growth in PNG’s terms of trade, boosting the net surplus in merchandise trade. Larger deficits in net primary income over the same period had only a moderately offsetting effect, while overall movements in services trade and current transfers were negligible. The current account surplus is estimated to have reached a record high of K18.3 billion (24.9 percent of GDP) in 2018. On the surface, this looks very healthy for PNG with the country’s income and current transfers from the rest of the world significantly exceeding what it spends. However, the strong current account surplus also partly reflects an artificial constraint on spending and a corresponding welfare loss, with businesses and consumers often unable to access foreign exchange (FX) to import goods and services that they need, even if they have the local currency to purchase them. Foreign currency inflows from the current account surplus continue to be largely offset by outflows associated with capital and financial account deficits.

The February 2018 earthquake had a devastating impact on the economy and the population of Papua New Guinea (PNG). The 7.5 magnitude earthquake led to a temporary disruption in the production of liquefied natural gas (LNG) and other mining activities concentrated in the highlands area, leading to a contraction in the extractive sector which almost fully offset the expansion of the non-

Recognizing the economy’s dependence on the resource sector, the authorities have taken steps to promote greater diversification of the economy. First, in October 2018 the government adopted its new five year Medium Term Development Plan for 2018–22 (MTDP III), focusing on inclusive and sustainable growth. Second, in November 2018 the government announced the 2019 National Budget with a focus on supporting the implementation of MTDP III and building a broader-based economy. The government successfully tapped the international

122

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Papua New Guinea

Recent Developments

MANAGING HEADWINDS

bond market to address the FX shortage and finance its new development vision under the MTDP III. Following a roadshow to promote its debut sovereign bond, PNG raised a ten-year USD500 million sovereign bond (which was oversubscribed by seven times) in September 2018. Due to high demand, the bond interest rate was set at 8.375 percent, closer to the lower bound of a targeted range. Ongoing reforms to strengthen the monetary and exchange rate policy and framework are expected to improve business confidence and increase private investment and growth in the non-resource economy. Measures include addressing the FX shortage, managing the liquidity effects of the use of FX to clear the FX orders backlog, working on greater exchange rate flexibility, considering options for strengthening the interest-rate transmission mechanism, and enhancing modeling capacity in the central bank. From global as well as regional perspectives, prevalence of extreme poverty in PNG is high. About 38 percent of the population in 2010 (the latest household budget survey available) lived under the internationally recognized extreme poverty line of US$1.90 per day (2011 PPP terms). The national poverty rate was estimated at 39.9 percent of the population. This incidence of poverty is by far one of the highest rates in the East Asia and Pacific region. It is also higher than in many of PNG’s lower middle-income, resource-rich peer countries. Broadly consistent with the high proportion (87 percent) of the population living in rural areas, almost 90 percent of the country’s poor are located in rural PNG and are more likely to be engaged in agricultural activities.

Outlook Papua New Guinea’s medium-term economic outlook is relatively optimistic, underpinned by further large-scale resource projects. Real GDP growth is forecast to rebound to about 5 percent in 2019, primarily driven by a return to full annual production in the extractive sector. Nonextractive sector activity is expected to continue expanding,

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Papua New Guinea

with better investor confidence supported by improved access to foreign exchange. In the coming years, growth is estimated to hover at about 3–4 percent per year, until planned investments in new gas and mining projects kick in and improve PNG’s growth potential. Future large-scale investment in the resource sector appears likely, with plans to double LNG production and develop new gold, copper, and silver reserves. With increased FX inflows into the economy, the current pressure on the exchange rate may reverse, adversely affecting the competitiveness of the non-resource economy.

Risks and Challenges Downside risks to macroeconomic outcomes stem from both external and domestic sources. The main external risks include a softening of commodity prices—which would dampen exports and GDP growth and increase pressure on the exchange rate—and another natural disaster. Natural disasters, which are frequent in PNG, can devastate the local economy, disrupt the extraction and processing of natural resources, and create considerable fiscal pressures. Domestic risks include a failure to deliver macroeconomic stability via fiscal and monetary policy implementation and any civil unrest or disturbances, which could adversely affect production in the extractive sector, with potential negative spillovers to the rest of the economy. While not all of these risks can be fully mitigated (as they remain largely outside authorities’ control), the government’s ongoing fiscal consolidation efforts— aiming to boost revenue collection and streamline inefficient expenditure—will act as a stabilizing factor. To strengthen fiscal and debt sustainability the government should adhere to the adopted non-resource primary fiscal balance as a fiscal anchor and operationalize the established sovereign wealth fund. These measures, along with the implementation of the Public Expenditure and Financial Accountability Road Map 2015–18, constitute important efforts to strengthen fiscal resilience.

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

To facilitate broad-based, inclusive, and sustainable development, the government will need to focus more on investing in human capital and strengthening the business environment to spur private sector development. The government has already adopted the MTDP III, which focuses on facilitating inclusive and sustainable growth and the new medium-term budget with the central theme of building a broader-based economy. As the long-term development vision has already been developed and adopted, it will be critically important for implementation to follow in due course. While the government has identified certain sectors to be targeted, it will also be vital to focus on broad-based structural reforms that will benefit all economic sectors.

Substantial potential exists for the non-resource economy to serve as an engine of growth and job creation. Unleashing this potential requires specific sectoral policy responses to remove key impediments to private sector development, ranging from improving the productivity of physical and human capital to strengthening institutional capacity and addressing governance and corruption.

Figure 1. Real GDP growth, contribution to real growth

Figure 2. Key fiscal and debt indicators

Percent, percentage points

Percent of GDP

6

35

5 25 4 15

3 2

5 1 -5

0 -1

-15 -2 -25

-3 2016e

JJExtractive sector

2017e

2018e

JJNon-extractive sector

2019f

2020f

2021f

▬▬Real GDP growth

Source: World Bank staff estimates and forecast.

2016

JJRevenue

2017

2018e

2019f

▬▬Overall balance

JJExpenditure

2020f

2021f

▬▬Public debt, net

Source: World Bank staff estimates and forecast.

PAPUA NEW GUINEA S elected Indicators Real GDP growth, at constant market prices Extractivea Non-extractive Inflation (Consumer Price Index p.a.) Current Account Balance (% of GDP) Resourcea Non-resource Overall fiscal balance (% of GDP) Non-resource primary balance (% of non-extractive GDP) Public debt, net (% of GDP)

2016

2017e

2018e

2019f

2020f

2021f

2.6 11.5 0.3 6.7 22.0 25.6 -3.6 -5.0 -4.5 34.6

2.8 6.8 1.8 5.4 22.7 27.7 -5.0 -2.6 -1.6 34.6

0.3 -9.2 3.0 4.7 24.9 28.9 -4.0 -2.6 -2.8 35.4

5.1 12.6 3.0 4.8 24.7 30.6 -6.0 -2.3 -2.7 34.9

3.1 1.4 3.6 4.0 24.6 28.8 -4.2 -1.8 -1.0 34.7

3.4 3.4 3.5 4.0 21.2 25.0 -3.8 -1.5 -0.6 33.8

Sources: World Bank staff estimates and forecast. Note: e= estimate; f = forecast. a) The extractive sector includes mining, quarrying, petroleum and gas production.

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PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Papua New Guinea

MANAGING HEADWINDS

PHILIPPINES

net exports sector as exports slowed due to the downturn in electronics trade and weaker services trade. Investment drove growth, benefiting from expansionary fiscal policy which focused on addressing the country’s physical infrastructure gaps. Services and industry fueled growth despite a deceleration in 2018. A moderation in global trade activity dampened industry growth as manufacturing expanded by its slowest rate in seven years. Meanwhile, the agriculture sector continued to disappoint, barely contributing to growth, highlighting long-standing productivity gaps and vulnerabilities. 2018 106.5 331.7 3,114 6.1 26.0 55.1 44.4 110.9 69.1

Headline inflation increased to an average of 5.2 percent year-on-year in 2018 from 2.9 percent in 2017 driven by rising food, energy, and transport prices. Excluding the volatile food and energy items, the core inflation reached 4.1 percent year-on-year in 2018 from 2.5 percent in 2017, suggesting an underlying price pressure in the economy. Both headline and core inflation breached the central bank’s target range of 2–4 percent in 2018. In response, the central bank raised the policy rate by a cumulative of 175 basis points throughout 2018.

Philippine economic growth moderated in 2018 due to weak net export performance and a deceleration in private consumption brought by high inflation. Monetary policy tightening counterbalanced expansionary fiscal policy to maintain macroeconomic stability. Going forward, declining inflation will support a rebound in consumption and growth in the near term. The positive outlook will support poverty reduction through job creation, higher wages, and continuation of social programs. However, downside risks remain as both domestic and external policy uncertainty remain elevated.

The fiscal gap widened to 3.2 percent of GDP in 2018, breaching the deficit ceiling of 3.0 percent as the government maintained its expansionary fiscal policy stance. Public expenditure reached its highest level in more than three decades, driven by substantial increases in infrastructure and personnel services expenditures. Meanwhile, national government revenues reached its highest level in over two decades, helping contain the fiscal gap and ensuring long-term fiscal sustainability. This was partly due to the implementation of recent reforms to tax policy and administration, which contributed to the highest tax take (in percent of GDP) in two decades. Despite the wider deficit, the overall fiscal position remains healthy as the national government debt-to-GDP ratio further declined in 2018.

Population, million GDP, current US$ billion GDP per capita, current US$ International poverty rate ($1.9)a Lower middle-income poverty rate ($3.2)a Upper middle-income poverty rate ($5.5)a Gini indexa School enrolment, primary (% gross)b Life expectancy at birth, yearsb Sources: WDI, Macro Poverty Outlook, and official data. Notes: a. Most recent value (2015) 2011 PPPs. b. Most recent WDI value (2016).

Recent Developments The Philippine economy expanded by 6.2 percent yearon-year in 2018 from 6.7 percent in 2017, below the government’s 6.5–7.0 percent target. The growth moderation was a result of slower private consumption growth in 2018 which was dampened by the highest inflation in a decade, and the weaker performance of the

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Philippines

The peso weakness persisted in 2018, as it depreciated in nominal terms by 4.3 percent year-on-year in 2018, following a 5.8 percent depreciation in 2017. The weaker peso was driven by volatilities in financial markets due to the U.S. and China trade dispute, weakness in some

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

emerging economies, the ongoing normalization of the U.S. Federal Reserve rate, and a rising current account deficit reflecting lower export growth and higher imports of capital and intermediate goods. The countryâ&#x20AC;&#x2122;s balance of payments deficit widened in 2018 as improvements in the capital and financial account were not enough to compensate for the current account deficit. The expansion of real wages beginning the second half of 2018 and the continued movement of workers from agricultural employment to non-agricultural wage jobs, likely contributed to the increase in household incomes. Overall, household per capita income continued to increase faster than inflation and the income of the bottom 40 percent of the population grew at a faster rate than the average of the population during that period. It is likely that the growth of household incomes, especially of the bottom 40 percent of the population, has continued in 2018 although the impact of inflation may have slowed down poverty reduction.

Outlook The Philippine medium-term growth trajectory remains positive with growth expected to recover from the moderation in 2018. The World Bank forecasts real GDP growth at 6.4 percent in 2019 and 6.5 percent in 2020 and 2021. Growth is expected to be driven by higher private consumption growth on the back of subsiding inflation and strong election activities. Capital formation growth may moderate in the first half of 2019 due to the budget approval delay and the implementation of the pre-election spending ban on new public construction projects, but is expected to accelerate in the second half of 2019 as the public infrastructure investments regain momentum. Exports will remain sluggish given a weak external environment, while imports remain robust driven by capital requirements of businesses and for the infrastructure projects. Filipino households are likely to continue reaping the gains from high economic growth. Non-agriculture wages will

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continue to spur growth in household incomes particularly those belonging to the lower income groups. Social cash transfers, including programs that were started in 2018 will help mitigate the impact of high inflation. This year, the government has committed to continue the program with increased benefits. Poverty reduction is likely to continue based on the growth outlook in the coming years. Medium-term projections of poverty based on the middle-income poverty line of $3.20/day is projected to decline from 26 percent in 2015 to 20.7 percent in 2019, 19.5 percent in 2020 to 18.5 percent in 2021.

Risks and Challenges Downside risks to growth remain elevated. Key external risks come from heightened uncertainty generated by the US-China trade dispute, the ongoing policy normalization in advanced economies, and tighter global financing conditions. Key domestic risks come from the delayed implementation of the public infrastructure investment projects, partly caused by delayed 2019 budget approval, and policy uncertainty over tax reform programs that could prolong weakened investor confidence. In the medium term, the governmentâ&#x20AC;&#x2122;s expansionary fiscal strategy could lead to fiscal sustainability challenges if not accompanied by revenue increases. Still, strong macroeconomic fundamentals are in place to buffer against shocks. The long-term challenge for the Philippines is fostering the countryâ&#x20AC;&#x2122;s inclusive growth agenda. This requires a commitment to structural reforms that enhance market competition, encourage investments, and improve labor market condition. Key initiatives include revisiting foreign participation limits in the domestic market and enhanced efforts to improve doing business in the country. Supporting policies in the labor market includes training, job-search programs and measures to support workers affected by the sectoral shifts of employment. Sustained investment in human capital development specially in health and education, and in sectors that create quality employment are needed to support inclusive growth.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Philippines

MANAGING HEADWINDS

Figure 1. Real GDP growth, contribution to real growth

Figure 2. Actual and projected poverty rates, 2006–21

Percent, percentage points

Percent

15

Constant LCU, thousands

70

12

60

10

10 50

8 5 40 6 0

30 4 20

-5 10

2

0

0

JJPrivate consumption

JJGovernment consumption

JJInvestments

▬▬International poverty rate

▬▬Lower middle-income poverty rate

JJDiscrepancy

JJNet exports

▬▬GDP growth

▬▬Upper middle-income poverty rate

▬▬Real GDP per capita, rhs

Source: Philippine Statistics Authority (PSA).

PHILIPPINES Selected Indicators Real GDP growth, at constant market prices Private Consumption Government Consumption Gross Fixed Capital Investment Exports, Goods and Services Imports, Goods and Services Real GDP growth, at constant factor prices Agriculture Industry Services Inflation (Consumer Price Index) Current Account Balance (% of GDP) Net Foreign Direct Investment (% of GDP) Fiscal Balance (% of GDP) Debt (% of GDP) Primary Balance (% of GDP) International poverty rate ($1.9 in 2011 PPP)a,b Lower middle-income poverty rate ($3.2 in 2011 PPP)a,b Upper middle-income poverty rate ($5.5 in 2011 PPP)a,b

21 20

19 20

17 20

15 20

13 20

11 20

09 20

07 20

05 20

03 20

Q3 -2 01 8

Q1 -2 01 8

Q3 -2 01 7

Q1 -2 01 7

Q3 -2 01 6

Q1 -2 01 6

Q3 -2 01 5

Q1 -2 01 5

-10

Sources: World Bank staff estimates.

2016

2017

2018e

2019f

2020f

2021f

6.9 7.1 9.0 26.1 11.6 20.2 6.9 -1.2 8.0 7.5 1.3 -0.4 2.7 -2.4 45.6 -0.3 5.4 24.5 53.9

6.7 5.9 7.0 9.5 19.5 18.1 6.7 4.0 7.2 6.8 2.9 -0.7 3.2 -2.2 45.1 -0.3 4.7 23.1 52.7

6.2 5.6 12.8 14.0 11.5 14.5 6.2 0.8 6.8 6.6 5.2 -2.4 3.0 -3.2 45.0 -1.2 4.2 21.9 51.7

6.4 6.0 10.8 11.4 12.4 14.0 6.4 1.1 6.7 6.9 3.5 -2.3 2.9 -2.8 44.8 -0.7 3.7 20.7 50.6

6.5 6.0 10.0 16.5 13.0 16.4 6.5 1.5 6.8 6.9 3.3 -2.5 2.9 -2.8 44.5 -0.6 3.2 19.5 49.6

6.5 6.0 9.7 17.0 13.8 17.0 6.5 1.5 6.9 6.9 3.0 -2.5 2.8 -2.8 44.3 -0.6 2.8 18.5 48.5

Source: World Bank, Poverty & Equity and Macroeconomics, Trade & Investment Global Practices. Notes: e = estimate, f = forecast. a) Calculations based on EAPPOV harmonization, using 2006-FIES and 2015-FIES. Actual data: 2015. Nowcast: 2016–2018. Forecast are from 2019 to 2021. b) Projection using annualized elasticity (2006–2015) with pass-through = 1 based on GDP per capita in constant LCU.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Philippines

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SOLOMON ISLANDS

Population, million GDP, current US$ billion GDP per capita, current US$ National basic needs poverty rate (%)a School enrolment, primary (% gross)a Life expectancy at birth, yearsa

2017 0.6 1.3 2,133 12.7 114.8 70.7

Source: WDI, Macro Poverty Outlook, and official data. Notes: a. Solomon Islands National Statistics Office. Most recent value (2013). Most recent WDI value (2016).

Growth in 2018 is projected at 3.5 percent, backed by record log output. Increased global commodity and domestic food prices saw inflation increase to 2.7 percent in 2018. Strong fiscal consolidation efforts included measures to mobilize revenues and restrain expenditures, and a reduction of arrears. The 2019 budget continues this path. The economic policy dialogue with development partners and budget support was resumed. Elections are scheduled for April 2019. Risks include a sharp downturn in the Chinese economy and uncertainties in the logging and mining sectors.

Recent Developments Economic growth is projected at around 3.5 percent for 2018, underpinned by growth in agriculture, forestry, manufacturing, and services. Forestry remains a key contributor to economic growth and a key source of foreign exchange for Solomon Islands. Exports are projected to reach a record high of 2.8 million cubic meters, an increase by nine percent compared to 2017. Between 2015

128

and 2017, the government pursued expansionary fiscal policy with investments towards rural infrastructure and development, and the health and education sectors. These increased levels of expenditures resulted in fiscal deficits, financed through a draw-down of the government’s cash reserves, which declined from 3.6 months of recurrent spending to around 1 month over the same period. As a result, the government’s ability to absorb price or natural disaster shocks was severely limited. Public financial management problems throughout 2017 resulted in the accumulation of substantial domestic payment arrears (1.4 percent of GDP), impeding private sector activity. A newly-formed government in end-2017 eliminated the payment arrears and returned to fiscal prudence with the passage of a balanced budget in 2018. This was achieved through a substantial reduction in development expenditures, possibly affecting levels of service delivery in rural areas. A supplementary budget was passed in August to cater mainly for unbudgeted public works contracts and payment arrears arising throughout the year, financed almost fully by stronger than expected revenues and a domestic development bond. The 2019 government budget continues the fiscal consolidation efforts of 2018, targeting a fiscal balance of zero. This is underpinned by conservative revenue estimates that show a decline in revenue by nine percent, reflecting a projected decline in donor support and in logging exports in line with the new sustainable logging policy. Expenditure allocations are six percent lower than in 2018, mainly due to a reduction in allocations for constituency development funds. Total PPG external debt increased from 7.7 percent of GDP at end-2017 to 9.3 percent at end-2018. International reserves have increased from US$576 million at end2017 to US$613 at end-2018, equivalent to 8.8 months of imports. The current account deficit is projected to widen from 4.2 percent of GDP in 2017 to over 6 percent in 2018, reflecting heightened levels of imports related to large infrastructure projects—most of which are partly or fully externally financed. Inflation (period average) is projected to have accelerated from 0.5 percent in 2017 to 2.7 percent in 2018, mainly on account of increases in the prices of food and beverages and higher global commodity prices.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Solomon Islands

MANAGING HEADWINDS

Outlook

Risks and Challenges

Despite current fiscal consolidation efforts, growth is projected to only marginally decline from current levels, averaging just under 3 percent per year over the medium-term, and continue to be driven by major infrastructure investments in the roads, air transport, telecommunications and energy sectors. This baseline scenario also assumes resumed gold-mining activity, the exploitation of large nickel deposits, and sustained levels of foreign direct investment averaging 3.3 percent of GDP. A new sustainable forestry policy seeks to gradually curb log output and is expected to impact fiscal space going forward. However, the continuation of sound fiscal management in 2019, complemented by key public financial management reforms and a tax review, are expected to ease fiscal pressures. The payment of expenditure arrears instilled confidence. Enhanced commitment control and cash management will be essential to avoid the recurrence of arrears. Cash reserves will need to be rebuilt to ensure effective cashflow management and buffer against shocks. Expenditure pressures associated with large unmet expenditure needs for infrastructure and public service delivery, and the hosting of the 2023 South Pacific Games pose a risk to medium-term fiscal consolidation. The current account deficit—financed through large aid flows in the capital account—is expected to widen further to around 8 percent of GDP in 2019, reflecting a continued increase in imports, and the underlying long-run decline in logging exports. The Honiara Consumer Price Index is expected to remain at around 3 percent over the medium term.

Parliamentary elections scheduled for April 2019 bring uncertainty with regard to the economic policy stance of a new government, including with regard to the continuation of the fiscal consolidation path set out in the 2019 budget and efforts to enhance the quality of public spending. With logging sources expected to be depleted in the long run and uncertainty around the exploitation of the country’s mining potential, Solomon Islands faces the challenge of developing new sources of growth. In the near term, growth will be supported by infrastructure projects and logging may not decline significantly. This outlook is subject to considerable risks, particularly from any contraction in log demand in China (the main export destination for logs), or delays in infrastructure projects. Thereafter, the impending decline of the logging industry will impact growth and be a vital source of government revenue. The new sustainable forestry policy may risk being undermined and result in foregone revenues, if insufficient resources are dedicated to its implementation. Mining could become a driver of growth but developments in the sector hinge on the adoption of a legal and regulatory framework conducive to mining, and on clear procedures for the acquisition of land (for the exploration and exploitation). Such frameworks and procedures, which are currently being put in place, will also ultimately impact the extent to which forthcoming benefits from mining are shared across the population. In the context of a constrained fiscal environment, a heightened focus on development expenditures could maximize their effectiveness for the most vulnerable.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Solomon Islands

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Figure 1. Real GDP per capita

Figure 2. Trade balance

Percent change

2003=100 160

12 10

140

8

$ thousands

Percent of GDP 40

1,000 900

30

800 120

6

20 700

100

4

80

2 0

60

-2

10

600

0

500 400

-10

300 40

-20 200

JJReal GDP per capita

▬▬Real GDP per capita index

Sources: Word Bank staff estimates, IMF.

SOLOMON ISLANDS Selected Indicators Real GDP growth, at constant market prices Inflation (Consumer Price Index) Balance of Payments Current Account Balance (% of GDP) Imports, Goods and Services Exports, Goods and Services Foreign Direct Investment Fiscal Balance (% of GDP) External Debt (% of GDP)

▬▬Imports

JJTrade balance, rhs

20 20

18 20

16 20

14 20

12 20

20

10

-40

08

0

20

20 20

18 20

16 20

14 20

12 20

10 20

20

20

08

0

06

-8

-30

100

06

20

-6

20

-4

▬▬Exports

Sources: Central Bank of Solomon Islands, World Bank staff estimates, IMF.

2016

2017e

2018e

2019f

2020f

2021f

3.3 0.5

3.0 0.5

3.5 2.7

2.9 2.6

2.8 2.9

2.7 3.2

-3.9 50.7 44.9 3.0 -3.8 7.2

-4.2 51.4 45.6 1.9 -3.8 7.7

-6.4 53.3 45.3 2.1 0.0 9.3

-8.3 55.5 45.1 3.2 0.0 11.6

-8.8 55.3 44.5 3.3 0.1 14.3

-7.4 53.7 42.3 3.4 0.3 16.6

Sources: World Bank, Poverty & Equity and Macroeconomics, Trade & Investment Global Practices. Notes: e = estimate; f = forecast.

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SOUTH PACIFIC ISLANDS

2017 Population, million Samoa Tonga Vanuatu GDP, US$ billion Samoa Tonga Vanuatu GDP per capita, current US$ Samoa Tonga Vanuatu

0.20 0.11 0.28 0.84 0.45 0.87 4,255 4,200 3,100

wire harnesses in August 2017, and as fishing exports reverted to more normal levels after two exceptional years. This was only partially offset by the impact of higher public infrastructure spending and Samoa’s hosting of regional meetings. Average annual inflation rose to 3.7 percent in FY2018 from 1.3 percent in FY2017, due primarily to increases in import prices, but also increases in domestic food prices in the wake of TC Gita in February 2018 (which had a relatively limited economic impact otherwise). Since FY2016, the current account deficit has narrowed to below 3 percent of GDP, due in part to strong growth in tourismrelated services exports, although imports for various construction projects have picked up more recently. Due to significant increases in domestic revenue collection, prudent controls on budgeted spending, and in some cases weaker-than-expected spending execution, the government ran only small fiscal deficits in FY2016 and FY2017 (averaging less than 1 percent of GDP) and a budget that was close to balance in FY2018. Spending is expected to pick up in FY2019, in part due to preparations for the Pacific Games to be held in July 2019.

Recent Developments

Tonga continues to recover from Cyclone Gita which hit in February 2018, caused widespread damage and losses estimated to total US$164 million, or 38 percent of GDP. Latest estimates suggest that growth slowed to around 1 percent in FY2018 due to the impact of the cyclone on agricultural production, tourism, and the commercial sector, though these impacts appear to have been somewhat smaller than originally feared. Relatively fast inflation—7.3 percent in annual average terms in FY2017, due primarily to dry weather and policy-driven tax increases—has persisted for longer than expected, due in part to the impact of TC Gita on local market food prices. The current account deficit narrowed to around 7 percent of GDP in FY2018 (from 12 percent of GDP in FY2017) due to an increase in remittances and current aid transfers.

Economic growth in Samoa slowed sharply to 0.7 percent in FY2018 (year ended June) from 2.7 percent in FY2017, due to the closure of a major manufacturer of automotive

In recent years the authorities have maintained a generally prudent fiscal stance, with the deficit contained at around half a percent of GDP in FY2016 and FY2017,

Sources: WDI, World Bank staff estimates.

In the South Pacific countries—Samoa, Tonga, and Vanuatu—growth has been affected by natural disasters and other economic shocks. Tonga is in the early stages of recovery from Tropical Cyclone (TC) Gita which hit in February 2018, while several reconstruction projects have supported growth in Vanuatu since TC Pam struck in 2015. Fiscal pressures in each country and further risks of natural disasters require an increase in domestic revenues, controlled current spending, and carefully prioritized capital spending.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: South Pacific Island Countries

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

and domestic revenues on an upwards trend. Despite the substantial recovery and reconstruction needs associated with TC Gita, a small fiscal surplus was realized in FY2018, due to delays in the roll-out of cyclone-related spending; substantial government efforts to create fiscal space by limiting other expenditures; and prompt donor support. Vanuatu is close to full recovery from Tropical Cyclone Pam, which struck in March 2015. Continued work on infrastructure projects—including roads, ports, and airports—as well as a strength in tourism arrivals are expected to have driven GDP growth of around 3.4 percent in CY2018, from 4.4 percent the previous year. Annual inflation was recorded at 3.2 percent in the December quarter of 2017, reflecting increased domestic demand for food, transport and education, but slowed to 2.3 percent in the June quarter of 2018, in part due to the introduction of government subsidies for school fees. The current account deficit was estimated to have widened to around 9 percent of GDP in 2017 and 2018—in line with the high import content of infrastructure projects—and was financed in part through foreign grants. The advancement of several major reconstruction and rehabilitation projects following Tropical Cyclone Pam resulted in significant fiscal pressures in 2016 and 2017. Government spending in 2017 surpassed 2016 levels by around 13 percent, largely due to severance payments and the Pacific Mini Games, widening the fiscal deficit from 6.1 percent in 2016 to 7.5 percent in 2017. An increase in the public wage bill and a substantial supplementary budget added to fiscal pressures in 2018, though these pressures have been offset by an increase in the VAT rate from 12.5 to 15 percent (in January 2018) and underspending of the capital budget.

to: i) the establishment of two new business operations at the old Yazaki plant (producing mattresses and wire harnesses, and re-employing a small proportion of the exYazaki workers); ii) the July 2019 Pacific Games, which will drive increases in tourism and related activities; and iii) the completion of several public infrastructure projects. Over the medium term, the economy will be supported by continued growth in the tourism and agriculture sectors, which should directly create formal job opportunities for Samoa’s more vulnerable people (including its youth who tend to experience particularly high levels of unemployment), while also spurring related activity in the informal sector. In Tonga, reconstruction and repair activity for housing, public buildings, and schools is projected to ramp up over the next two to three years, which, together with a continued recovery in the agriculture and services sector, is expected to drive a rebound in growth to around 4 or 5 percent. Nevertheless, public sector cyclone recovery needs estimated at around a quarter of GDP have only been partially covered by donor pledges, which may lead to some pressure on government finances and/or mean that some recovery needs remain unmet. In Vanuatu, GDP growth of 3.6 percent is projected for 2019, but growth is expected to ease to around 3 percent over the medium-term, as large infrastructure projects are completed. Nevertheless, the government’s substantial public investment and cyclone reconstruction program should ultimately help to raise the productive capacity of the economy over the medium to long term. Reforms to tax administration and a focus on improved compliance, coupled with a winding down of capital spending, are expected to gradually narrow the fiscal deficit to around 3 percent of GDP over the next two to three years.

Outlook Risks and Challenges In Samoa, economic growth is projected to pick up in FY19 and FY20 before settling at between 2 and 2.5 percent per year in the medium term. Growth is expected to rebound to 3.2 percent in FY19 and around 5 percent in FY20, due

132

For each of these small South Pacific nations, natural disasters and external economic shocks pose a constant threat to economic growth and fiscal sustainability. Efforts

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: South Pacific Island Countries

MANAGING HEADWINDS

to expand and maintain fiscal buffers are important to help manage these risks. In Samoa, continued fiscal restraint is important to prevent a rise in public debt. Government spending is projected to rise in Samoa, though the projected increases are relatively small compared to the substantial fiscal consolidation achieved over the last few years, with external public debt declining to well below 50 percent of GDP. Nevertheless, as public debt remains comparatively high, it is important that overall fiscal restraint is maintained, consistent with recent government efforts to increase domestic revenues, control spending, and pursue only high-priority and concessionally-funded capital investments.

In general, the key challenge facing Tonga in the next few years is to maintain its prudent fiscal stance in the face of several competing pressures. The government should carefully prioritize cyclone-reconstruction and development spending, mindful of budget and local capacity constraints, and continue to strengthen management of the government wage bill. In Vanuatu, public investment prioritization remains an important challenge. The much-needed public investments in infrastructure have placed considerable pressure on public finances, and delays in the implementation of new revenue mobilization measures could further strain fiscal accounts. Current and planned public investments therefore need to be implemented in a prioritized fashion, and with due regard to domestic capacity constraints.

Figure 1. I ncidence of poverty at international poverty lines and national hardship thresholds

Figure 2. Public and publicly guaranteed external debt

Percent of the population

Percent of GDP

45

60

40 50 35 40

30 25

30 20 20

15 10

10 5 0

0 TON (2009)

WSM (2008)

JJExtreme poverty (US$1.90/day) JJPoverty (US$3.20/day)

VUT (2010)

JJNationally defined hardships

Sources: World Bank (2016), Systematic country diagnostic for the eight small Pacific Island Countries.

SOUTH PACIFIC ISLANDS S elected Indicators Real GDP growth, at constant market prices Samoa Tonga Vanuatu

2010

2011

▬▬Samoa

2012

2014

▬▬Tonga

2016

2017

2018

▬▬Vanuatu

Sources: Latest available joint World Bank and IMF DSAs.

2015

2016

2017

2018

2019f

2020f

1.6 3.7 0.2

7.1 3.4 3.5

2.7 2.7 4.4

0.7 1.2 3.4

3.2 3.9 3.6

5.0 5.1 3.2

Sources: World Bank, Macroeconomics and Fiscal Management Global Practice, and Poverty Global Practice. Notes: Financial years for Samoa and Tonga are Jul–Jun, for Vanuatu is Jan–Dec. e = estimate; f = forecast.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: South Pacific Island Countries

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

THAILAND

Population, million GDP, current US$ billion GDP per capita, current US$ Upper middle-income poverty rate ($5.5)a Gini indexa School enrolment, primary (% gross)b Life expectancy at birth, yearsb

in private consumption and private investment. While exports value slowed down in 2018, private consumption and private investment posted their highest growth rates in six years, expanding by 4.6 percent and 3.9 percent respectively. In line with the strong expansion in private consumption, manufacturing, wholesale, retail trade and services contributed the most to real GDP growth on the production side.

2018 69.2 493.2 7,129 7.8 36.5 100.7 75.3

Source: WDI, Macro Poverty Outlook, and official data. Notes: a. Most recent value (2017), 2011 PPPs. b. Most recent WDI value (2016).

The Thai economy posted the highest growth rate in six years (4.1 percent), despite adverse external shocks to trade and tourism in 2018. Strengthening domestic demand helped offset a significant decline in exports and foreign tourists. As global economic prospects deteriorate, private consumption, private investment and expansionary fiscal policy are expected to support growth in 2019 and 2020. Domestic risks to this outlook include a delay in private investment due to a continued slowdown in exports, policy discontinuity after the elections, and a delay in infrastructure spending due to slow disbursement. External risks include further deceleration in global trade.

Recent Developments Despite external shocks to trade and tourism in 2018, the Thai economy posted the highest growth rate in six years, at 4.1 percent. The economy has so far proven to be resilient to strong global headwinds thanks to a strengthening domestic demand stemming from a continued upswing

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The macroeconomic environment remained healthy and stable, contributing to the economyâ&#x20AC;&#x2122;s resilience. The government continued to maintain a stable fiscal deficit, estimated at 3 percent of GDP in 2018. While government revenues were up 6.8 percent in FY2018, compared to FY2017, public expenditures only grew by 4 percent in FY2018. Headline inflation remained low, averaging 1.1 percent in 2018. Although, inflation remained low and near the lower bound of the inflation target range, the Bank of Thailand increased the policy rate from 1.5 percent to 1.75 percent in December 2018 in response to global financial market volatility and risks of capital outflows. The current account remained in surplus, but has declined due to the narrowing trade surplus, going from US$34.2 billion in 2017 to US$25.9 billion in 2018. The Thai baht appreciated in 2018, stemming from a current account surplus and net capital inflows in the Thai bond market. This contrasts sharply with most currencies in the region which have weakened in response to net portfolio outflows and higher current account deficits in 2018. In recent years, progress in poverty and inequality reduction has slowed down. Poverty rates based on the Upper-Middle Income Class poverty line ($5.5/day 2011PPP) increased between 2015 (7.1 percent) and 2017 (7.8 percent), mainly due to negative shocks to the agricultural sector and sluggish wage growth during the 2015â&#x20AC;&#x201C;17 period, which was much lower compared to previous years. This led to low and negative growth in household consumption among the poorer segments of the population and caused a small increase in (consumption) inequality. Inequality has become a social issue at the forefront of policy discussions as more evidence of a widening gap emerges. Only 39 percent of Thais in 2018 felt that their standard

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Thailand

MANAGING HEADWINDS

of living was getting better, the lowest when compared to other East Asian countries surveyed during a similar period. While worsening and stagnating poverty and inequality conditions were seen between 2015–17, positive indicators are emerging in 2018 that may signal renewed progress in poverty reduction. In 2018, Q3 employment levels in both agricultural and non-agricultural sectors simultaneously increased for the first time in 22 quarters. Total employment in 2018 increased after 4 years of decline, led by strong recovery in agricultural employment. In line with the rise in employment, the unemployment rate in Q3-2018 was the lowest in 8 quarters. In April 2018, the minimum wage was raised to 308–330 baht per day (varying by province), from a previous range of 300–310 baht per day.

Outlook Due to headwinds such as weaker global economic prospect, moderating industrial production, and lingering trade tensions, real GDP growth is projected to soften to 3.8 percent in 2019 and 3.9 percent in 2020. Growth will be supported by public spending on large infrastructure projects, as well as a robust expansion of private consumption and private investment.

Risks and Challenges Amid heightened global uncertainty from trade protectionism, there is an increased risk that the expected slowdown in exports may derail the ongoing reorientation from external to domestic demand driven economic growth. That is because, investors may hold back private investment in export industries as well as related industries. In addition, near-term growth projections assume that the government will deliver on planned public infrastructure projects, which is scheduled to accelerate in 2019 and pick up in 2020 as Eastern Economic Corridor related projects are implemented. Failure to implement public projects in a timely fashion and increase public investment disbursement rates pose the largest domestic risk to growth going forward (disbursement rate stood below 60 percent in FY2017 and FY2018). Political risk surrounding the long-awaited elections recently held on March 24 remains substantial. The transition to a new government may take longer than expected, potentially affecting the continuity of government programs and delaying public and private investment decisions.

In terms of how this outlook affects households, it will depend on the distributional nature of growth. The poorest households in Thailand are usually in rural areas, with employment in the agricultural sector, and have household heads who are elderly and/or have low levels of education. Fiscal policy will play an important role for these poorer households since they are typically less dependent on market income, and a larger share of their income is from non-labor sources such as remittances, social assistance, and transfers. Government spending on unconditional transfer programs and elderly and pension schemes could help reduce poverty and inequality, but questions exist as to how well targeted these programs are and if they are reaching the poor.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Thailand

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Figure 1. Real GDP growth, contribution to real growth

Figure 2. Employment growth and unemployment rate

Percent

Percent yoy

Percent 1.4

6

4

5

3

4

2

3

1

2

0

0.8

1

-1

0.6

0

-2

-1

-3

-2

-4

1.2 1.0

0.4

-3

0.2

-5 2016

2017

2018

2019

2020

JJPrivate consumption

JJGovernment consumption

JJInvestment

JJNet exports

JJChange in inventories

▬▬GDP growth

Sources: National Statistics Office and World Bank staff estimates.

THAILAND Selected Indicators Real GDP growth, at constant market prices Private Consumption Government Consumption Gross Fixed Capital Investment Exports, Goods and Services Imports, Goods and Services Real GDP growth, at constant factor prices Agriculture Industry Services Inflation (Consumer Price Index) Current Account Balance (% of GDP) Net Foreign Direct Investment (% of GDP) Fiscal Balance (% of GDP) Debt (% of GDP) Primary Balance (% of GDP) Upper middle-income poverty rate ($5.5 in 2011 PPP)a,b

2021

0 2013

JJTotal

2014

JJAgricultural sector

2015

2016

2017

JJNon-agricultural sector

2018

▬▬Unemployment rate

Sources: Office of the National Economic and Social Development Council.

2016

2017

2018e

2019f

2020f

2021f

3.3 3.0 2.2 2.8 2.8 -1.0 3.5 -2.5 2.9 4.6 0.2 11.7 -0.1 0.6 41.2 1.4 8.4

3.9 3.2 0.5 0.9 5.5 6.8 4.0 6.2 1.6 5.3 0.7 11.0 -2.3 -2.5 40.1 -1.4 7.8

4.1 4.8 5.2 4.8 5.9 7.2 4.0 4.0 5.3 3.3 1.1 8.1 -0.2 -2.9 40.0 -1.7 6.9

3.8 4.3 4.6 5.8 5.7 7.1 3.8 3.3 4.5 3.5 1.0 6.4 0.4 -3.0 41.6 -2.0 6.0

3.9 4.8 4.3 4.5 5.5 6.8 3.9 3.3 4.0 3.9 1.0 4.7 0.8 -2.9 44.4 -2.4 5.4

3.9 4.8 4.3 5.1 5.5 6.8 3.9 3.3 4.0 3.9 1.0 3.0 0.8 -2.9 46.1 -2.3 4.7

Source: World Bank, Poverty & Equity and Macroeconomics, Trade & Investment Global Practices. Notes: e = estimate; f = forecast. a) Calculations based on EAPPOV harmonization, using 2017-SES. Actual data: 2017. Nowcast: 2018. Forecast are from 2019 to 2021. b) Projection using neutral distribution (2017) with pass-through = 0.87 based on GDP per capita in constant LCU.

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TIMOR-LESTE

Population, million GDP, current US$ billion GDP per capita, current US$ School enrolment, primary (% gross)a Life expectancy at birth, yearsa

is thought to have been used to settle previous financial commitments. These fiscal trends had notable effects on the private sector, affecting both consumer and business confidence. Overall, non-oil gross domestic product (GDP) is estimated to have contracted by 0.7 percent in 2018.

2018 1.3 1.6 1,187 109.5 68.9

Source: WDI, Macro Poverty Outlook, and official data. Notes: a. Most recent WDI value (2016).

The economy is expected to have contracted for a second consecutive year, partly owing to a large decline in public spending during the first nine months of 2018. Private consumption was also adversely affected by the contraction in public spending, as well as by political and economic uncertainty. The promulgation of the 2019 state budget in February underpins a favourable economic outlook, but medium-term risks remain elevated. Safeguarding fiscal sustainability and improving the quality of public expenditure should be the key policy priorities.

Recent Developments The political impasse that followed the mid-2017 parliamentary elections continued to affect economic activity in 2018. But unlike 2017, much of 2018 went by without an approved budget. Spending was hampered by limited domestic resources, since access to the Petroleum Fund is typically secured through the budget process. At the end of September, spending was about one-third lower than in the first three quarters of 2017. The remainder of 2018 witnessed a strong recovery, although most spending

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Timor-Leste

The fiscal deficit eased to some extent. Total revenues were boosted by an increase in the Estimated Sustainable Income (ESI), which is the amount that can be sustainably withdrawn from the Petroleum Fund for budget financing. The rise in the ESI more than offset the 9 percent drop in domestic revenues, while public expenditure was about 3 percent lower than in 2017. The deficit was largely financed through excess withdrawals from the Petroleum Fund, which ended the year with a balance of $15.8 billion—about $1 billion lower than in 2017. Consumer price inflation remained contained despite increasing to 2.1 percent in 2018. Inflation was driven by higher food and tobacco prices, as well as education and transport. The real effective exchange rate appreciated in 2018 because of the strengthening of the US dollar—the legal tender in Timor-Leste. Credit to the private sector declined by 2 percent, probably owing to concerns over creditors’ ability to repay debts. In fact, the proportion of non-performing loans is rising once again—from 4 percent in March to 6 percent in December—due to weakening economic conditions. The trade deficit improved as a result of stronger exports— which mainly comprise travel services and coffee—and lower imports. Primary income increased as petroleumrelated revenues benefited from higher international oil prices, which partly contributed to the improvement in the current account balance. The economic and social impacts of two consecutive contractions is likely to become clearer throughout the year, as data on employment levels and labour earnings becomes available.

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Outlook Despite the late promulgation of the state budget, the economic outlook for 2019 seems more favourable than six months ago. GDP is forecast to grow by 3.9 percent under a scenario of greater political and economic stability. An expansionary fiscal stance will steer economic recovery, coupled with stronger private consumption. By 2020, the economy is predicted to be above the activity levels observed in 2016. Inflation is expected to remain below 4 percent, assuming favourable international food prices and a relatively strong US dollar. However, the fiscal balance is likely to deteriorate further due to rising public expenditures, a declining ESI, and subdued domestic revenue mobilization. The current account deficit is also anticipated to widen in the medium-term. The demand for imports will continue to expand, partly as the development of the ambitious Tasi Mane project accelerates—which comprises a liquified natural gas (LNG) plant in Beaço, a refinery and petrochemical complex in Betano, and a supply base in Suai. Primary income will decrease because of unwinding petroleum production at the Bayu-Undan field, while revenues from the Greater Sunrise fields are unlikely to start flowing very soon. Consequently, the financial account will continue to support large (and growing) fiscal and current account deficits through even larger withdrawals from the Petroleum Fund.

Internal risks remain elevated, as political tensions have subsided but not dissipated. A new political cycle began in mid-2018 with a change in government. However, the President vetoed the initial budget proposal as well as a contentious law amendment that regulates petroleum activities. While these issues were subsequently overcome, several members of cabinet are yet to be confirmed by the President, which may affect the smooth implementation of the state budget. With offshore petroleum production expected to cease in 3–4 years, large Petroleum Fund withdrawals will accelerate asset depletion and further threaten fiscal sustainability. Securing private investors for upstream and downstream development of the Greater Sunrise oil and gas fields would lessen exposure to commercial risks. Moreover, fiscal policy improvements can have multiplier effects on the economy—especially through greater spending efficiency and more strategic budget allocations. Improving the quality of public spending would ensure that better economic and social outcomes can be achieved for the same level of resources invested. The key challenges facing Timor-Leste include accelerating economic growth—to reach the government’s 7 percent target rate—and diversifying the economy. Improvements in these areas would support much needed job creation for the youth and a faster reduction in income poverty.

Risks and Challenges The economy is somewhat shielded from external shocks due to limited trade and financial integration in the region. However, rising international food prices (or a falling US dollar) could impact poorer households, while lower petroleum prices would reduce petroleumrelated revenues. In addition, worsening global financial conditions would affect the Petroleum Fund’s investment returns through negative stock market revaluations. Despite these downside risks, the large fiscal buffer provided by the sovereign wealth fund can be used to weather most external shocks.

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PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Timor-Leste

MANAGING HEADWINDS

Figure 1. Real GDP growth, contribution to real growth

Figure 2. Fiscal aggregates

Percent, percentage points

Percent of GDP

10

100

5

50

0

0

-5

-50

-10

-100 2016

JJConsumption

2017

JJInvestment

2018

2019

JJChange in inventory

2020

JJNet exports

2021

▬▬Growth

Sources: Ministry of Finance and World Bank staff estimates.

TIMOR-LESTE S elected Indicators Real GDP growth, at constant market prices Private Consumption Government Consumption Gross Fixed Capital Investment Exports, Goods and Services Imports, Goods and Services Real GDP growth, at constant factor prices Agriculture Industry Services Inflation (Consumer Price Index) Current Account Balance (% of GDP) Fiscal Balance (% of GDP)a

2016

2017e

2018e

JJRecurrent expenditure JJCapital expenditure

2019f

JJTotal revenue

2020f

2021f

▬▬Fiscal balance

Sources: Ministry of Finance and World Bank staff estimates. Note: Total revenue includes the ESI but not excess withdrawals.

2016

2017e

2018f

2019f

2020f

2021f

5.1 7.9 -1.2 15.3 6.6 8.4 4.7 3.0 7.6 4.4 -1.3 -32.3 -49.3

-3.5 0.9 -5.8 -16.7 -37.7 -11.6 -3.3 -3.2 -23.4 2.6 0.6 -17.9 -29.8

-0.7 -4.1 -8.5 10.5 3.3 -5.4 -0.7 1.5 -11.2 1.1 2.1 -10.2 -26.0

3.9 2.8 10.4 7.3 3.7 11.3 3.9 1.9 6.9 3.8 2.5 -15.3 -34.1

4.6 4.3 2.9 7.9 3.9 4.9 4.6 2.1 5.1 5.1 3.3 -20.1 -31.5

4.9 4.4 2.4 8.4 5.1 4.4 4.9 2.3 4.9 5.5 3.7 -22.8 -30.6

Source: World Bank, Poverty & Equity and Macroeconomics, Trade & Investment Global Practices. Notes: e = estimate, f = forecast. a) The ESI is part of total revenue, while excess withdrawals from the PF is a financing item.

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Timor-Leste

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

VIETNAM

Population, million GDP, current US$ billion GDP per capita, current US$ International poverty rate ($1.9)a Lower middle-income poverty rate ($3.2)a Upper middle-income poverty rate ($5.5)a Gini indexa School enrolment, primary (% gross)b Life expectancy at birth, yearsb

growth accelerated to 7.1 percent in 2018, underpinned by a broad-based pickup in economic activity. Growth in the agriculture, forestry, and fishery sectors accelerated to 3.5 percent from 2.8 percent in 2017. The industrial and construction sectors expanded by 8.5 percent, driven by robust growth of 13 percent in manufacturing that benefitted from healthy external demand. The services sector posted 7.2 percent growth, supported by sustained strength in domestic consumption and tourism.

2018 94.6 243.3 2,572 2.0 8.4 29.0 35.3 110.0 76.3

Source: WDI, Macro Poverty Outlook, and official data. Notes: a. Most recent value (2016), 2011 PPPs. b. Most recent WDI value (2016).

Vietnam’s economy continues to show fundamental strength, supported by robust domestic demand and export-oriented manufacturing. The extreme poverty rate is estimated to have declined to below 3 percent. While the medium-term outlook is broadly favorable, significant downside risks are tied to weak external demand, global financial volatility, and incomplete banking and stateowned enterprise (SOE) reforms. On the upside, Vietnam is strongly positioned to benefit from numerous free trade agreements that are coming into force now and over the forecast period.

Recent Developments Vietnam’s economy continues to show fundamental strength, supported by robust domestic demand and export-oriented manufacturing. Following 6.8 percent growth in 2017, preliminary data indicate that GDP

140

Strong economic activity has supported continued employment creation and poverty reduction. Unemployment was unchanged at 2.2 percent in 2018, as in 2017, and underemployment declined to 1.5 percent over the same period from 1.7 percent in 2017. Estimates of poverty based on the international lower middleincome poverty line ($3.2 PPP 2011) are projected to have declined from 8.4 percent in 2016 to 5.9 percent in 2018. After accelerating in the first three quarters of 2018, reflecting hikes in administered prices, the headline CPI moderated significantly in the last quarter of 2018, due to softer food and fuel prices. For the year as a whole, the headline CPI remained moderate at 3.5 percent, well below the State Bank of Vietnam’s (SBV) inflation target of 4 percent. Vietnam’s monetary policy continues to balance its dual objectives of maintaining stability while supporting economic growth. While the monetary policy stance remains broadly accommodative, the SBV introduced some tightening of credit in 2018 by setting credit growth limits for commercial banks and controlling lending to high risk sectors (real estate, securities, and consumer market). Liquidity in the banking sector also tightened markedly, due to slower deposit growth pushing up short term interbank interest rates. Amid tighter financing conditions, credit growth moderated to about 14 percent (year-on-year) in 2018 from 18 percent in 2017. Nevertheless, corporate and household balance sheets are increasingly leveraged with Vietnam’s credit-to-GDP ratio at about 135 percent. This leaves the economy vulnerable to shocks and potential financial market stress, especially

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Vietnam

MANAGING HEADWINDS

given legacy NPLs and relatively thin capital buffers in some banks. Vietnam’s external balances continued to improve in 2018, despite uncertain global trade developments. Vietnam’s merchandise exports are estimated to have expanded by 13.2 percent in 2018—below the 21.8 percent recorded in 2017, but significantly outperforming global trade growth. Merchandise import growth posted a stronger deceleration to 11.1 percent in 2018, compared with 21.9 percent in 2018, reflecting a slowdown in imports of investment and intermediate goods. Vibrant trade activity has positioned Vietnam as one of the most open economies in the world, with its trade to GDP ratio reaching nearly 200 percent for the year. Strong exports also helped Vietnam to sustain a current account surplus for an eighth consecutive year. Vietnam’s capital account surplus also remains sizeable owing to sustained high FDI inflows. Robust external positions eased foreign exchange pressures, and helped the SBV build up international reserves, which increased from the equivalent of 2.1 months of import cover at end-2015 to about 2.8 months at end-2018. Bolstered by strong external positions, the exchange rate has been relatively stable since mid-2018. However, there remain concerns about real exchange rate appreciation of the dong, and its possible negative impacts on Vietnam’s export competitiveness. Vietnam’s fiscal stance has improved, with the overall fiscal deficit estimated to have narrowed to 4 percent of GDP in 2018 from 4.3 percent in 2017 and 4.9 percent in 2016. Total revenues are estimated to have remained at 23.6 percent of GDP in 2018—about the shares reported in 2016 and 2017—supported by a cyclical recovery in major tax revenues tied to strong consumption and income growth. Over the same period, total expenditures have declined to an estimated 27.6 percent of GDP in 2018 from 28.5 percent in 2016 and 27.8 percent in 2017, to a large extent reflecting lower capital expenditures and rationalization of other discretionary spending items. These measures, while effective in the short term, could hamper needed investments for infrastructure and human capital development. The Government’s commitment to

PART III. COUNTRY SUMMARIES AND KEY INDICATORS: Vietnam

strengthen budgetary discipline, therefore, needs to be balanced with reforms that create fiscal space to maintain critical investments in infrastructure and spending on essential public services.

Outlook The baseline outlook is positive on balance. Growth is projected to moderate to 6.6 percent in 2019, driven by credit tightening, slower private consumption and weaker external demand. Inflationary pressures are projected to remain moderate, due to subdued global demand conditions and moderate global energy and food prices. Over medium term, growth is projected to stay around 6.5 percent, as the impact of current cyclical uptick dissipates. Poverty is expected to decline further, as labor market conditions remain favorable.

Risks and Challenges Despite improved short-term prospects, there are significant downside risks. Domestically, a slowdown in the restructuring of SOEs and banking sector could adversely impact the macro-financial situation, undermine growth prospects, and create public sector liabilities. A continued slowdown of public investment could undermine long-term development objectives, and further fiscal consolidation should focus on containing recurrent spending while stabilizing revenue performance. Vietnam’s economy also remains susceptible to further volatile developments in the global economy, given its high trade openness and relatively limited fiscal and monetary policy buffers. Weaker external demand and heightened global financial volatility call for a continued focus on sound macroeconomic management to safeguard against possible shocks. Growth is also spatially uneven, which may see regional disparities continue to widen.

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EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019

Figure 1. Real GDP growth, contribution to real growth

Figure 2. Actual and projected poverty rates and real GDP per capita

Percent, percentage points

Poverty rate, percent

10

60

8

50

6

40

4

30

2

20

0

10

-2

0

GDP per capita, constant VND, million 50

40

30

JJGross capital formation

JJGovernment consumption

JJNet exports of GNFS

▬▬GDP growth

JJHousehold consumption

Sources: Official data and World Bank staff estimates.

VIETNAM S elected Indicators Real GDP growth, at constant market prices Private Consumption Government Consumption Gross Fixed Capital Investment Exports, Goods and Services Imports, Goods and Services Real GDP growth, at constant factor prices Agriculture Industry Services Inflation (Consumer Price Index) Current Account Balance (% of GDP) Fiscal Balance (% of GDP) Debt (% of GDP) Primary Balance (% of GDP) International poverty rate ($1.9 in 2011 PPP)a,b Lower middle-income poverty rate ($3.2 in 2011 PPP)a,b Upper middle-income poverty rate ($5.5 in 2011 PPP)a,b

10

20 20

18 20

16 20

14 20

12 20

10

0

20

20 21 f

20 20 f

20 19 f

20 18 e

20 17

20 16

20 15

20 14

20

▬▬International poverty rate

▬▬Lower middle-income poverty rate

▬▬Upper middle-income poverty rate

▬▬Real GDP per capita

Sources: Official data and World Bank staff estimates.

2016

2017

2018e

2019f

2020f

2021f

6.2 7.3 7.5 9.9 13.9 15.3 6.2 1.4 7.6 7.0 3.2 2.9 -4.9 60.0 -2.8 2.0 8.4 29.0

6.8 7.4 4.9 9.4 14.9 15.3 6.7 2.8 8.0 7.1 3.5 2.8 -4.3 58.6 -2.3 1.7 7.1 25.8

7.1 7.3 4.7 8.3 14.5 14.3 7.1 3.5 8.5 7.2 3.5 2.9 -4.0 57.6 -2.1 1.4 5.9 22.9

6.6 7.2 5.8 8.4 14.1 14.2 6.6 2.5 8.0 6.9 4.0 2.4 -3.9 57.2 -2.0 1.2 5.0 20.4

6.5 7.2 6.0 8.0 14.0 14.1 6.5 2.0 8.0 6.7 4.0 2.2 -3.9 57.0 -1.9 1.0 4.3 18.3

6.5 7.2 6.0 8.0 14.0 14.1 6.5 2.0 8.0 6.7 4.0 1.9 -3.9 56.9 -1.8 0.8 3.6 16.4

Source: World Bank, Poverty & Equity and Macroeconomics, Trade & Investment Global Practices. Notes: e = estimate, f = forecast. a) Calculations based on EAPPOV harmonization, using 2014-VHLSS and 2016-VHLSS. Actual data: 2016. Nowcast are from 2019 to 2021. b) Projection using annualized elasticity (2014–16) with pass-through = 1 based on GDP per capita in constant LCU.

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WORLD BANK EAST ASIA AND PACIFIC ECONOMIC UPDATE APRIL 2019