Stepping Up Skills in Urban Ghana by World Bank Group Publications

DIREC TIONS IN DE VELOPMENT

Human Development

Stepping Up Skills in Urban Ghana Snapshot of the STEP Skills Measurement Survey Peter Darvas, Marta Favara, and Tamara Arnold

Stepping Up Skills in Urban Ghana

Direc tions in De velopment Human Development

Stepping Up Skills in Urban Ghana Snapshot of the STEP Skills Measurement Survey Peter Darvas, Marta Favara, and Tamara Arnold

© 2017 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 20 19 18 17 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

This work is available under the Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO) http:// creativecommons.org/licenses/by/3.0/igo. Under the Creative Commons Attribution license, you are free to copy, distribute, transmit, and adapt this work, including for commercial purposes, under the following conditions: Attribution—Please cite the work as follows: Darvas, Peter, Marta Favara, and Tamara Arnold. 2017. Stepping Up Skills in Urban Ghana: Snapshot of the STEP Skills Measurement Survey. Directions in Development. Washington, DC: World Bank. doi:10.1596/978-1-4648-1012-1. License: Creative Commons Attribution CC BY 3.0 IGO Translations—If you create a translation of this work, please add the following disclaimer along with the attribution: This translation was not created by The World Bank and should not be considered an official World Bank translation. The World Bank shall not be liable for any content or error in this translation. Adaptations—If you create an adaptation of this work, please add the following disclaimer along with the attribution: This is an adaptation of an original work by The World Bank. Views and opinions expressed in the adaptation are the sole responsibility of the author or authors of the adaptation and are not endorsed by The World Bank. Third-party content—The World Bank does not necessarily own each component of the content contained within the work. The World Bank therefore does not warrant that the use of any thirdparty–owned individual component or part contained in the work will not infringe on the rights of those third parties. The risk of claims resulting from such infringement rests solely with you. If you wish to reuse a component of the work, it is your responsibility to determine whether permission is needed for that reuse and to obtain permission from the copyright owner. Examples of components can include, but are not limited to, tables, figures, or images. All queries on rights and licenses should be addressed to World Bank Publications, The World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; e-mail: pubrights@worldbank.org. ISBN (paper): 978-1-4648-1012-1 ISBN (electronic): 978-1-4648-1013-8 DOI: 10.1596/978-1-4648-1012-1 Cover photo: © Peter Darvas/World Bank. Used with permission. Further permission required for reuse. Cover design: Debra Naylor, Naylor Design, Inc. Library of Congress Cataloging-in-Publication Data has been requested.

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Contents

Foreword xi Acknowledgments xiii Overview xv Abbreviations xxv Chapter 1

Country Context 1 Economic, Social, and Demographic Trends 1 Education and Skills 3 Persistent Challenges in Education 4 Notes 6 References 6

Chapter 2

Conceptual Framework: Why Is It Important to Focus on Skills? 7 Introduction 7 Which Skills Are Relevant? 9 How Are Cognitive, Behavioral, and Technical Skills Formed? 10 Understanding the Focus on Adults and Urban Areas 11 Notes 12 References 12

Chapter 3

Skills Toward Employment and Productivity Data 13 Introduction 13 Data and Sample Characteristics 13 Types of Skills Measured 14 Methodology 18 Note 19 References 19

Chapter 4

Education Issues in Ghana Foundational Skills: Early Childhood Education Socioeconomic Disparities Constraints for Education: Late Entry, Completion Delay, and Dropouts

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The Gender Gap in Education 29 Reference 31 Chapter 5

Labor Market Participation 33 Introduction 33 Wage Employment, Self-Employment, and Formality 35 Occupation Type 37 Economic Sector of Occupation 37 Gender Disparities 40 Notes 42 Reference 42

Chapter 6

The Use of Cognitive Skills, Job-Specific Skills, 43 and Literacy Introduction 43 The Use of Cognitive Skills: Overall Use and Intensity of Use 43 Job-Relevant (or Task-Related) Skills 47 Socioemotional Skills 50 Reading Literacy Assessment 54 Developing Skills beyond Education: Training and Apprenticeships 65 Notes 67 References 68

Chapter 7

The Returns to Education and Skills: Building the Job-Relevant Skills That Employers Demand 69 Introduction 69 Returns to Education and Skills 70 Returns to Education: Is There a Gender Premium? 74 Notes 76 References 76

Chapter 8

Mismatch of Skills: A Measurement Issue and Unexploited Potential at Work Mismatch between Self-Reported Skills and Core Literacy Test Results: Does Language Matter? Are There Unexploited Skills in the Workforce? Conclusions and Looking Forward

77 77 78 79

Appendix A

Summary of Statistics

Appendix B

Skills Definitions, Survey Questions, and Aggregation Strategy

Definitions of Variables Used in the Analysis

Appendix C

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Appendix D Differences in Mean

Appendix E

Returns to Education and Skills

103

Appendix F

Mismatch of Skills and Unexploited Potential Tables

131

Appendix G Effect of Socioemotional Skills on Education and Labor Outcomes

145

Boxes 1.1 2.1 4.1 5.1 6.1

The Ghanaian Education System Skills Toward Employment and Productivity Definitions of Education Variables Definitions of Labor Market Terms Used in the Skills Toward Employment and Productivity Survey What Does It Mean to Pass the Core Literacy Test?

3 8 25 34 55

Figures 1.1 B2.1.1 2.1 3.1 3.2 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 4.10 4.11 4.12 4.13 4.14 5.1

Net Migration Rate, by Region 2 The Skills Toward Employment and Productivity Framework 9 Skills Classification 10 The STEP Household Survey Instrument 14 Workflow for the STEP Skills Measurement Survey 16 Participation in Early Childhood Education in Ghana 22 Regular Use of Reading, Writing, Numeracy, and Computer Skills in Ghana 22 Intensity of Skill Use in Ghana 23 Educational Attainment in Ghana 23 Educational Level in Ghana, by Age Groups 24 Regional Disparities in Changes in the Primary Completion Rate 26 Education Level Attained in Ghana, by Socioeconomic Status 26 Evolution of Educational Profile in Ghana, by Socioeconomic Status 27 Delay in the Official Age of School Entry and Graduation 28 Dropped Out of Highest Educational Level Started, by Maximum Level of Education Completed and Socioeconomic Status 28 Main Reason for Dropping Out 29 Educational Attainment, by Gender 30 Educational Composition: Is the Gender Gap Narrowing? 30 The Gender Gap in Educational Attainment (Male–Female), by Age Group 31 Labor Force Participation and Nonparticipation in Ghana 34

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5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 5.10 5.11 5.12 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9 6.10 6.11

6.12 B6.1.1 B6.1.2 B6.1.3 B6.1.4 6.13 6.14 6.15 6.16 6.17 6.18

Labor Status, by Educational Level The (Slow) Transition from School to Work: Labor Status, by Age Group Employment Status, by Age Group Employment Status, by Education Level Type of Occupation, by Employment Status Type of Occupation, by Education Level Type of Occupation, by Economic Sector Characterizing Each Economic Sector by the Education Level of Its Labor Force How People with Different Levels of Education Are Distributed across Economic Sectors Employment Status, by Marital Status Labor Status, by Gender and Age Group The Use of Cognitive Skills, by Level of Education Completed The Use of Cognitive Skills, by Level of Education Completed and Age The Intensity of Use of Reading Skills, by Education Level The Intensity of Use of Writing Skills, by Education Level The Use of Cognitive Skills at Work, by Employment Status The Use of Cognitive Skills at Work, by Economic Sector Job-Relevant Skills, by Employment Status Average Score of Personality Traits and Grit Average Scores for Hostile Bias and Time and Risk Preferences Coefficients of Socioemotional Skills on Years of Education, Controlling for Sociodemographic Characteristics Coefficients of Socioemotional Skills on the Probability of Attaining at Least SHS Education, Controlling for Sociodemographic Characteristics Coefficients of Socioemotional Skills on the Probability of Selected Labor Market Outcomes Main Language Spoken at Home and Work Self-Reported Ability to Speak and Read/Write in English at Work Performance in the Core Literacy Test According to Self- Reported Ability to Speak and Read/Write in English Did the Lack of English Keep You from Getting a Job? Distribution of Reading Component and Core Literacy Test Respondents Performance on the Reading Component Performance According to the Self-Reported Use of Reading and Writing Skills Performance According to Age Group and Education Level Core Literacy Test Performance Performance on Literacy Exercise Booklets: Proficiency Levels

35 36 36 37 38 38 39 39 40 41 41 44 44 46 47 48 48 49 50 51 52

52 53 55 56 56 57 58 59 59 60 61 63

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6.19

6.20

6.21 6.22 6.23 6.24 6.25 7.1 7.2 7.3 7.4 7.5

Distribution of Core Literacy Test Results, by Proficiency Levels Achieved on Literacy Exercise Booklets 63 Literacy Level According to Gender, Education Level, Age Group, Reading Intensity, Labor Status, and Employment Status 64 Differences in Proficiency Levels, by Self-Reported Reading Intensity 64 Certificate, Training, and Apprenticeship, by Education Level and Age Group 65 Are Students Choosing Apprenticeship Instead of Formal Education? 66 Certificate, Training, and Apprenticeship, by Employment Status 66 Certificate, Training, and Apprenticeship, by Occupation and 67 Economic Sector Returns to Education 70 Returns to Education, by Type of Employment 71 Level of Education, by Employment Status 73 Linear Probability Model of Being Self-Employed 74 The Returns to Education 75

Tables 3.1 3.2 A.1 A.2 A.3 D.1 D.2 D.3 D.4 D.5 E.1 E.2

Definitions of Skill Types Levels of Reading Proficiency Summary of Statistics from the STEP Survey Sampling Procedure Comparison of STEP, GLSS 5, and GLSS 6 Regional PSU Sample Size Comparison of STEP, GLSS 5, and GLSS 6 Difference in Mean of Those Passing the Core Literacy Test Threshold and Those Failing the Core Difference in Mean of Those Passing the Core Literacy Test Threshold and Those English Illiterate Difference in Mean of Those Answering Core Literacy Test and Those Who Did Not Answer It Difference in Mean of Those Missing and Those English Illiterate Difference in Mean of Those Answering the Socioemotional Section and Those Who Did Not Returns to Years of Education (Mincer Equation), Controlling for Skills Returns to Education Level (Mincer Equation), Controlling for Skills

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E.3 E.4 E.5 E.6 E.7 E.8 E.9 E.10 E.11 F.1 F.2 F.3 F.4 F.5 G.1 G.2 G.3 G.4 G.5

Returns to Years of Education (Mincer Equation) for Informal Wageworkers, Controlling for Skills Returns to Education Level (Mincer Equation) for Informal Wageworkers, Controlling for Skills Returns to Years of Education (Mincer Equation) for Formal Wageworkers, Controlling for Skills Returns to Education Level (Mincer Equation) for Formal Wageworkers, Controlling for Skills Returns to Years of Education (Mincer Equation) for Male Workers, Controlling for Skills Returns to Education Level (Mincer Equation) for Male Workers, Controlling for Skills Returns to Years of Education (Mincer Equation) for Female Workers, Controlling for Skills Returns to Education Level (Mincer Equation) for Female Workers, Controlling for Skills Linear Probability Model of Self-Employment, Controlling for Skills Difference in Mean of Self-Reported Readers Who Passed and Who Failed the Reading Assessment Core Literacy Test Unexploited Potential: Reading Skill Unexploited Potential: Writing Skill Unexploited Potential: Numeracy Skill Unexploited Potential: Computer Skill Years of Education, Controlling for Socioemotional Skills Linear Probability Model of Completing SHS or Tertiary Education, Controlling for Socioemotional Skills Linear Probability Model of Being Employed, Controlling for Socioemotional Skills Linear Probability Model of Being Self-Employed, Controlling for Socioemotional Skills Linear Probability Model of Working in a Medium- to HighSkilled Occupation, Controlling for Socioemotional Skills

108 110 112 115 117 119 122 124 127 131 134 136 139 142 145 146 147 149 150

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Foreword

The past two decades in Ghana have been marked by steady economic progress, which has transformed the country into a lower-middle-income economy, accompanied by a decline in poverty, increases in incomes for families, improvements in health, and expanded educational opportunities. As Ghana looks forward to a future of economic growth, it needs to regain growth from the 2016 slowdown, including improving competitiveness and economic diversification and raising labor productivity. A well-equipped workforce will be key to obtaining these goals. The Government of Ghana and its development partners such as the World Bank have long recognized the importance of investments in human capital. Insufficient skills in young people will be an obstacle to improving competitiveness in all sectors across the economy, be they informal or formal, in traditional sectors or in the modern areas such as information and telecommunications technologies. An agenda for improving skills in the workforce relies on being able to identify where the more practical and profitable investments in the current skills profile should be made. To that end, Skills Toward Employment and Productivity (STEP) is an innovative tool used across the world to assess the education, cognitive, work-related, and socioemotional skills stock in a population, as well as the impact of these traits on employment and earnings. Ghana is among the first two countries (along with Kenya) in Sub-Saharan Africa where this systematic assessment of skills has been carried out. The evidence collected through this assessment shows that the multidimensional nature of skills requires nurturing from early childhood education to school and university systems, as well as through school-based and on-the-job training. This broad concept of skills has a significant impact both on jobs and on earnings, and the relationship is also mutual: jobs attract and reward skills. The information from the Stepping Up Skills in Urban Ghana study provides detailed insights for policy makers. These insights cover areas including investments in early childhood education, the role of improvements in the quality of education, and the creation of incentives for economic actors to invest in on-the-job training to improve Ghana’s competitiveness and the well-being of its citizens. Henry Kerali Country Director for Ghana The World Bank

Jaime Saavedra Chanduvi Senior Director, Education Global Practice The World Bank

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Acknowledgments

The authors thank Henry Kerali, World Bank Country Director for Ghana; Jaime Saavedra Chanduvi, Senior Director; Amit Dar, Director; Luis Benveniste, Director; and Peter Nicolas Materu, Meskerem Mulatu, and Halil Dundar, Managers of the World Bank Education Global Practice, for their overall leadership and management guidance. We would also like to thank Alexandria Valerio, Kathleen Beegle, Maria Laure Sanchez Puerta, and Omar Arias for peer reviews and technical guidance. The team also received valuable advice from Deborah Mikesell and Eunice Ackwerh. The survey work was carried out by a team of the Institute for Social Statistical and Economic Research of the University of Ghana, led by Frank Ochere. The literacy assessment was completed with technical support by the Educational Testing Service (Princeton, New Jersey). Technical support to data management was provided by Tania M. Rajadel and Sebastian Monroy Taborda, both at the World Bank. Financial support was provided by the Multi-Donor Education Trust Fund and the Bank-Netherlands Partnership Support Program, both managed by the World Bank. Editing and publishing support were provided by Jonathan Faull and Aziz Gökdemir. Janet Adebo provided invaluable administrative support throughout the process.

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Introduction Ghana stands at the cusp of extraordinary opportunity. Since the country’s return to democratic rule and the advent of the Fourth Republic, per capita gross domestic product (GDP, current US$, PPP [purchasing power parity]) has increased almost fourfold, from US$375 in 1993 to US$1,442 in 2014. In 2011, Ghana was the only African economy to demonstrate double-digit economic growth, surpassing 14 percent that year. In the aftermath of the Chinese economic slowdown and the slump in global commodities markets, Ghana’s growth tempered to 4 percent in 2014 but is expected to recover above 8 percent in the medium term as the country begins exploiting significant oil and gas resources. Throughout the period of the Fourth Republic, fertility rates have remained relatively high, falling from 5.3 births per female in 1993 to 4.2 in 2014. Concurrently, the proportion of children under the age of 15 in the total population declined only marginally from 43 percent in 1993 to 39 percent in 2014. As a consequence, Ghana’s labor force has grown rapidly, from approximately 6.5 million in 1993 to 11.3 million in 2014, and is expected to continue to grow in the coming decades. Population growth has also contributed to an erosion of the effects of buoyant economic growth on poverty reduction. Although the country has made progress in reducing poverty—with the proportion of the population living below the government’s poverty line falling from 32 percent in 2005 to 24 percent in 2012—stubborn disparities persist with regard to access to economic, social, and political opportunities. Inequity is particularly evident in the differences between the populations of the poorer northern Savannah regions and the rest of the country. In the three northernmost administrative regions of the country, more than half, or

Unless stated, all statistics cited in the Introduction are drawn from the World Bank Group’s Data Bank, accessible at data.worldbank.org (accessed March 23, 2016). Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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58 percent, of the population falls below the poverty line, compared to 19 percent in the seven administrative districts of the south of the country. The spatial distribution of poverty and economic opportunity, in turn, has led to significant migration from north to south, and a swelling of the ranks of the urban labor force. Nevertheless, a significant economic dividend is implicit in Ghana’s increasingly abundant urban labor force. If current and future generations of workers can be empowered to realize their potential in a vibrant and increasingly competitive economy, the prospect of sustained poverty reduction, further economic development, and the reaping of benefits associated with a demographic transition could profoundly reshape Ghana’s society and economy for future generations. Equipping current and future generations of workers with the skills they need to improve their livelihoods and to drive increases in national productivity and competitiveness requires that these workers have skills appropriately aligned with the needs of a growing economy. Some skills are innate, arbitrarily assigned through the accident of birth. Other skills are acquired through education, work, and life experience. The primary means through which a government can develop the skills of its labor force is through policies and strategies implemented through the education system. Jobs form the foundation of economic development, rising living standards, increases in productivity, and improved social cohesion. Equipping people with appropriate skills to access meaningful work constitutes the means for achieving these objectives. This report, premised on the Skills Toward Employment and Productivity (STEP) framework, considers education the instrument for learning and acquiring skills and the key for accessing employment. Although the Ghanaian government has made significant progress in expanding access to basic education, many challenges persist in the education sector. These include the low quality of learning in both basic and post-basic education, inequity of access, and the limited capacity of the education system to equip beneficiaries with skills aligned with increasing competitiveness and productivity in the economy. If education and training institutions are unable to provide the skills demanded by the market, economic inefficiencies could be compounded. Skills development strategies can be effective only if they are appropriately calibrated to the needs of the economy and only if they take into account the current skills endowment of the existing labor force. The most effective skills development strategies are informed by evidence, and effective implementation requires the ongoing collection of data to gauge shifting demand for skills and the changing character of the labor force and economy at large. To date, evidence regarding the stock of existing skills in Ghana’s labor force is relatively underdeveloped. The precise measurement of the prevalence of different categories of skills within the population is required for the effective design of policy interventions that target improved training to reduce skill gaps

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Overview

aligned with the needs of specific sectors, improvement in productivity, and increased employability of workers. With the data it gathers, the first STEP household survey aims, in part, to address this deficiency through a rigorous analysis of the skills endowment of urban Ghanaian adults. The STEP survey was carried out between September 2011 and December 2013 in Ghana, as part of the first wave of surveys initiated under the STEP Skills Measurement Program. The Ghanaian sample consists of about 3,000 individuals between 15 and 64 years of age, living in urban areas across 71 districts. In addition to standardized information captured at the household level, the STEP survey collects information regarding the level of skill, level of education completed, and work history. On skills, the STEP survey includes information about (i) self-reported cognitive skills (that is, a subjective assessment of an individual’s use of foundation skills—reading, writing, and numeracy— at work and in daily life); (ii) assessed cognitive skills (that is, an objective assessment of reading literacy based on the International Adult Literacy Survey); (iii) socioemotional skills (that is, personality traits, behavior, and risk and time preferences); and (iv) job-specific skills (that is, an indirect assessment of skills used at work). The STEP framework is structured according to five iterative steps and associated objectives: (i) getting children off to the right start; (ii) ensuring that all students learn; (iii) building job-relevant skills; (iv) encouraging entrepreneurship and innovation; and (v) facilitating labor mobility and job matching. Ultimately, if these five steps are achieved, Ghana will significantly advance the likelihood of realizing the potential of its labor force, with considerable positive implications for the livelihoods of its people, poverty reduction, improved productivity, economic development, and the betterment of society at large.

Objectives This report is intended to complement and support the work of the Government of Ghana as it seeks to accelerate progress toward the achievement of the education-related Millennium Development Goals (MDGs) and the work of the Ministry of Education (MOE) and the Ghana Education Service (GES) in advancing the reforms envisaged by the Education Strategic Plan (ESP) for 2010–20. This report is divided into eight chapters: • Chapter 1 of the report describes Ghana’s economic, social, and demographic trends and the current challenges faced by the education system. Chapter 2 outlines the report’s framework for enquiry and a detailed description of the STEP framework. Chapter 3 provides an overview of the STEP survey’s sampling methodology, a description of methodologies used to measure each subset of skills, and limitations to the analysis.

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• Drawing on data collected through the STEP survey, chapter 4 describes the education profile of the urban adult population; explores trends in preschool, primary, secondary, and tertiary completion rates, disaggregated by age group, gender, and region; explores the effect of socioeconomic and demographic factors on educational attainment, dropout rates, and age of entry into the education system; and looks at the relationship between education attainment and inequality. • Chapter 5 analyzes labor force participation, employment status, and underemployment; the correlation between labor market status and skills and education; and regional disparities in education and labor market opportunity. • Chapter 6 focuses on the use of cognitive skills (both self-reported and assessed), socioemotional skills, and technical skills. The authors analyze the mismatch between self-reported and assessed cognitive skills and the mismatch between respondents who report high levels of education attainment but who performed poorly when these skills were tested and vice versa. This section of the report aims to answer the following research questions: How do socioemotional skills relate to cognitive skills? Does inequality with regard to years of schooling reflect inequality in cognitive skills? What are the characteristics of respondents who under- or over-report cognitive ability? Do incremental increases in educational achievement result in more developed skill sets? • Chapter 7 looks at the association between education and skills and labor market opportunity. It discusses the extent to which it is worthwhile for individuals to invest in (or for others to subsidize) education and/or skills development and to what extent these investments inform the development of skills demanded by the economy. In so doing, this chapter aims to answer the following research questions: Does education lead to better job market opportunities? Do skilled (educated) workers demonstrate higher earnings? Does education inculcate job-relevant skills? Which skills matter the most for employability? How much of the wage premium accruing to educated people is explained by skills? Is training relevant in producing good skills? • Section 8 quantifies the magnitude of unused skills and underexploited potential within the labor force, examines the proportion of the employed population who do not use their skills at work, and weighs evidence of skills and education mismatching in the labor market.

Key Findings The Educational Profile of Ghana’s Adult Urban Population Ghana has made significant progress in expanding access to basic education, having achieved near universal access to primary education. However, challenges persist with regard to improving the quality of basic education to enhance learning outcomes and to expanding access to post-basic levels of education. Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Overview

Moreover, a significant gender gap in educational achievement is evident for all levels of education in Ghana. The expansion of early childhood education (ECE) in Ghana’s urban areas has dramatically improved, and participation in ECE is positively correlated with household socioeconomic status and the intensity with which workers use basic skills. Only 30 percent of Ghanaians between ages 45 and 64 attended an ECE program compared to 87 percent of the youngest generation surveyed. Seventy-seven percent of adults living in households in the upper socioeconomic brackets had participated in an ECE program, compared to 49 percent of adults in the poorest households. Adults with ECE are more likely to read and write regularly and do so with greater intensity. Approximately two-thirds of students who complete primary school do so without demonstrating proficiency in core subject areas. In terms of the quality of senior high school (SHS) programs, a large disparity in further educational attainment is evident between students attending the highest-performing schools and the rest of the sector. The highest-performing 10 percent of high schools account for 90 percent of students entering university. There are significant regional, gender-based, and income-based disparities in access to and the returns accruing to post-basic education. Pass rates for the Basic Education Certificate Examination (BECE) vary greatly by region, with the poorest performance evident in the administrative regions of the north. The magnitude of difference in BECE pass rates for the north and south are upwards of 60 percent. Access to tertiary education has not changed substantially over time. Over three generations, the percentage of people with a tertiary qualification increased by only two percentage points, from 11 percent for adults ages 45 to 64 to 13 percent for respondents in the generation ages 25 to 34. A child’s age on entry to the school system is correlated with educational achievement. Officially, children should commence formal schooling at the age of six; however, in practice many children enter school later, with negative implications for further education. Approximately 51 percent of those with incomplete primary education enrolled in primary school at eight years of age, whereas 89 percent of those with postsecondary education enrolled at the official age of entry. Approximately one out of four members of the adult labor force dropped out of school prior to completing the highest grade of the level of education they had enrolled in, with the highest rates of dropout evident in the primary and junior high school (JHS) cycles of education. The most commonly cited reason for dropping out of school before the age of 16 is a lack of money for out-of-pocket expenses, regardless of the child’s socioeconomic status.

Labor Force Participation and Employment Status Characteristics The overall urban labor force participation rate in Ghana is 67 percent: 62 percent of respondents ages 15 to 64 years reported being employed, 5 percent reported being unemployed but looking for work, 23 percent were deemed Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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economically inactive (22 percent in education, 1 percent had retired), and 10 percent fell into the category “Not in Education, Employment, or Training” (NEET). A significant majority of the employed labor force works in the informal sector, primarily in self-employed work (66 percent) or as informal wage workers (20 percent). Only 15 percent of the employed population is engaged in salaried employment in the formal sector. However, these trends are changing, with younger generations less likely to be self-employed and more likely to hold salaried employment in formal or informal firms. Although female workers are as likely to be employed as their male counterparts, a significant gender gap exists in the quality of employment enjoyed by male and female workers. Across all age groups, female workers are more likely than male workers to be self-employed. Approximately half of male workers are self-employed, with the remaining share split almost evenly between formal and informal wage employment. By contrast, 79 percent of female workers are self-employed, and only 7 percent are retained as employees in the formal sector. A worker’s level of education is strongly associated with employment status. Approximately 37 percent of workers holding a tertiary qualification work in the informal sector (20 percent as self-employed and 17 percent as informal employees), compared to 99 percent of workers with no formal education (86 percent as self-employed and 13 percent as informal employees). A key determinant of a worker’s likelihood of accessing a job in the formal wage sector is education. Approximately 44 percent of workers in the formal sector have a tertiary education, 32 percent graduated from SHS, and 24 percent report JHS education or less. The level of educational attainment is also strongly associated with employment in higher-skilled occupations. The majority of the employed population works in low-skilled occupations in the informal sector, and just 13 percent of the working population is employed in high-skilled occupations, concentrated in the formal sector. SHS and tertiary graduates are more likely to be employed in mid- or high-skilled occupations than are workers with lower levels of educational attainment. Approximately 29 percent of SHS graduates are employed in the high-value-added services sector, compared to just 3 and 8 percent of workers in this sector having terminated their education following the primary and JHS cycles, respectively.

The Skills Profile of Ghana’s Adult Urban Population As mentioned previously, the STEP survey collects information about cognitive skills by asking people about their use of numeracy, reading, and writing skills and through an objective assessment of their reading proficiency. According to self-reporting by those surveyed, working-age Ghanaians use their numeracy skills on a regular basis, regardless of their level of education. At the same time, the use of reading and writing skills is significantly

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lower and strongly correlates with the level of education and with employment status. The intensity of the use of reading skills is higher among SHS graduates and highest for respondents with a tertiary qualification. All respondents who received tertiary education report using their reading and writing skills on a regular basis, and approximately 64 and 60 percent of the population with primary education report the regular use of reading and writing skills, respectively. Nevertheless, even among those who completed tertiary education, almost half write only with low intensity. Similarly, 84 percent of formal employees reported using their reading and writing skills on a daily basis, compared with approximately 41 percent of informal wageworkers and 21 percent of self-employed workers. Overall, the use of reading and writing skills has intensified over time, with the youngest cohort surveyed reporting regular use of their writing (89 percent of respondents) and reading (90 percent) skills, compared to the oldest age cohort of workers who reported a lower regular use of reading (41 percent of respondents) and writing (41 percent). The results of the reading proficiency tests mirror the respondents’ self-reported levels of skill use. Educational attainment was highly predictive of relative success on the Core Literacy Test component of the survey. Ninety-three percent of those who failed the test reported educational attainment of JHS or less (42 percent report no formal education, and 33 percent attended JHS), whereas about 57 percent of those who passed the test have at least an SHS education and approximately 21 percent report having tertiary education. Nevertheless, average performance across all three measures of reading is low. Respondents who reported using their reading and writing skills more frequently performed better in sentence processing and passage comprehension tests than those who did not. However, poor performance on the print vocabulary subcomponent of the reading assessment was relatively uniform across all subgroups. Respondents with higher reported levels of educational attainment performed better on all aspects of the reading component. Younger respondents were more likely to perform better in sentence and passage comprehension tests than older respondents. Respondents with lower socioeconomic status, and for whom English was not their main language at home or at work, were less likely to pass the Core Literacy Test. Of those who passed the test, 73 percent reported using English as their primary workplace language, compared with 17 percent of those who failed the test. However, in light of the fact that the reading test was administered in English, it is not surprising that a higher percentage of those who passed the test report speaking English as their primary language at home and work than those who failed. Of the respondents who were employed, 81 percent of those who failed the reading test were self-employed and only 3 percent were formal wageworkers. By contrast, 38 percent of those who passed the reading assessment were self-employed and 34 percent were formal wageworkers, with one-third retained in high-skilled occupations. Respondents who passed the reading

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assessment earned on average 274 GHS (approximately US$80) per month more than those who failed the test. Average performance on the Literacy Exercise Booklets section of the test, which allows for an in-depth analysis of reading ability, was very poor. Sixty-one percent of the subsample to whom the Literacy Exercise Booklets were administered scored on the lowest rung of proficiency. Respondents who attained higher scores were more likely to be younger, to have reported higher levels of educational attainment (SHS or tertiary), to work in the formal sector, to have reported the use of English as their primary home or workplace language, and to have reported using their reading and writing skills more intensively. Finally, it is worth mentioning that the data show a substantial mismatch between self-reported use of skills and tested literacy: of the sample as a whole, approximately 69 percent of adults reported reading regularly, but only 42 percent passed the Core Literacy Test component of the literacy assessment. However, the poor results in the Core test may reflect poor English literacy rather than present a true measurement of general reading skills. Those who reported being able to read but who then failed the Core test are more likely to be women, more likely to work in low-skilled occupations and to be less educated, and less likely to work in the high-value-added sector. Respondents who reported being able to read but then failed the Core test also earn approximately 41 percent less than those who reported being able to read and who passed the Core test. The analysis suggests that socioemotional skills are closely associated with educational attainment and labor market outcomes. Individuals with higher self-reported scores relative to the “Big Five” personality traits (stability, agreeableness, extraversion, conscientiousness, and openness) also had higher educational attainment. Similarly, individuals scoring higher on the Big Five personality traits, and who demonstrated lower levels of hostile bias, are less likely to be self-employed. The association between socioemotional skills and labor market outcomes is reversed nevertheless when controlling for education. This finding confirms that education and socioemotional skills are (positively) correlated and also suggests that the development of socioemotional skills might be one of the channels through which education can contribute to better labor market outcomes.

Job-Specific Skills Employment in the formal sector requires that a worker be capable of regularly learning new skills at work, more frequently involves the supervision of others’ work, and more often requires workers to make presentations. Survey data demonstrate that work in the informal sector is less cognitively demanding, more repetitive, and more physically demanding. Self-employed workers reported greater autonomy at work and a greater incidence of repetitive tasks than did wage workers. Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Further Education and Training Approximately 32 percent of the population surveyed had actively engaged in activities to further develop their skills in the year prior to taking the survey. More than one in four respondents surveyed by STEP reported participating in an apprenticeship, and less than 7 percent had participated in a training course of 30 hours or more. Apprenticeship-based training is more common among self-employed workers, whereas formal wageworkers are more likely to enroll in skills training courses. Approximately 26 percent of formal workers reported attending a work-related or personal skills training course in the year prior to the survey, compared to 3 and 6 percent of self-employed and informal wageworkers, respectively. On the other hand, approximately 38 percent of self-employed and 25 percent of wageworkers had participated in an apprenticeship in the 12 months prior to the survey.

Returns to Education and Skills The analysis demonstrates that an additional year of education is associated with an increase of 6–10 percent in monthly earnings. After controlling for socioeconomic characteristics, primary education is associated with no distinguishable earnings premium for people with no formal education or incomplete primary education. On the contrary, the wage premium accruing to SHS and tertiary graduates is 29–79 percent (SHS) and 112–172 percent (tertiary) higher than the average wage of workers with no formal education or incomplete primary education. The premium for workers with JHS over workers with no formal education or incomplete primary education is much lower (35–59 percent). Returns to education and skills vary by type of employment and with respect to the type of skill. An additional year of education increases the monthly earnings of informal wageworkers by 4–6 percent, compared to 7–10 percent for formal wageworkers. However, taking into account the individual’s skills (cognitive, socioemotional, and job-related skills), the earnings premium associated with any additional year of education decreases by 2 percent. The premium accruing to a female worker through an additional year of education is higher than that accruing to male workers (between 9 and 13 percent for female workers, compared to between 6 and 9 percent for men). For male workers, a pronounced premium associated with educational attainment becomes evident only at the tertiary level, whereas the data suggest that substantial payoffs accrue to female workers from JHS and above. Furthermore, with respect to skills, the pro-women gender gap is persistent at tertiary education (female workers with tertiary education make 164 percent more than those without compared to a 118 percent advantage for men). However, this apparent gender gap may be misleading because it does not take into account the fact that average labor market participation and educational attainments are lower for female workers. Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Evidence of an Unrealized Potential in the Labor Force An apparent mismatch between skills and their use at work could reflect unexploited human capital in the labor force. Within the overall population of employed adults, the evidence suggests that there is a subset of individuals who use their cognitive and computer skills at home but not at work. Moreover, there is a disproportionately large number of young workers who report being able to use a computer but who are not required to do so at work. The evidence suggests that the greatest residue of unexploited potential is located in lowskilled occupations and low-value-added sectors. Approximately 34 percent of self-employed workers report reading at home but never using this skill at work. On the other hand, only 6 percent of formal sector workers report this skills mismatch.

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Abbreviations

ALL BECE ECE ESP GDP GES GLSS V GSS IALS JHS MDG MOE NEET OECD PIAAC PPP SES SHS SSA STEP TVET WAEC WASSCE

Adult Literacy and Life Skills Survey Basic Education Certificate Examination early childhood education Education Strategic Plan gross domestic product Ghana Education Service Ghana Living Standards Survey (Fifth Round) Ghana Statistical Service International Adult Literacy Survey junior high school Millennium Development Goals Ministry of Education not in education, employment, or training Organisation for Economic Co-operation and Development Programme for the International Assessment of Adult Competencies purchasing power parity socioeconomic status senior high school Sub-Saharan Africa Skills Toward Employment and Productivity technical and vocational education and training West African Examinations Council West African SHS Certificate Examinations

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Country Context

Economic, Social, and Demographic Trends In the contemporary period, Ghana has achieved sustained economic growth and significant poverty reduction. The country has experienced 20 years of positive economic growth (in the range of 4–5 percent) and in 2011, with yearon-year growth of 14.4 percent, was one of only seven countries in the world, and the only country in Sub-Saharan Africa (SSA), to achieve double-digit economic growth (IMF 2012).1 Improved economic performance has been accompanied by significant poverty reduction, underpinned by rural development and increasing urbanization. In rural areas, small-scale agriculture has benefitted from improved agricultural productivity (notably in cocoa), rising incomes, and rising domestic demand. Concurrently, Ghana’s rapidly growing urban centers have led to a significant expansion of the service sector and a growing labor force, inclusive of migrants from rural areas who have been absorbed into better-paying jobs in both the formal and the informal sectors of the economy. Despite this impressive progress, deep inequity continues to characterize Ghanaian society and is reflected in significant disparities in access to economic, social, and political opportunities. This is especially evident when observing differences in access to opportunity between the populations of the poorer northern “Savannah regions” and the rest of the country. The bulk of Ghana’s poverty is concentrated in the three northernmost administrative regions of the country: the Upper East, Upper West, and Northern regions. These Savannah regions (home to approximately one quarter of the country’s population) are the locus of an average poverty rate of 58 percent, compared to 19 percent in the seven administrative districts in the south of the country. Between 1995 and 2005, the number of people living in poverty fell by 2.5 million in the south. Over the same period the number of people living in poverty in the north increased by 0.9 million, although the poverty rate for this area declined because of an absolute increase in the population.2

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Unemployment and underemployment in Ghana are structural in nature, which is not atypical in SSA. However, when demographic trends are taken into account, the structural nature of the challenges becomes more pronounced, with most economies on the continent being unable to generate sufficient rates of growth to create the jobs required to absorb the ever-increasing number of workers entering the labor force. The scale of the challenge is evident in the fact that formal private sector employment accounts for only a small proportion of available manpower. To sustain and accelerate economic growth and poverty reduction, Ghana’s education strategy is focused on building the skills profile of the youth demographic (IMF 2012). The urgent need to intervene in this regard is underlined by a national median age of approximately 20 years (UNDP 2011). Although the country’s youth demonstrate the highest levels of educational attainment relative to older generational cohorts, younger workers also depend most on salaried employment because of the inability of rural agriculture to sustain workers and their families and the contingent movement of migrants from the countryside to Ghana’s urban centers. From a developmental perspective, the most important demographic trend is the pace and character of migration from the northern regions of the country to the south (figure 1.1). Migrants to cities in search of jobs, education, skills, and business opportunities disproportionately include large family groups with children of school-going age and unemployed youth with poor educational attainment.

Figure 1.1 Net Migration Rate, by Region Upper West Upper East Northern Brong-Ahafo Ashanti Eastern Volta Greater Accra Central Western –400

–300

–200

–100

100

200

300

400

Number of migrants, in thousands Source: GSS 2013.

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Education and Skills Ghana has made significant progress in expanding access to basic education over the course of the past 15 years. Having achieved near universal access to primary education, the country now faces two new urgent challenges: (i) improving the quality of basic education to enhance learning outcomes and (ii) expanding access beyond basic levels of education. The majority of students receiving upper secondary education in Ghana are enrolled in three-year senior high schools (SHS), following the completion of 11 years of basic education (comprising preprimary school, primary school, and junior high school [JHS]) (see box 1.1 for more information on Ghana’s education system). The government intends to universalize access to upper secondary education by enabling students who are unable to afford fees to attend secondary school at no charge. Informal apprenticeships currently equip many more workers with skills than do formal public technical and vocational education and training (TVET) programs.3 Fewer than 10 percent of workers with technical and vocational skills acquired their skills through public TVET institutions. Moreover, there are approximately one and a half times as many trainees enrolled in private TVET institutions as in public institutions, and the number of students engaged in informal apprenticeships is 10 times that of students enrolled in the formal TVET sector.

Box 1.1 The Ghanaian Education System In theory, the age range for children and young people engaged in the Ghanaian education system spans from 3 to 21 years. The educational system in Ghana consists of the following cycles or levels of education: • Preschool, equivalent to U.S. kindergarten (ages 4–5) • Primary school (ages 6–11) • Junior high school (JHS), equivalent to U.S. middle school (ages 12–14) • Senior high school (SHS), equivalent to U.S. high school (ages 15–17) • Tertiary education/institution, equivalent to U.S. college/university (ages 18–21) A full cycle of basic education is optimally provided over the course of 11 years, comprising two years of kindergarten, six years of primary school, and three years of JHS. Ghanaian children enter class one (first grade) during the calendar year in which they reach their sixth birthdays. During the first three years, the medium of instruction is either English or a combination of English and local languages. JHS education comprises forms 1 through 3 (U.S. grades seven through nine). Admission to JHS is open to any student who has completed primary class six. There is no entrance exam, and JHS education is considered integral to the country’s nine-year cycle of basic education, to which all Ghanaian children are entitled. At the end of JHS form 3 (ninth grade), students sit box continues next page

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Box 1.1 The Ghanaian Education System (continued)

for the Basic Education Certificate Examination (BECE) in nine or ten subjects. The BECE is administered and graded by the West African Examinations Council (WAEC). Admission to SHS is based exclusively on a student’s BECE results. After JHS, students may choose to go into different streams within the SHS system or to pursue further skills acquisition through an apprenticeship scheme with some support from the government. All SHS courses prepare students for university education, but most TVET students are likely to join the labor market once they graduate. SHS consists of forms 4 through 6 (equivalent to U.S. grades 10 through 12). The core SHS curriculum comprises six subjects—English, science, mathematics, social studies, physical education, and religious and moral education—which are studied throughout the three-year SHS cycle. Students undergo examinations only in the first four of these subjects. To complete a full course of SHS education, each student must choose—in addition to the core curriculum— one program (general arts, general science, agriculture, economics, business, or technical and vocational) and three or four elective subjects from within that chosen program. At the end of the three-year SHS cycle, all students are required to sit the West African Senior School Certificate Examinations (WASSCE). Usually, the student’s overall score is determined by aggregating the student’s grades in his or her elective subjects and then adding this score to the aggregate score of the student’s best “core” subjects, with scores in English and mathematics considered first. The Ministry of Education considers any SHS graduate with an aggregate score of 24 (a D average) or better to be a successful school-leaver, equivalent to a graduate of a U.S. high school. Entrance to universities is by examination following the completion of SHS. Students obtaining aggregate scores of 36 or above (six subjects) on the WASSCE can enter university. After completing SHS, students also have the option to pursue further education through a polytechnic.

Persistent Challenges in Education Despite Ghana’s steady economic growth and improved access to basic education, many challenges persistent in the education sector. Among other things, the primary challenges concern • The poor quality of learning outcomes, in both basic and post-basic education; • Inequity of access, especially in secondary education; and • The limited capacity of the education system to create relevant skills aligned with increasing competitiveness and productivity within the economy. The National Education Assessment carried out biannually since 2005 shows a persistent trend: approximately two-thirds of students who complete primary school do so without demonstrating proficiency in core subject areas. In terms of the quality of SHS programs, the annual WASSCE demonstrates a large disparity in further educational attainment between students attending the 100 highestperforming schools and the rest of the sector. The highest-performing 10 percent Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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of high schools account for 90 percent of students entering university. Approximately 65–70 percent of SHS graduates do not continue education at the tertiary level. Students exiting the SHS cycle with low WASSCE scores are unable to access tertiary education, with many of these graduates going on to enroll in some form of training or apprenticeship program. There are significant regional, gender-based, and income-based disparities in access to, and the relevance of, post-basic education. The 2010 Population and Housing Census and the 2013 Ghana Living Standards Survey (GLSS) demonstrate very low pass rates for the BECE in the Upper East (11 percent), Volta (17 percent), and Northern and Upper West (both 22 percent) administrative regions, compared to high pass rates in the Greater Accra (90 percent), Western (88 percent), Brong-Ahafo (86 percent), and Ashanti (81.5 percent) regions (GSS 2013, 2014). Survey data also demonstrate that the limited capacity of Ghana’s education and training systems inhibits their ability to produce human capital of sufficient quality to meet the needs of the labor market and to drive a more competitive and diversified economy. Many JHS and SHS graduates are unable to find jobs in the formal sector, or are unable to pursue further education and training because of poor performance in exit examinations, a lack of information, and/or the suboptimal supply of training providers. Consequently, many JHS and SHS graduates are limited to self-employment or finding employment in the informal sector. According to data from the most recent National Census (2010), approximately two-thirds of the adult population is self-employed, and the proportion of employment accounted for by the formal private sector has declined since 2000 (GSS 2013). Formal (public or private) employment accounts for only 17 percent of total employment and is disproportionately concentrated in urban areas, although a relatively large minority of public employees—primarily teachers—are present in rural areas. Skills development in Ghana encompasses the inculcation of foundational, or basic, skills (literacy, numeracy); transferable and soft skills; and technical and vocational skills. These skills are acquired over the course of a lifetime through formal education, training, and higher education; through on-the-job and professional training; and through the family, community, and media. The majority of young Ghanaians acquire technical and vocational skills through informal onthe-job apprenticeships (Darvas and Palmer 2014). Although the scale and scope of Ghana’s TVET systems are difficult to measure, clear opportunities exist for further skills development at the intersection of education, youth, and the needs of the labor market (Darvas and Palmer 2014). Enterprise surveys demonstrate mixed perceptions on the part of firms with respect to the quality of workers’ skills and the extent to which poor skills act as a constraint to improved economic performance (Darvas and Palmer 2014). However, in light of the demonstrable inadequacy of the supply of relevant and quality skills to the economy, a more deliberate analysis of enterprise survey data is required to more effectively understand the underlying causes of the apparent low demand for skills. If strategies for the further development of Ghana’s Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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human capital and economic development are to be successful, it is imperative that skills development strategies are premised on a thorough understanding of the existing supply of and demand for skills, as well as of the use of skills in the economy, in order to more effectively match the supply of skills to demand (Campbell 2012; Darvas and Palmer 2014). Despite the central role skills play in shaping employment outcomes, there is very little information about the distribution of different types of skills in the Ghanaian labor force or of their contribution to labor market outcomes. Ultimately, the paucity of relevant information undermines the design of more effective skills development policies and programs (World Bank 2014). The Skills Toward Employment and Productivity (STEP) project—through its use of a framework enabling the analysis of Ghana’s labor market conditions based on internationally comparable skills data—will help to address this knowledge gap and assist in the development of policies aligned to the needs of the economy.

Notes 1. Real gross domestic product (GDP) growth was 8 percent in 2010, 4 percent in 2009, 8.4 percent in 2008, 6.5 percent in 2007, 6.1 percent in 2006, 6 percent in 2005, 5.3 percent in 2004, 5.1 percent in 2003, and 4.5 percent between 1993 and 2002 (IMF 2012b, 196; IMF 2011, 185). 2. Calculations based on the Ghana Living Standards Surveys GLSS3, GLSS4, GLSS5 available at http://documents.worldbank.org/curated/en/2011/03/14238095/tackling -poverty-northern-ghana. 3. This report uses the terms “technical and vocational education and training (TVET)” and “technical and vocational skills development” interchangeably.

References Campbell, M. 2012. “Skills for Prosperity? A Review of OECD and Partner Country Skill Strategies.” LLAKES Research Paper 39, University of London, United Kingdom. Darvas, P., and R. Palmer. 2014. Demand and Supply of Skills in Ghana: How Can Training Programs Improve Employment? Washington, DC: World Bank. GSS (Ghana Statistical Service). 2013. 2010 Population & Housing Census: National Analytical Report. Accra: GSS. ———. 2014. Ghana Living Standards Survey Round 6 (GLSS 6): Main Report. Accra: Ghana. IMF (International Monetary Fund). 2012. “Ghana: Poverty Reduction Strategy Paper.” IMF Country Report 12/203, IMF, Washington, DC. UNDP (United Nations Development Programme). 2011. Human Development Report 2011. Sustainability and Equity: A Better Future for All. New York: UNDP. World Bank. 2014. “STEP Skills Measurement Program.” World Bank, Washington, DC. http://microdata.worldbank.org/index.php/catalog/step/about.

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Chapter 2

Conceptual Framework: Why Is It Important to Focus on Skills?

Introduction It is generally recognized that there is a strong positive correlation between the educational and skills profile of the workforce and a country’s per capita gross domestic product (GDP)—which is intended here as a proxy of productivity. Thus, education and training are the foundations for a skilled workforce and would benefit not only individuals but also the economy as a whole. If the education and the training system are of low quality, however, workers will be ill-prepared for the labor market. This could lead to several types of mismatches. For example, the education level of an individual may not match his or her skills, or individuals may overrate their own skills, thus leading to a mismatch between self-reported skills and tested skills. In another type of mismatch, workers may lack the skills required for available jobs or lack access to high-quality training programs that would increase their skill level and enable them to apply for higher-productivity jobs. As a result, many employees are either under- or overqualified for their occupations. These mismatches lead to a loss of human capital and show that having post-basic or higher education does not automatically translate into getting a good job. In all of these cases of mismatch, investments in education may not pay off. Education policy makers and other education stakeholders in Ghana are paying more attention to learning outcomes by testing all students from early grades through basic and post-basic education. Various research and diagnostic work has highlighted the fact that the reading and mathematics proficiency of Ghana’s students continues to be below acceptable levels. This means that most of them are unable to reach important milestones in literacy, to access post-basic education, or to develop a foundation for lifelong learning. As a result, their employment prospects are limited. Policy makers have identified the low quality of inputs and the limited relevance of science and technology education as being

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Conceptual Framework: Why Is It Important to Focus on Skills?

among the main causes of these limited prospects. Policy makers also highlight Ghana’s large disparities in learning outcomes and related inequalities in the delivery of education services.1 Furthermore, policy makers and researchers have also homed in on several persistent challenges on the demand side. Not only do services and educational performance vary greatly by students’ social and economic status and by geography, but demand for skills, job opportunities, productivity, and expectations also vary widely and are affected by similar disparities. Despite the central role played by skills in improving employment outcomes and increasing productivity and growth in Ghana, information about the supply and demand of skills is sparse. Assessments of supply have largely focused on the outputs of mostly school and tertiary-level education and training institutions, whereas assessments of demand rely only on the responses to a few questions in enterprise surveys and rate-of-return analyses based on the last three Ghana Living Standard Surveys (GLSS) carried out in 1995, 1999, and 2005.2 Recently, more systemic analyses, surveys, and impact evaluations have been initiated, and we hope their results will inform future policy making. The lack of data and information on the skills endowment has made it difficult to design skills development policies and programs in Ghana, as in many other Sub-Saharan African (SSA) countries. Precise measurement of the prevalence of different types of skills among the population is needed to inform the design of public policies to reduce skill gaps in specific sectors, to increase the employability of the population, to improve training, and to enhance productivity. The Skills Toward Employment and Productivity (STEP) framework considers education as the instrument that enables individuals to learn and acquire skills, and subsequently access employment (box 2.1). Jobs are the foundation of economic development, improved standards of living, improved productivity,

Box 2.1 Skills Toward Employment and Productivity (STEP) The STEP framework (see figure B2.1.1) is informed by the following five interlinked steps: • Step 1. Getting children off to the right start—by developing the technical, cognitive, and behavioral skills conducive to high productivity and flexibility in the work environment through early child development (ECD), emphasizing nutrition, stimulation, and basic cognitive skills. Research shows that the handicaps built early in life are difficult if not impossible to remedy later in life and that effective ECD programs can have a very high payoff. • Step 2. Ensuring that all students learn—by building stronger systems with clear learning standards, good teachers, adequate resources, and a proper regulatory environment. Lessons from research and ground experience indicate that key decisions about education systems involve how much autonomy to allow and to whom, accountability from whom and for what, and how to assess performance and results. box continues next page

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Box 2.1 Skills Toward Employment and Productivity (STEP) (continued) Figure B2.1.1 The Skills Toward Employment and Productivity (STEP) Framework

Productivity and growth

Getting children off to the right start

Ensuring that all students learn

Building job-relevant skills

Encouraging entrepreneurship and innovation

Facilitating labor mobility and job matching

Source: Banerji et al. 2010.

• Step 3. Building job-relevant skills that employers demand—by developing the right incentive framework for both pre-employment and on-the-job training programs and institutions (including higher education). There is accumulating experience showing how public and private efforts can be combined to achieve more relevant and responsive training systems. • Step 4. Encouraging entrepreneurship and innovation—by creating an environment that encourages investments in knowledge and creativity. • Step 5. Matching the supply of skills with the demand—by moving toward more flexible, efficient, and secure labor markets. Avoiding rigid job protection regulations while strengthening income protection systems, complemented by efforts to provide information and intermediation services to workers and firms, is the final complementary step transforming skills into actual employment and productivity. Source: Banerji et al. 2010.

and social cohesion. As a consequence, equipping people with the right mix of skills is the means for achieving these objectives.

Which Skills Are Relevant? A worker’s skill set comprises different categories of skills, including cognitive skills, social and behavioral skills, and technical skills (see figure 2.1). These categories of skills relate to job skills relevant to specific occupations as well as to Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Conceptual Framework: Why Is It Important to Focus on Skills?

Figure 2.1 Skills Classification Cognitive

Social and Behavioral

Technical

Involving the use of logical, intuitive and creative thinking

Soft skills, social skills, life-skills, personality traits

Involving manual dexterity and the use of methods, materials, tools and instruments

Raw problem solving ability vs. knowledge to solve problems

Openness to experience, conscientiousness, extraversion, agreeability, emotional stability

Technical skills developed through vocational schooling or acquired on the job

Verbal ability, numeracy, problem solving, memory (working and long-term) and mental speed

Self-regulation, perseverance, decision making, interpersonal skills

Skills related to a specific occupation (e.g. engineer, economist, IT specialist, etc)

Source: Pierre et al. 2014.

cognitive ability and the various personality traits that inform relative success in the labor market (Pierre et al. 2014). Cognitive skills include the use of logic, intuition, and critical thinking, as well as problem-solving skills deployed using acquired knowledge. They also include literacy, numeracy, and the ability to understand complex ideas, to apply lessons accrued through experience, and to analyze problems using logical thought processes. Social and behavioral skills relate to personality traits that are linked to labor market success, such as an individual’s relative openness to new experiences, conscientiousness, extraversion, agreeability, and emotional stability. Technical skills range from manual dexterity in the use of complex tools and instruments to occupation-specific knowledge and skills for use in professional and technical occupations such as engineering or medicine.

How Are Cognitive, Behavioral, and Technical Skills Formed? The process of skills formation should be considered as a continuum spanning an individual’s life, with critical stages for the development of both cognitive and socioemotional skills. Four features of skills formation are particularly relevant to the development of a skills strategy: 1. Foundational cognitive and behavioral skills are formed early in an individual’s life and serve as a platform upon which other skills are developed. Children who fall behind early face significant disadvantages in catching up with their peers. Non-cognitive skills appear to be more malleable throughout life, but early interventions appear to have significant positive effects for their further development in the longer term. 2. Aggregate skills formation and development benefit from previous investments in skills development and are cumulative over an individual’s life. For example, a child who has learned to read fluently by second grade will be able Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Conceptual Framework: Why Is It Important to Focus on Skills?

to absorb more in third grade than a child of equivalent age who cannot read at the commencement of grade three. This implies that early investments in skills development are likely to have a greater longer-term impact on aggregate skills formation because it is easier and less costly to develop these skills when children are young and most receptive to learning. 3. Social and behavioral skills are particularly valuable early in a child’s life because they support, and benefit from, the development of cognitive skills. For example, children who are open to new experiences are more likely to be imaginative and creative and to apply themselves at school. 4. The acquisition of technical and job-specific skills is facilitated by strong cognitive and behavioral skills acquired earlier in the education system. These skills are often acquired last, through technical and vocational education and training (TVET), higher education, and on-the-job learning. The skills learned in formal education help workers to continuously update their technical skills during their working lives.

Understanding the Focus on Adults and Urban Areas Early investments are smart and cost-effective and prepare future generations of workers for the labor market. However, skills development strategies should also focus on maximizing the potential of current generations of workers. In recent decades Ghana has experienced large-scale migration from more rural and comparatively impoverished areas to Ghana’s more prosperous and urban areas. Migrants are disproportionately young adults who are motivated by educational opportunities and jobs in cities. Urbanization represents both a challenge and an opportunity for development because it has been associated with rising per capita income in Europe, Latin America, and, more recently, Asia. However, Africa has been an exception in this regard, because of the fact that in many African countries, including Ghana, industrialization has generally not accompanied urbanization. The majority of migrants to Ghana’s urban areas find employment in the comparatively poorly productive informal sector. However, even informal employment is, in many instances, much more than migrants could aspire to in their home regions. Equipping migrants with skills aligned with the needs of the urban labor market would give them a further opportunity for self-improvement. Accurately measuring the skills of the adult population is critical for informing policies aimed at increasing the productivity of those already in the labor force. Understanding the demographic structure and the socioeconomic status of the adult population in Ghana, as well as the associations between levels of education and an individual’s skills endowment, will help to inform the development of effective nonformal education and skills development programs aligned with the specific contextual characteristics of Ghanaian society and the labor force. It is for this reason that the STEP Skills Measurement Survey (discussed in the next chapter) is premised on gathering information about the skills endowment of the adult urban population. Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Notes 1. References on equity, demand and supply work, and other analyses include Balwanz and Darvas (2014) and Darvas and Palmer (2014). 2. The GLSS 6 survey results have just been released, and a later version of this report will also analyze these results (GSS 2014).

References Balwanz, David, and Peter Darvas. 2014. Basic Education beyond the Millenium Development Goals in Ghana: How Equity in Service Delivery Affects Educational and Learning Outcomes. Washington, DC: World Bank. Banerji, Arup, Wendy Cunningham, Ariel Fiszbein, Elizabeth King, Harry Patrinos, David Robalino, and Jee-Peng Tan. 2010. Stepping Up Skills for More Jobs and Higher Productivity. Washington, DC: World Bank. Darvas, Peter, and Robert Palmer. 2014. Demand and Supply of Skills in Ghana: How Can Training Programs Improve Employment? Washington, DC: World Bank. GSS (Ghana Statistical Service). 2014. Ghana Living Standards Survey Round 6 (GLSS 6): Main Report. Accra: Ghana. Pierre, Gaëlle, Maria Laura Sanchez Puerta, Alexandria Valerio, and Tania Rajadel. 2014. STEP Skills Measurement Surveys: Innovative Tools for Assessing Skills. Social Protection and Labor Discussion Paper 1421. Washington, DC: World Bank.

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Chapter 3

Skills Toward Employment and Productivity Data

Introduction The Skills Toward Employment and Productivity (STEP) survey provides a unique opportunity to collect information on the use of skills and skills proficiency in Ghana. The objective of the study is to yield a clearer understanding of the complex relationship between skills, employment, and productivity. This chapter discusses the characteristics of the sample used in the Ghana STEP survey, the data arising from the survey, and the definitions of skill and other variables used in this analysis.

Data and Sample Characteristics This household survey was carried out in Ghana as part of the first wave of surveys under the STEP Skills Measurement Program between September 2011 and December 2013. The Ghanaian sample was gathered through a two-stage random sampling of households and individuals. It consists of 2,987 individuals between 15 and 64 years of age. Table A.1 in appendix A provides a complete description of the sample in terms of demographic characteristics, education, language, labor and employment status, economic sector and occupation, and geographic region. It is important to note that the weighted sample represents only the urban population. Therefore, the findings of this report cannot be extended to the national level because the urban population is likely to differ from the rural population along many dimensions. For example, workers in the urban areas are likely to have higher education levels and to be relatively more concentrated in the services sector than workers in the rural areas. Along with the standard information captured at the household level, the STEP survey collects extensive information on the skills level, education, and work history of one individual between ages 15 and 64 randomly selected from

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Figure 3.1 The STEP Household Survey Instrument

Household information

Random selection of one HH respondent

PART A Household roster

Urban individual selected aged 15–64

Background

PART B Dwelling characteristics

Education pathways

PART C Identification of respondent

Health

Cognitive skills

Job-specific skills

Socioemotional skills

Self-reported Direct assessment (Basic or Extended Test)

Employment history Family background

Source: Banerji et al. 2010. Note: HH = household; STEP = Skills Toward Employment and Productivity.

each sampled household (figure 3.1). The survey includes three innovative modules on skills: (i) a specially designed assessment of reading literacy and competence to access, identify, integrate, interpret, and evaluate information, scored on the same scale as the test in the Program for the International Assessment of Adult Competencies (PIAAC) of the Organisation for Economic Co-operation and Development (OECD); (ii) a battery of questions capturing self-reported information on personality traits and behaviors; and (iii) a series of questions on job-specific skills that the respondent possesses or uses in his or her jobs. The skills of the entire sampled population are captured, irrespective of their labor force status (employed, unemployed, or inactive) or sector of employment.

Types of Skills Measured The STEP survey evaluates three categories of skill: (i) cognitive (self-reported and direct assessment); (ii) socioemotional skills; and (iii) job-specific skills. Table 3.1 and appendix B summarize the dimensions of skills captured in each category, and the corresponding survey questions used to create the relevant variables for analysis. Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Table 3.1 Definitions of Skill Types Skills type Cognitive

Definition The “ability to understand complex ideas, to adapt effectively to the environment, to learn from experience, to engage in various forms of reasoning, [and] to overcome obstacles by taking thought”a

Socioemotional skills

Related to traits covering multiple domains (social, emotional, personality, behaviors, attitudes, and so on)

Job-specific skills

Task related and build on a combination of cognitive and noncognitive skills

Measure Indirect assessment (selfreported) of individual’s use of foundation skills at work and in daily life Direct assessment of reading literacy based on the International Adult Literacy Survey (IALS) using the same scale as the Programme for the International Assessment of Adult Competencies (PIAAC) Personality traits

Skills Reading Writing Numeracy Reading proficiency

Openness Conscientiousness Extraversion Agreeableness Emotional stability Persistence Behavior Decision making Hostility bias Risk and time preferences Risk-taking preferences Time preferences Qualifications required for the job Qualification requirement for and job learning times current job Learning times Indirect assessment of skills used Autonomy and repetitiveness at job Computer use Contact with clients Solving and learning Supervision Physical tasks

Note: For further details, see appendix B and Pierre et al. 2014. a. Neisser et al. 1996.

Cognitive Skills The STEP survey measures cognitive skills in two ways: First, respondents are asked to report whether and with what intensity they use their reading, writing, and numeracy skills in daily life and at work (if they work). These measures are likely to capture a combination of an individual’s actual ability to conduct tasks involving these skills and their motivation or opportunity to do so. Second, the survey makes use of an objective literacy assessment to directly measure cognitive skills. The self-reported questions capturing the use of reading and writing skills may substantively differ from an individual’s actual ability to read or write. The STEP literacy test has been aligned with a series of large-scale international surveys, such as the International Adult Literacy Survey (IALS), the Adult Literacy and Life Skills Survey (ALL), and the PIAAC. The assessment consists of three parts: Reading Components, the Core Literacy Test, and the Literacy Exercise Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Booklets, as shown in figure 3.2. The Reading Components focus on foundational reading skills, including a respondent’s ability to assess word meaning, process sentences, and comprehend passages. The Core Literacy Test consists of eight literacy questions, which function as a screen to sort the least literate respondents from those with the highest literacy skills. Only respondents who were capable of answering two or more questions of the Core Literacy Test correctly are asked to complete the Literacy Exercise Booklets. The Booklets are broken down into four parts with a total of 18 questions, which allow for a more granular evaluation of reading skills among the relatively more literate respondents. All tests are conducted in English (see box 6.1 for further discussion). Cumulatively, the data gathered by the STEP survey consist of: (i) the Reading Components score(s),1 (ii) pass/fail information for the Core Literacy Test, and (iii) the score obtained in the Exercise Booklets grouped into five levels of competency (table 3.2), inclusive of descriptions of basic literacy skills from 1, the lowest level, to 5, the most advanced level.

Socioemotional Skills Socioemotional skills refer to skills and traits that are not directly related to intelligence, such as social, emotional, personality, behavioral, and attitudinal skills. The measures used to capture behavioral attributes are less established

Figure 3.2 Workflow for the STEP Skills Measurement Survey General booklet Section A. Reading components (10 min) (Part 1. Print vocabulary; Part 2. Sentence processing; and Part 3. Passage Comprehension Section B. 8 Core literacy items (7 min)

Fail core

Pass core

Exercise booklets 1, 2, 3 or 4 [18 Literacy items (28 min), random assignment] End of Module Source: Pierre et al. 2014.

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Table 3.2 Levels of Reading Proficiency Literacy Below Level 1 (0–175) The tasks at this level require the respondent to read brief texts on familiar topics in order to locate a single piece of specific information. Only a basic knowledge of vocabulary is required to complete these tasks, and the reader is not required to understand the structure of sentences or paragraphs or make use of other text features. There is seldom any competing information in the text, and the requested information is identical in form to information in the question or directive. Although the texts can be continuous, the information can be located as if the text were noncontinuous. Tasks below level 1 do not make use of any features specific to digital texts. Literacy Level 1 (176–225) Respondents are required to read relatively short digital or continuous print, noncontinuous print, or mixed texts to locate a single piece of information that is identical to, or synonymous with, the information given in the question or directive. Some tasks may require the respondent to enter personal information into a document, in the case of some noncontinuous texts. Little, if any, competing information is present. Some tasks may require simple processing of more than one piece of information. Tasks at level 1 require knowledge and skill in recognizing basic vocabulary, evaluating the meaning of sentences, and reading paragraph text. Literacy Level 2 (226–275) At this level the relative complexity of the text increases. Texts may be digital or printed, and may comprise continuous, noncontinuous, or mixed types of text. Competing pieces of information may be present. The completion of level 2 tasks requires respondents to match the text to information and may require the ability to paraphrase or make low-level inferences. Tasks require the respondent to • Cycle through or integrate two or more pieces of information against given criteria; • Compare, contrast, and/or reason about information requested in the question; or • Navigate within digital texts to access and identify information from various parts of a document. Literacy Level 3 (276–325) Texts at this level are comparatively dense and lengthy, and include continuous, noncontinuous, mixed, and/or multiple pages. Respondents must demonstrate an understanding of textual and rhetorical structures to successfully complete tasks, especially in the navigation of complex digital texts. Tasks require the respondent to identify, interpret, or evaluate one or more pieces of information, and often require varying levels of inference. Many tasks require the respondent to construct meaning across larger chunks of text, or perform multistep operations in order to identify and formulate responses. Tasks may also require that the respondent disregard irrelevant or inappropriate text to answer the question accurately. Competing information is present, but it is not more prominent than correct information. Literacy Level 4 (326–375) Tasks at this level require respondents to perform multiple-step operations to integrate, interpret, and/or synthesize information from complex or lengthy continuous, noncontinuous, mixed, or multiple-page texts. Complex inferences and the application of background knowledge may be needed to perform successfully. Many tasks require the identification and understanding of one or more specific, noncentral ideas in the text to interpret or evaluate subtle evidentiary claims or persuasive discursive relationships. Conditional information is frequently present in tasks at this level and must be taken into consideration by the respondent. Competing information is present and may be as prominent as correct information. Literacy Level 5 (376–500) At this level, tasks may require the respondent to search for and integrate information across multiple, dense texts; construct syntheses of similar and contrasting ideas or points of view; and/or evaluate evidence-based arguments. Application and evaluation of logical and conceptual models of thinking may be required to accomplish tasks. Evaluating the reliability of evidentiary sources and selecting key information is frequently a requirement to successfully complete tasks. Level 5 tasks require respondents to be aware of subtle, rhetorical cues, to make high-level inferences, and/or to use specialized background knowledge. Source: Adapted from Valerio et al. 2014. Note: Scores are out of a possible 500.

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than those used to measure cognitive skills, in part because of the absence of a consensus on the structure and evolution of personality. STEP builds on the “Big Five” personality traits (openness, conscientiousness, extraversion, agreeableness, and stability), a widely accepted taxonomy for capturing personality traits. This taxonomy has been found to be replicable across cultures and can be used to capture the evolution of a personality over an individual’s lifetime (John and Srivastava 1999). Measures of grit and hostility bias were also included. The survey of socioemotional skills includes a module aimed at assessing respondents’ time and risk preferences.

Job-Specific Skills Job-specific skills are task related and build on a combination of cognitive and noncognitive skills. The STEP survey asks individuals about specific tasks they perform and the skills that they use in their current job. Questions on job-specific skills are intended to capture an individual’s technical skills, reflecting his or her acquired knowledge in particular areas. Because technical skills are often specific to a certain discipline, they are difficult to capture using a survey instrument aimed at the general population. As a consequence, the STEP survey focuses on a range of skills relevant to performance in multiple jobs.

Methodology This report uses a combination of descriptive statistics, simple probability models (to estimate what determines the probability of acquiring education and skills and of finding employment), and the Mincer equation (to estimate the returns to education and skills). The descriptive analysis includes simple distributions of the use and intensity of use of skills across genders, age cohorts, different socioeconomic statuses, and regions. The estimation is done using the sample weights, and the results are representative for the urban population of Ghana. The returns to education are estimated using a Mincerian wage regression. The total log monthly earnings of the main and second occupation are estimated as a function of education and a number of control variables (as detailed in appendix C). The sample is restricted to those individuals with monthly earnings different from zero, and models are estimated using ordinary least squares (OLS) with robust standard errors. For all skills, dummies of nonresponse (missing variables) have been included in the regression. These models describe associations between earnings and education or skills but do not claim any causal relation. If a person with a college degree earns more than a person with lower education it does not necessarily mean that the college education is the cause of the difference in pay. Rather, the person who went to college might have some characteristics that make him or her more productive in the labor market, thus resulting in higher earnings. It is possible, for example, that high-ability people self-select themselves into college. Thus, higher productivity might be the result of this selection rather than the consequence of the education level achieved. Therefore, it is uncertain whether the education premium reﬂects Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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the returns to education or a higher market value of unobserved skills. In an attempt to alleviate this selection problem, the regression model included a broad set of controls. Nevertheless, there are many other observable and unobservable factors that might affect both the probability of being employed and of working in specific sectors and occupations and the returns to education.

Note 1. The scores for Reading Components will depend on whether there are sufficient data to report three subscales or just a single reading components score.

References Banerji, Arup, Wendy Cunningham, Ariel Fiszbein, Elizabeth King, Harry Patrinos, David Robalino, and Jee-Peng Tan. 2010. Stepping Up Skills for More Jobs and Higher Productivity. Washington, DC: World Bank. Carroll, J. B. 1993. Human Cognitive Abilities: A Survey of Factor-Analytic Studies. New York: Cambridge University Press. Cattell, R. B.1971. Abilities: Their Structure, Growth, and Action. Boston, MA: Houghton, Mifflin. Horn, J. L., and R. B. Cattell. 1967. “Age Differences in Fluid and Crystallized Intelligence.” Acta Psychologica 26: 107–29. John, O. P., and S. Srivastava. 1999. “The Big Five Trait Taxonomy: History, Measurement and Theoretical Perspectives.” In Handbook of Personality: Theory and Research, edited by L. A. Pervin and O. P. John. New York: Guilford Press. Neisser, U., G. Boodoo, T. J. Bouchard, Jr., A. W. Boykin, N. Brody, S. J. Ceci, D. F. Halpern, J. C. Lochlin, R. Perloff, R. J. Sternberg, and S. Urbina. 1996. “Intelligence: Knowns and Unknowns.” American Psychologist 51 (2): 77–101. Pierre, Gaëlle, Maria Laura Sanchez Puerta, Alexandria Valerio, and Tania Rajadel. 2014. STEP Skills Measurement Surveys: Innovative Tools for Assessing Skills. Social Protection and Labor Discussion Paper 1421. Washington, DC: World Bank. Valerio, Alexandria, Maria Laura Sanchez Puerta, Gaelle Pierre, Tania Rajadel, and Sebastian Monroy Taborda. 2014. STEP Skills Measurement Program: Snapshot 2014. Washington, DC: World Bank.

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Chapter 4

Education Issues in Ghana

Foundational Skills: Early Childhood Education Early childhood is a critical stage for long-lasting skills development. Investment in children between the time of birth and the beginning of primary education is a major determinant of their future school performance and labor market success. Various studies find a strong association between cognitive and socioemotional skills gained at a young age and school achievement, graduation rates, and employment outcomes. Provision of early childhood education (ECE) in Ghana has dramatically increased since 2000. Only 30 percent of Ghanaians between the ages of 45 and 64 attended an ECE program (kindergarten, crèche, day care, and/or nursery school) against 87 percent of the youngest generation ages 15–19 years old. Interestingly, there are no significant differences in ECE participation between males and females. Participation in preschool is positively correlated with household socioeconomic status. Seventy-seven percent of adults living in households in the upper socioeconomic brackets participated in an ECE program as compared to 49 percent of individuals from the poorest households (figure 4.1). This is consistent across all age cohorts. Adults who received ECE are more likely to read and write regularly. Adults who did not attend preschool programs report lower levels of reading and writing regularly (47 and 45 percent, respectively) compared with 82 and 77 percent of those who benefitted from ECE (figure 4.2). Almost all of the population reported using their numeracy skills on a daily basis. Figure 4.3 demonstrates that those who participated in ECE also use their reading, writing, and numeracy with more intensity. Only 27 percent of the adult population of Ghana uses a computer. A third of those who attended ECE programs use one, whereas only one in every ten adults who did not attend ECE uses one. Over time, access to primary and secondary education has substantially increased. In fact, most of the population has completed at least primary education (80 percent) and junior high school (JHS) (69 percent) (figure 4.4).

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Figure 4.1 Participation in Early Childhood Education in Ghana 100 90

Adults who received ECE (%)

80 70 60 50 40 30 20 10 0 15–19

20–24

25–34

35–44

45–64

Male

Female

Low SES

Middle SES

High SES

Note: The figure includes people currently attending school. ECE = early childhood e ducation; SES = socioeconomic status.

Figure 4.2 Regular Use of Reading, Writing, Numeracy, and Computer Skills in Ghana

Adults using skill regularly (%)

100

0 Did not attend ECE Reading

Attended ECE Writing

Numeracy

Computer

Note: The regular use of skills is defined on the basis of general questions about daily activities that involve the use of skills at work and outside work. The figure includes people currently attending school. ECE = early childhood education.

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Figure 4.3 Intensity of Skill Use in Ghana b. Writing

100

80 Percent

Percent

a. Reading

60 40 20

0 No ECE

ECE

No ECE d. Computer use

100

80 Percent

Percent

c. Numeracy

ECE

60 40 20

0 No ECE

No ECE

ECE High

Mid

Low

ECE

Not used

Note: Intensity of skill use is defined as follows: High = more than 25 pages a week; Medium = 6–25 pages; Low = 1–5 pages requiring the use of skills at work and outside work. The figure includes people currently attending school. ECE = early childhood education.

Adults with education level completed (%)

Figure 4.4 Educational Attainment in Ghana 100

0 None

ECE

Primary

JHS

SHS

Tertiary

Note: Attainment is the ratio of the population who complete a specific level of education to the population who could have finished this level of education (see box 4.1). The figure includes people currently attending school. ECE = early childhood education; JHS = junior high school; SHS = senior high school.

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Figure 4.5 Educational Level in Ghana, by Age Groups

Maximum level of education (%)

0 45–64

35–44 None

JHS

25–34 SHS

Primary

20–24 Tertiary

Note: The figure excludes those who are currently attending school. JHS = junior high school; SHS = senior high school.

In general, younger generations have more years of schooling than their elders. Whereas adults in the 45–64 age cohort have an average of 7.4 years of education, adults ages 20–24 have 2.6 more years of schooling. About 14 percent of adults ages 20–24 report not having completed primary education, but the equivalent figure was 31 percent among the oldest generation (ages 45–65) (figure 4.5). Also the proportion of adults who have completed senior high school (SHS) has increased substantially over time. About 37 percent of adults ages 20–24 have completed SHS against only 13 percent of the oldest generation. Tertiary education is also increasing but at a slower rate. In three generations the percentage of people with a tertiary education increased by only two percentage points, from 11 percent for the 45–64 age group to 13 percent among the 25–34 age group (figure 4.5). About 29 percent of the 20–24 age cohort is still attending tertiary education, and 5 percent have already graduated (see box 4.1 for a discussion of educational attainment and education levels).

Regional Disparities in Access to Primary Education Although primary education attainment among younger adults has increased in all regions, the increase, as measured in the Skills Toward Employment and Productivity (STEP) survey, was more significant in the Northern, Brong-Ahafo, and Volta regions. Nevertheless, it is worth remembering that, although similar trends are likely to have occurred in the Upper West and Upper East, the STEP Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Education Issues in Ghana

Box 4.1 Definitions of Education Variables The education variables include five subgroups of respondents: (i) those with no formal education or incomplete primary (henceforward called the “No education” or “None” subgroup); (ii) those with complete primary education; (iii) those who completed junior high school (JHS); (iv) those who completed senior high school (SHS); and (v) those who completed tertiary education. We define two variables for education: educational attainment and educational level. Educational attainment identifies the percentage of the population that has completed a specific education level whereas education level identifies the maximum level of education achieved. For example, someone whose education level is tertiary has attained primary, secondary, high school, and tertiary education. Thus, tertiary attainment is the ratio of those with tertiary-level education to all those who achieved (or are currently attending) a lower level of education. Notably, educational attainment is age independent. Indeed, at the denominator, it takes into account only those who, given their age, might have achieved the same level of education. Thus, for example, tertiary education attainment is the ratio of individuals at least 21 years of age having completed tertiary education to the same age-specific group with lower educational attainment. The age references for each educational level are defined as following: 11 years old and above for primary level, 14 years old and above for JHS, 17 years old and above for SHS, and 21 years old and above for tertiary level. Educational attainment is therefore useful for understanding the coverage of a specific education level within a population. For instance, if 80 percent of the population in a country has attained primary education, this includes those who have also achieved higher levels of education. In contrast, when analyzing educational level, the focus is on the highest level completed by the population. Educational level is useful for analyzing how the overall years of education completed by individuals might be correlated with their labor force participation, health, and life outcomes.

survey’s small sample of urban households made it impossible to measure them. In the Northern region the proportion of people who attained (or currently attend) primary education increased from 22 percent among adults ages 45–65 to 100 percent among the youngest population. Similarly, in Brong-Ahafo only 42 percent of the 45–64 cohort attained primary education compared to 96 percent of the youngest cohort. The Central region is the only region that is lagging behind, with only 83 percent of those 15–19 years old having attended primary education (figure 4.6).

Socioeconomic Disparities As might be expected, educational attainment increases with household wealth. More than 36 percent of individuals from the lowest quintile have not completed formal education compared with only about 19 percent of individuals from the highest income quintile (figure 4.7). Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Population completing primary education (%)

Figure 4.6 Regional Disparities in Changes in the Primary Completion Rate 100 90 80 70 60 50 40 30 20 10 0 Northern

BrongAhafo

Volta

Central

Eastern

15–19 year-olds

Ashanti

Western

Accra

45–64 year-olds

Note: The figure includes those who are currently attending school. Upper West and Upper East not reported because of their small sample size.

Figure 4.7 Education Level Attained in Ghana, by Socioeconomic Status 100

Urban adults (%)

80 60 40 20 0 Low SES

Middle SES Tertiary

SHS

JHS

High SES Primary

None

Note: The figure excludes those who are currently attending school and uses a subjective measure of socioeconomic status (SES) at age 15. JHS = junior high school; SHS = senior high school.

Nevertheless, Ghana is far from universal attainment in basic education, even among the urban population, and the education disparity is increasing. The richest segment of the population has been driving most of the improvement in education achievement—especially at the secondary level. Educational level has increased more quickly among the wealthiest, thus increasing the education gap between the poor and the wealthy (figure 4.8). Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Figure 4.8 Evolution of Educational Profile in Ghana, by Socioeconomic Status 120

Urban adults (%)

100 80 60 40 20

Bottom 20 percent Tertiary

4 –6 45

4 –4 35

4 –3 25

–2 20

–6 45

4 –4 35

4 –3 25

–2

Top 20 percent SHS

JHS

Primary

None

Note: The figure excludes those who are currently attending school and uses a subjective measure of socioeconomic status at age 15. JHS = junior high school; SHS = senior high school.

Constraints for Education: Late Entry, Completion Delay, and Dropouts Delaying school entry correlates to educational achievement. The average age for starting school for all Ghanaians is 7 years even though the official entry age is 6 years old. On average, those who completed a higher level of education began school around the official age of entry. About 51 percent of those who never complete primary education enroll in school at age 8, whereas 89 percent of those with a post-secondary education enrolled at the official entry age. Figure 4.9 shows the average age of school entry and completion for each level of education achieved compared with the official ages for entry and graduation. Although education attainment is increasing, delays in completion remain prevalent. Primary school should be completed by age 11, JHS by age 14, and SHS by age 17. However, those whose maximum level of education is primary graduate at an average age of 16.4. Considering their late entry, it takes them almost nine years to complete this level, four years more than expected (figure 4.9). For JHS and SHS, the difference between the actual and expected ages of graduation decreases, with the difference being about three years for both JHS and SHS. However, students are graduating from SHS at the age at which they should be finishing tertiary education instead. Tertiary education is the level with the highest delay in completion: although the expected age of completion is 21, the graduation age is on average almost six years later. Almost one out of four adults dropped out of school. The dropout rate is highest during primary education and JHS: among dropouts, 44 percent left school before completing primary education, 37 percent while attending JHS, 16 percent while attending SHS, and 4 percent during tertiary education. Among those starting primary education, 82 continue with a higher level of education; for 8 percent, primary education is their highest level of education, and 10 percent dropped out of primary education before completing it (figure 4.10, panel a). Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Tertiary

Figure 4.9 Delay in the Official Age of School Entry and Graduation

SHS

Tertiary

JHS

SHS

Primary None

Primary

Age of entry

JHS

Age of entry

Age of completion

Note: The figure excludes those who are currently attending school. The dash lines indicate the expected age of completion for each education level. JHS = junior high school; SHS = senior high school.

Figure 4.10 Dropped Out of Highest Educational Level Started, by Maximum Level of Education Completed and Socioeconomic Status a. Dropouts by maximum level of education completed

b. Dropouts by socioeconomic status

100

30 Dropouts (%)

Adults (%)

80 60 40

0 Primary

JHS

SHS

Tertiary

Low SES

Middle SES

High SES

Dropout Continued with education Highest level completed Note: The figure excludes those who are currently attending school. JHS = junior high school; SES = socioeconomic status; SHS = senior high school.

Among those starting JHS, 10 percent dropped out before completing this level; 9 percent of SHS students dropped out before completing SHS. Most of the dropouts belonged to households with low socioeconomic status when they were 15 years old. Whereas the dropout rate for individuals from the richest households is about 26 percent, this rate increases to 38 percent among the poorest households (figure 4.10, panel b). Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Figure 4.11 Main Reason for Dropping Out

Low SES

Money High opportunity cost Others Poor grades Unsafe Middle SES

Money High opportunity cost Others Poor grades Unsafe High SES

Money High opportunity cost Others Poor grades Unsafe 0

Percent citing this reason for dropping out Note: The figure excludes those who are currently attending school and uses a subjective measure of socioeconomic status (SES) at age 15.

The lack of money for out-of-pocket expenses is the top reason for dropping out at age 15 for all households, regardless of their socioeconomic status. Among the poorest households, which suffered the highest dropout rate, 66 percent mentioned lack of money for fees, uniforms, or school materials as a reason for dropping out (figure 4.11). High opportunity costs were the second most frequently mentioned reason. These high opportunity costs stemmed from the fact that students with lower qualifications might (relatively) easily find self- employment in the informal sector.

The Gender Gap in Education The gender gap in education attendance is significant for all levels of education in Ghana (figure 4.12). For example, at 26 percent, the proportion of female students completing SHS education is significantly lower than the completion rate of male SHS students, at 47 percent. Moreover, in primary education, 74 percent of female students enrolling in primary education complete a full course of primary education, compared to 88 percent for their male counterparts. The gender gap in the primary completion rate is still significant. Females make up a larger proportion of adults with no formal education. About 13 percent of men and 26 percent of women have no or an incomplete primary education. Nevertheless, women’s educational attainment at both the primary and secondary level is increasing over time (figures 4.13 and 4.14). Within the oldest generation, Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Education Issues in Ghana

Adults with education level completed (%)

Figure 4.12 Educational Attainment, by Gender 100

0 Male

Female

None

Primary

JHS

SHS

Tertiary

Note: Includes people currently attending school. For the definitions of the variables, see box 4.1. JHS = junior high school; SHS = senior high school.

Figure 4.13 Educational Composition: Is the Gender Gap Narrowing? 100

Urban adults (%)

0 Male

Female 20–24

Male

Female

Male

25–34 Tertiary

SHS

Female 35–44

JHS

Primary

Male

Female 45–64

None

Notes: The figure excludes those who are currently attending school and uses a subjective measure of socioeconomic status at age 15. JHS = junior high school; SHS = senior high school.

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Education Issues in Ghana

Figure 4.14 The Gender Gap in Educational Attainment (Male–Female), by Age Group

Difference in percentage points

30 20 10 0 –10 –20 –30 15–19

20–24 None

25–34 Primary

JHS

35–44 SHS

45–64

Tertiary

Note: The figure excludes those who are currently attending school.

41 percent of women have no formal education (compared with 18 percent of men), but this proportion is 23 percentage points lower among the youngest cohort. Similarly, only 8 percent of women ages 45–64 have SHS education against an SHS completion rate of 35 percent among the youngest. In sum, the STEP survey data show a clear trend of increases in education attainment across generations. Although driven mostly by deprived regions catching up with the rest of the country, these increases were also led by the highest-income groups. Despite improvements, inequality persists because lowerincome groups continue to have high opportunity costs.

Reference World Bank. 2014. “STEP Skills Measurement Program.” World Bank, Washington, DC. http://microdata.worldbank.org/index.php/catalog/step/about.

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Chapter 5

Labor Market Participation

Introduction Following the analysis of education attainment based on the Skills Toward Employment and Productivity (STEP) survey, we analyze the survey’s data on labor force participation and employment. The labor force participation rate in Ghana is 67 percent, with 62 percent reported to be working and only 5 percent to be unemployed (figure 5.1, panel a). About 23 percent of the population are inactive either because they are enrolled in school1 (22 percent) or because they are retired (1 percent). The remaining 10 percent are “Not in Education, Employment, or Training” (NEET) (see box 5.1 for definitions of various labor market terms). The most common reasons that respondents gave for being NEET were being a housewife, being unfit to work, or having been discouraged from working (figure 5.1, panel b). Unemployment rates are generally low, and inactivity varies very little across levels of education achieved. Unemployment is up to 6 percent for those with tertiary education, and the rate of NEET varies between 11 percent for people with no formal education and those with senior high school (SHS) education and 6 percent among tertiary graduates (figure 5.2). The transition from school to work is very slow. Individuals ages 35–44 have the highest employed rate. Whereas unemployment and NEET rates vary little across age groups, inactivity declines significantly (by about 28 percentage points) between the age 20–24 and 25–34 cohorts and falls by 7 additional percentage points for those ages 35–44 (figure 5.3). Although this trend might be explained by a change over time of the labor market structure, it also shows (together with the prevalence of late school entry and late completion) a slow transition from school to work.

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Labor Market Participation

Figure 5.1 Labor Force Participation and Nonparticipation in Ghana percent a. Labor force

b. Reason for being NEET Other

Inactive, 23

Looking for work In transition Pregnancy/ nursing Discouraged

NEET, 10

Unfit Housewife Employed, 62

Unemployed, 5

Reasons for NEET (%)

Note: NEET = Not in Employment, Education, or Training.

Box 5.1 Definitions of Labor Market Terms Used in the Skills Toward Employment and Productivity (STEP) Survey Ghana’s labor force includes people ages 15–64, both employed and unemployed (and those seeking a job). The employed labor force includes those working for pay, those who have found a job but are not working because they are sick or waiting to start their new job, those working for profit, and those in apprenticeships. The unemployed labor force includes those who are looking for job and who have been laid off for 30 days or less. The employment/unemployment rate can be computed as share of employed/unemployed people over the whole population aged 15–64 or over the labor force (which excludes the inactive population). The inactive population includes people enrolled in school and those who are “Not in Education, Employment, or Training,” or NEET. The NEET rate is defined as a share of NEET over the 15- to 64-year-old population, including both the active and inactive population. The inactive subgroup is ultimately broken down to distinguish between married and unmarried people. The underemployed are those working less than 40 hours a week (considering the primary and secondary occupations together) and willing to work more hours. Underemployment is defined both as a share of the active labor force and as a share of the employed labor force only. A further distinction is made between those employed in the formal sector and those working in the informal sector. The STEP survey defines informal sector workers as unpaid workers (mainly employed in family businesses), the self-employed and wageworkers who report not having any social security or benefits, or informal wageworkers. The rest of the employed population constitutes the formal sector, made up predominantly of wageworkers. box continues next page

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Box 5.1 Definitions of Labor Market Terms Used in the Skills Toward Employment and Productivity (STEP) Survey (continued)

Occupations are classified into three categories on the basis of the level of skills required. Low-skilled occupations include agricultural, forestry, and fishery workers; craft and related trades workers; plant and machine operators and assemblers; and elementary occupations. Mid-skilled occupations include technicians and associate professionals; clerical support workers; and service and sales workers. High-skilled occupations include managers and professionals. Finally, the economic sectors are classified in four groups: (i) agriculture, fisheries, and mining; (ii) manufacturing; (iii) low-to-mid-value-added services; and (iv) high-value-added services. The low-to-mid-value-added services sector includes electricity, gas, steam, and air conditioning supply; water supply and sewage; waste management; construction; the wholesale and retail trade; transportation and storage; accommodation and food services; information and communication; arts, entertainment, and recreation; other services activities; and the activities of households and extraterritorial organizations and bodies. The high-value-added services sector includes financial and insurance activities; real estate activities; professional, scientific, and technical activities; administrative and support service activities; public administration and social security; and education, human health, and social work activities.

Figure 5.2 Labor Status, by Educational Level 100

Urban adults (%)

80 60 40 20 0 None

Primary Inactive at school

JHS NEET

SHS Unemployed

Tertiary Employed

Note: The figure includes people currently studying but not inactive retired people. JHS = junior high school; NEET = Not in Education, Employment, or Training; SHS = senior high school.

Wage Employment, Self-Employment, and Formality Most of the employed labor force works in the informal sector, either as selfemployed (66 percent) or as informal wageworkers (20 percent).2 In fact, only 15 percent of the employed population works as salaried workers in the formal sector. However, this trend is changing: younger generations are less likely to be self-employed and more likely to be salaried workers, with either formal or Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Figure 5.3 The (Slow) Transition from School to Work: Labor Status, by Age Group 100 90 80

Percent

70 60 50 40 30 20 10 0 20–24

25–34 Inactive

35–44 NEET

Unemployed

45–64

Employed

Note: The figure includes people who are currently studying. NEET = Not in Education, Employment, or Training.

Figure 5.4 Employment Status, by Age Group

Maximum level of education (%)

100

0 45–64

35–44

25–34

20–24

Age group Self-employed

Formal employee

Informal employee

Note: The figure excludes people currently studying.

informal firms. Nevertheless, still more than 95 percent of the youngest age cohort (20- to 24-year-olds) work in the informal sector, most of them as informal wageworkers rather than self-employed (55 percent) (figure 5.4). Education is strongly associated with employment status, as shown in figure 5.5. About 37 percent of those with a tertiary education work in the informal sector (20 percent as self-employed and 17 percent as informal employees), and this Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Figure 5.5 Employment Status, by Education Level 100

Urban adults (%)

0 None

Primary Self-employed

JHS Informal employee

SHS

Tertiary

Formal employee

Note: The figure excludes people who are currently studying. JHS = junior high school; SHS = senior high school.

share increases to 99 percent for those who do not have any formal education (86 percent as self-employed and 13 percent as informal employees).

Occupation Type Informality is synonymous with low-skilled occupations. Only 13 percent of the employed population works in high-skilled occupations, mainly in the formal sector (figure 5.6). Conversely, the majority is employed in low-skilled (39 percent) and mid-skilled occupations (48 percent). The prevalence of workers employed in low- or mid-skilled occupations is relatively higher among the self-employed than among informal wageworkers. Increasing education leads to better occupations. Nevertheless, although this is true for SHS and/or tertiary graduates, those with primary education and those with no formal education are equally distributed among low-skilled or mid-skilled jobs (figure 5.7). Junior high school (JHS) graduates do slightly better, with about 2 percent more working in mid-skilled occupations and about 4 percentage points fewer in low-skilled occupations. The scenario changes for those with an SHS education, with 18 percent working in high-skilled occupations and only 32 percent in low-skilled occupations. The contrast in terms of high-skilled jobs is even more pronounced for those with a tertiary education, for whom the figure reaches 70 percent, with only 6 percent working in low-skilled occupations.

Economic Sector of Occupation The largest share of the employed population works in services (61 percent in low-to-mid-value-added services and 17 percent in high-value-added services). The smallest share works in manufacturing (about 10 percent), followed by Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Figure 5.6 Type of Occupation, by Employment Status 100

Urban adults (%)

80 60 40 20 0 Formal employee

Informal employee

High-skilled

Mid-skilled

Self-employed Low-skilled

Note: The figure excludes people currently studying.

Figure 5.7 Type of Occupation, by Education Level 120

Urban adults (%)

100 80 60 40 20 0 None

Primary High-skilled

JHS Mid-skilled

SHS

Tertiary

Low-skilled

Note: The figure excludes people currently studying. JHS = junior high school; SHS = senior high school.

11 percent in agriculture, fishery, and mining combined. Almost all of the occupations in the manufacturing sector and the agriculture, fishery, and mining sector are low-skilled occupations (figure 5.8). Education attainment increases in line with employment in higher-value economic sectors. Almost half of the workers in the agriculture, fishery, and mining sector have no formal education (53 percent) compared to 21 percent in the manufacturing sector and 28 percent in the low-to-mid-value-added services sector (figure 5.9). The education level of employees in the manufacturing sector is very similar to that of workers in the low-to-mid-value-added services sector. Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Labor Market Participation

Figure 5.8 Type of Occupation, by Economic Sector 100

Urban adults (%)

0 Agriculture fishing, and mining

Manufacturing

High-skilled

Low-to-midvalue added

Mid-skilled

High-valueadded

Low-skilled

Note: The figure excludes people currently studying.

Figure 5.9 Characterizing Each Economic Sector by the Education Level of Its Labor Force 120

Urban adults (%)

100 80 60 40 20 0 Agriculture fishing, and mining

Manufacturing

Tertiary

SHS

Low-to-midvalue added JHS

Primary

High-valueadded None

Note: The figure excludes people currently studying. JHS = junior high school; SHS = senior high school.

The pool of people with tertiary education is concentrated in the high-valueadded services sector (43 percent). Although completing primary education reduces the probability of working in agriculture, the picture for those with a primary education and those with a JHS education is again very similar (figure 5.10). Conversely, Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Figure 5.10 How People with Different Levels of Education Are Distributed across Economic Sectors 100

Urban adults (%)

80 60 40 20 0 None

Primary

High-value-added Low-to-mid-value-added

JHS

SHS

Tertiary

Manufacturing Agriculture, fishery, and mining

Note: The figure excludes people currently studying. JHS = junior high school; SHS = senior high school.

completing SHS makes a difference, given that about 29 percent of SHS graduates work in the high-value-added services sector compared with 3 and 8 percent for those with primary and JHS educations, respectively (figure 5.10). Nevertheless, 8 percent of SHS graduates still work in the low-to-mid-value-added services sector.

Gender Disparities On average, labor force participation is very similar for men and women. However, when distinguishing between married and unmarried men and women, we find a significant gender gap among those who are married. About 89 percent of married men are employed compared with about 77 percent of married women. Married women are more likely to be out of the labor force than men and more likely to be NEET in their capacity as housewives (see figure 5.11). The difference between the labor market status of males and females across age cohorts is not as significant as might be expected (see figure 5.12). Notably, the percentage of females who are NEET is highest for the 20–34 age group, which likely correlates to age-specific life events such as childbearing rather than a change over time in the women’s labor market status. Increasing access to childcare and flexible work options might help to expand labor market participation and opportunities for women. Although women are as likely as men to be employed, the gender gap is very pronounced in the quality of employment. At all ages, females are more likely to be self-employed than men. About half of the male working population is

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Labor Market Participation

Figure 5.11 Employment Status, by Marital Status 120 100

Percent

80 60 40 20 0 Male

Female

Male

Single

Female

Male

Female

Married

Inactive

NEET

All

Unemployed

Employed

Note: NEET = Not in Education, Employment, or Training.

Figure 5.12 Labor Status, by Gender and Age Group

Urban adults (%)

100 80 60 40 20

Male Inactive

4 –6

–4 35

4 –3 25

4 –2 20

9 –1 15

–6 4

–4 35

4 –3 25

4 –2 20

–1

Female NEET

Unemployed

Employed

Note: The figure includes people currently studying. NEET = Not in Education, Employment, or Training.

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Labor Market Participation

self-employed whereas the other half is almost evenly distributed between formal and informal employment. In contrast, 79 percent of females are selfemployed and only 7 percent are formal sector employees.

Notes 1. The inactive category also included a few part-time students (6 percent of the total population) who reported that they were studying and working at the same time. The NEET group also included those who reported being employed as unpaid family workers (3.5 percent of the total population). 2. Unpaid family work is not very common in Ghana, making up only 3.5 percent of the population. In this report, unpaid family workers are classified as NEET.

Reference World Bank. 2014. “STEP Skills Measurement Program.” World Bank, Washington, DC. http://microdata.worldbank.org/index.php/catalog/step/about.

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Chapter 6

The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Introduction To the extent that workers’ productivity depends on their skills and is reflected by their wages, individuals with more skills should expect higher returns from their labor market participation. Most studies investigate the returns to investments in human capital using the education qualification attained. Only a few recent studies examine the returns to skills (Leuven et al. 2004; Tyler 2004). The data arising from the Skills Toward Employment and Productivity (STEP) survey provide a unique opportunity to analyze skills across a range of dimensions and measure their implications for an individual’s well-being and relative opportunity in the labor market. As mentioned in chapter 3, the STEP survey focuses on three types of skills: (i) cognitive skills (self-reported and direct assessment); (ii) socioemotional skills; and (iii) job-specific skills. The following section will assess the distribution of each category of skill across population subgroups and thereafter proceed to an analysis of the returns to skills.

The Use of Cognitive Skills: Overall Use and Intensity of Use The use of cognitive skills refers to the overall use of reading, writing, and numeracy skills either in daily life or at work.1 Almost everybody uses numeracy skills regularly, at all levels of education. Conversely, the regular use of reading and writing skills is positively correlated with education. The large majority of survey respondents who attended tertiary education read and write regularly. This can be compared with the population with a primary education who reported using their reading (64 percent) and writing skills (60 percent) on a regular basis (figure 6.1).

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The Use of Cognitive Skills, Job-Specific Skills, and Literacy

The use of reading and writing skills has increased greatly over time, especially among people with low educational attainment. In fact, the highest disparity in the use of skills by age groups is among people who completed only primary education. In the youngest cohort with only primary education, 89 percent use their writing skills and 90 percent use their reading skills. However, less than half of the oldest age cohort uses them, with only 40 percent using their reading skills and 41 percent using their writing skills (figure 6.2). The intensity of the use of various skills is linked to the level of proficiency and increase with the level of education attained. Overall, 31 percent

Figure 6.1 The Use of Cognitive Skills, by Level of Education Completed 100 Adults using skill regulary (%)

90 80 70 60 50 40 30 20 10 0

None

Primary Reading

JHS Writing

SHS

Numeracy

Tertiary

Computer

Note: The figure includes those who are currently in school. JHS = junior high school; SHS = senior high school.

Figure 6.2 The Use of Cognitive Skills, by Level of Education Completed and Age a. No education

b. Primary 100 Those using skill (%)

Those using skill (%)

100 80 60 40 20 0 45–64 35–44 25–34 20–24 15–19

80 60 40 20 0 45–64 35–44 25–34 20–24 15–19 figure continues next page

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The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Figure 6.2 The Use of Cognitive Skills, by Level of Education Completed and Age (continued) d. Senior high school

c. Junior high school 100 Those using skill (%)

Those using skill (%)

100 80 60 40 20 0 45–64 35–44 25–34 20–24 15–19

80 60 40 20 0 45–64 35–44 25–34 20–24 15–19

e. Tertiary

Those using skill (%)

100 80 60 40 20 0 45–64 35–44 25–34 20–24 15–19 Numeracy

Reading

Writing

Computer

Note: The figure excludes those who are currently in school.

of the population reported not using their reading skills at all. Among the 69 percent using them regularly, half of the population read with low intensity, 24 percent read with medium intensity, and 29 percent read with high intensity. Among those with no formal education, 87 percent do not read at all, and 11 percent read only very short documents, whereas only 1 to 2 percent read intensively (figure 6.3). Reading intensity is higher among graduates of senior high school (SHS) and tertiary education. Nevertheless, there are still 40 percent of SHS and 19 percent of tertiary graduates who do not read or who do so rarely. With regard to writing skills, about 35 percent of the adult population reported not writing regularly. Furthermore, most people use their writing skills less regularly than their reading skills. As in the case of reading skills, the use of writing skills increases with education. Writing skills significantly improve for those completing primary education and for those completing SHS and tertiary education. Nevertheless, even among those who completed tertiary education, almost half write only with low intensity (figure 6.4). The use of skills is strongly related to employment status. Formal employment requires an intensive and frequent use of reading skills. More than 84 percent of Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Figure 6.3 The Intensity of Use of Reading Skills, by Education Level percent a. No education

b. Primary

Medium, 1 High, 1 Low, 11

High, 16

c. Junior high school Skill not used, 37

High, 17

Skill not used, 20

Medium, 16 Medium, 16 Skill not used, 87

Low, 31

d. Senior high school

High, 33

Low, 46 e. Tertiary

Skill not used, 5

High, 52

Low, 35

Low, 19

Medium, 30

Medium, 26 Note: The figure includes those currently in school. Percentages in some panels do not add up to 100 percent because figures were rounded up.

formal employees use their reading and writing skills on a daily basis compared with about 41 percent of informal employees and about 21 percent of the selfemployed (figure 6.5). Although the use of numeracy skills is almost universal within all employment groups, computer use is low across the entire workforce. More than one-third of formal wageworkers reported using their computer skills at work, whereas only 11 percent of informal wageworkers and less than 3 percent of the self-employed reported using them (figure 6.5). Finally, the percentage of workers who use reading and writing skills and computers is significantly higher among those who work in the high-value-added services sector than in any other sectors (figure 6.6).

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The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Figure 6.4 The Intensity of Use of Writing Skills, by Education Level percent a. No education

b. Primary

Medium, High, Low, 1 0 11

High, 8 Medium, 8

High, 10

Medium, 9

Skill not used, 88

c. Junior high school Skill not used, 26

Skill not used, 41

Low, 58

Low, 41

d. Senior high school

e. Tertiary

High, Skill not 10 used, Medium, 9 16

High, 20

Skill not used, 1

Medium, 28 Low, 51

Low, 64 Note: The figure includes those currently in school. Percentages in some panels do not add up to 100 percent because figures were rounded up.

Job-Relevant (or Task-Related) Skills Job-relevant skills are task related and consist of a combination of cognitive and socioemotional skills. The STEP survey includes information on whether employed people perform any of the following tasks at work: repairing and maintaining electronic equipment, operating heavy machinery, making presentations, and supervising others. The survey also asked about the intensity of their computer use, solving and learning from problems, physical tasks, and autonomy and repetitiveness. For each skill, a score ranging from 0 to 3 was computed, with 0 being equivalent to not using the skill, 1 for low use, 2 for medium use, and 3 for high use. The data also include the respondents’ self-reported information of the educational attainment required to do their job and the time required to learn how to do it.

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Figure 6.5 The Use of Cognitive Skills at Work, by Employment Status 100

Adults using skill regularly at work (%)

90 80 70 60 50 40 30 20 10 0 Formal employee

Informal employee

Reading

Writing

Numeracy

Self-employed Computer

Note: The figure excludes those currently in school.

Figure 6.6 The Use of Cognitive Skills at Work, by Economic Sector

Adults using skill regularly at work (%)

100

Agriculture, fishing, and mining

Manufacturing Reading

Writing

Low-to-midvalue-added Numeracy

High-value-added

Computer

Note: The figure excludes those currently in school.

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The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Working in the formal sector implies regularly learning new things at work and more frequently involves supervising others’ work and making presentations. Conversely, work in the informal sector is less cognitively but more physically demanding and is more repetitive. Self-employed workers reported having more autonomy at work and performing more repetitive tasks than wageworkers (figure 6.7).

Figure 6.7 Job-Relevant Skills, by Employment Status a. Intensity of activities by employment status 3.0

Average score

2.5 2.0 1.5 1.0 0.5 0 Self-employed

Informal employee

Autonomy and repetitiveness

Formal employee

Physical task

Solving and learning

b. Frequency of people engaging in various types at work by employment status

Workers using skill (%)

100 80 60

40 20 0

Self-employed

Informal employee

Operates heavy machines Repairs electronic equipment Drives a car, truck, or three-wheeler

Formal employee Supervises others Makes presentations

Note: Excludes those currently in school. In panel a, the intensity of activities by employment status measured as a score ranging from 0 to 3 was computed, with 0 being equivalent to not using the skill, 1 for low use, 2 for medium use, and 3 for high use.

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Socioemotional Skills The survey includes information on socioemotional skills, more specifically on the “Big Five” personality traits (openness, conscientiousness, extraversion, agreeableness, and stability), grit, and hostile bias. Hostile bias is a behavioral characteristic that measures how often the individual believes that others are hostile to him or her. In addition, the survey also asks about risk and time preferences. Risk lovers have a high score, whereas risk-averse people score low. For time preference, those with a high score are more future oriented and those with a low score are more present oriented (more detail about the socioemotional skills can be found in appendix B). This self-administered section was presented in English to the full survey sample. Because of low literacy, about 37 percent of respondents were not able to answer. Therefore, the results are not representative of the whole urban population because those who did not complete this section were not randomly selected and have different characteristics than those able to answer. For example, nonrespondents are older, less educated, and more likely to work in lowskilled occupations than those able to answer (see table D.5 in appendix D for further details). All questions relating to the measurement of socioemotional skills were answered on the following scale: 1 corresponding to “Almost never,” 2 corresponding to “Some of the time,” 3 corresponding to “Most of the time,” and 4 corresponding to “Almost always.” As reported in figure 6.8, the respondents

Figure 6.8 Average Score of Personality Traits and Grit 4

Averge score

Openness Conscientiousness

Extraversion Agreeableness

Girt Mean of grit

Note: The data include only those answering the socioemotional section.

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scored around 3 in nearly all the personality traits, which means that most of the time they identify themselves positively with the Big Five and grit. Among them, extraversion is the trait with the lowest average score (2.5) and conscientiousness the one with the highest average score (3.2). On average, respondents located on the middle to low level in the hostile bias scale. With respect to their preferences, they are on average more likely to be present than future oriented and more likely to be risk averse than risk loving (figure 6.9). There is a growing literature underscoring the role of socioemotional skills in education and labor market achievement. Figure 6.10 illustrates the estimated coefficients for socioemotional skills as factors associated with the number of school years completed, controlling for sociodemographic characteristics (age, gender, maternal education, socioeconomic status at age 15, and the region of residency). Similarly, in figure 6.11 the same associations are reported for the estimated probability of attending at least SHS. Finally, figure 6.12 illustrates the association between socioemotional skills and the probability of being employed, being self-employed (versus wageworkers), and employment in midto high-skilled occupations (versus low-skilled occupations). Overall, the results suggest that socioemotional skills are closely associated with educational attainment (figures 6.10 and 6.11). More specifically, a higher self-reported score relative to the Big Five personality traits is associated with higher educational attainment. Among the personality traits, conscientiousness has the highest positive correlation, followed by extraversion, openness, and agreeableness. Grit and emotional stability are also positively associated but in smaller magnitude.

Figure 6.9 Average Scores for Hostile Bias and Time and Risk Preferences 4

Averge score

0 Hostile bias

Risk aversion

Time preference

Note: The data include only those answering the socioemotional section.

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Figure 6.10 Coefficients of Socioemotional Skills on Years of Education, Controlling for Sociodemographic Characteristics 0.3*

Stability

0.5***

Agreeableness

0.7***

Extraversion

1.0***

Conscientiousness 0.6***

Openness 0.3*

Grit –0.9***

Hostile bias –0.4***

Time preference

0.2**

Risk –1.0 –0.9 –0.8 –0.7 –0.6 –0.5 –0.4 –0.3 –0.2 –0.1 0

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Note: The “Big Five” (stability, agreeableness, extraversion, conscientiousness, and openness) are included simultaneously in the regression model. The rest of the skills are included on their own, with controls. Including each of the Big Five personality traits on their own with controls does not influence the results. Each coefficient should be interpreted as an indication of how a change in one unit of the skills score is related to years of education. *** p<0.01, ** p<0.05, * p<0.1. All models are estimated using ordinary least squares (OLS) controlling for maternal education, region, socioeconomic level at age 15, and gender. See table G.1 in appendix G for full results. *** p<0.01, ** p<0.05, * p<0.1.

Figure 6.11 Coefficients of Socioemotional Skills on the Probability of Attaining at Least SHS Education, Controlling for Sociodemographic Characteristics Stability

5.3%**

Agreeableness

5.2%** 8.5%***

Extraversion

14.1%***

Conscientiousness 7.8%***

Openness 2.9%

Grit Hostile bias

–11.5%*** –5.2%***

Time preference

3.6%***

Risk –16 –14 –12 –10

–8

–6

–4

–2

Note: The dependent variable is a binary variable that takes the value of one if the highest educational level is SHS or higher, and zero for all other levels of educational attainment. The Big Five (stability, agreeableness, extraversion, conscientiousness, and openness) are all included simultaneously in the same regression model. The rest of the skills are included on their own with controls. Including each of the Big Five personality traits on their own with controls does not influence the results. Each coefficient should be interpreted as an indication of how a change in one unit of the skills score is related to the probability of attaining SHS education or higher. All models are estimated using linear probability model controlling for maternal education, region, socioeconomic level at age 15 and gender. See table G.2 in appendix G for full results. *** p<0.01, ** p<0.05, * p<0.1.

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The Use of Cognitive Skills, Job-Specific Skills, and Literacy

The results are in line with the literature that relates better educational outcomes to those with higher levels of the Big Five personality traits and grit. Furthermore, those who are more trustful, more present oriented, and less risk averse have a higher probability of studying one additional year (figure 6.10). The results are substantially confirmed when analyzing the probability of completing at least SHS education (figure 6.11). In this case, a change in one score unit of conscientiousness is associated with 14 percentage points on the probability of completing SHS or tertiary attainment. As with years of education, higher agreeableness and stability levels, perceiving others as less hostile, being more present oriented, and being a risk lover increase the probability of completing higher levels of education Finally, we present the results of the association of socioemotional skills and the probability of being employed, being self-employed (versus wageworkers), and working in mid- to high-skill occupations (versus low-skill occupations). Figure 6.12 shows that in most cases the correlation is not statistically significant

Figure 6.12 Coefficients of Socioemotional Skills on the Probability of Selected Labor Market Outcomes –5.2%*

Stability Agreeableness Extraversion Conscientiousness

7.2%**

–4.0%*

–7.1%** –8.8%***

Openness Grit 8.8%***

Hostile bias Time preference –4.1%***

Risk –15

–10 Prob. employed

–5 Prob. self-employed

Prob. high-to-medium-skilled occupation

Note: The Big Five (stability, agreeableness, extraversion, conscientiousness, and openness) are all included simultaneously in the same regression model. The rest of the skills are included on their own with controls. Including each of the Big Five personality traits on their own with controls does not influence the results. Each coefficient should be interpreted as a measure of how a change in one unit of the score on the skill is related to the probability of being associated with the following labor market outcome: The probability of being employed is relative to those unemployed or inactive. The probability of being self-employed is relative to being a wage earner. The probability of being in high-to-medium-skilled occupations is relative to low-skilled ones. All models are estimated using linear probability model controlling for maternal education, region, socioeconomic level at age 15, gender, and level of education. See tables G.3 through G.5 in appendix G for full results. *** p<0.01, ** p<0.05, * p<0.1.

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The Use of Cognitive Skills, Job-Specific Skills, and Literacy

(once we controlled for education, one of the control variables included in the model). However, noncognitive skills seem to play a role in determining the quality of the occupation. Individuals with higher levels of the Big Five personality traits and lower levels of hostile bias are less likely to be self-employed (and therefore more likely to be wageworkers). Interestingly, the only socioemotional skill that is significantly associated with having a mid- to high-skill occupation is emotional stability, which relates to the ability to cope with stress. Included in mid- to high-skill occupations are managers, professionals, clerical support workers, and service and sales workers.

Reading Literacy Assessment The reading literacy assessment consists of three parts, all administered in English. The first part (Reading Components) evaluates foundation reading skills, including word meaning, sentence processing, and passage comprehension. The second part (Core Literacy Test) consists of a core literacy assessment that is intended to sort the least literate adults from those with higher reading skill levels. The Core Literacy Test has a total of eight items, and respondents with three or more correct responses are regarded as having met a minimum reading literacy threshold (see box 6.1 for more information on the Core Literacy Test). The third part (the Literacy Exercise Booklets) is administered only to those respondents who have passed the Core Literacy Test (see box 6.1). The Literacy Exercise Booklets use a variety of questions drafted around daily life situations. They require respondents to carry out different types of tasks such as accessing and identifying information (in both text-based and nonprose materials such as tables, graphs, and forms), integrating and interpreting information, and evaluating information by assessing the relevance, credibility, or appropriateness of the material for a particular task. Overall reading proficiency scores are reported on a scale ranging between 0 and 500, which is divided into five levels, with level 1 characterized by the least demanding tasks and level 5 the most demanding. For each respondent, 10 plausible values were generated. All survey respondents were asked to answer the Core Literacy Test. Nevertheless, the nonresponse rate is quite high—about 38 percent (figure 6.13). There are two types of nonrespondents: those who fail to complete the section because they are unable to read or understand English (“No English”) and those who did not complete the tests for multiple reasons (“Missing”).2 Those with no English literacy represent 21 percent of the adults, whereas the missing group represents 17 percent of the sample. The three groups (those who answered the Reading Components and the Core Literacy Test, the group with no English literacy, and the missing group) are significantly different; therefore, the findings summarized may not be applicable to the entire urban sample. For example, those who answered are more likely to speak English at work (57 percent versus 18 percent of the missing and those with no English together) and to read and write with higher intensity than those who did not answer the test. Compared to the nonrespondents, they have higher Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Box 6.1 What Does It Mean to Pass the Core Literacy Test? A sizable proportion of adults reported that they read regularly, even though they did not pass the minimum literacy threshold of the Core Literacy Test. One reason could be that the tests are in English whereas many individuals mainly speak a local language. Only 1 percent and 40 percent speak English as their main language at home and at work, respectively (figure B6.1.1). In contrast, Akan is widely used in daily life. Thus, although the literacy assessment captures reading proficiency in English, the self-reported measure could be a better proxy of respondents’ capacity to read and write in their daily life in their local language. Even though only 40 percent of adults speak English at work, 58 percent of the urban adults report being able to speak and to read and write English well enough to work in a job that requires them to do so (figure B6.1.2). As expected, the vast majority (90 percent) of those with no English and a third of those who failed the Core Literacy Test are unable to write, read, or speak in English at work. In contrast, among those who passed the Core Literacy Test, about 96 percent report being able to write, read, and speak English at work. (figure B6.1.3). Notably, about half of those who failed the Core Literacy Test report being able to use English at work—that is, there is a discrepancy between the self-reported and measured skills. Poor English language literacy does not seem to prevent people from getting a job (figure B6.1.4). Only 12 percent report that the lack of English kept them from getting a job. However, those who speak English at work tend to have better-quality jobs. They are more likely to be formal employees in high-value-added sectors and in high-skill occupations. They also earn on average 248 GHS per month (or 60 percent) more than those who do not speak English at work.

Figure B6.1.1 Main Language Spoken at Home and Work a. At home

b. At work

Akan

Ewe

Ga-Adangme

Mole-Dagbani

English

Other

Other 0

100

Percent

100

Percent

Note: This figure includes all individuals regardless of whether or not they are attending school as well as those who worked at any point during the previous 12 months. box continues next page

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The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Box 6.1 What Does It Mean to Pass the Core Literacy Test? (continued) Figure B6.1.2 Self-Reported Ability to Speak and Read/Write in English at Work percent Speak, write/read, 58

Don’t speak or write/read, 32

Don’t speak but do write/read, 1 Speak but don’t write/read, 8 Note: This figure includes individuals regardless of whether or not they are attending school. Proportions may not add up to 100 percent because figures are rounded.

Figure B6.1.3 Performance in the Core Literacy Test According to Self-Reported Ability to Speak and Read/Write in English 100

Percent

Missing

No English

Don’t speak or read/write

Failed Only speak

Passed Speak and read/write

Note: This figure includes all individuals regardless of whether or not they are attending school. box continues next page

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The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Box 6.1 What Does It Mean to Pass the Core Literacy Test? (continued) Figure B6.1.4 Did the Lack of English Keep You from Getting a Job? percent Don’t know/ haven’t applied, 11

Yes, 12

No, 76 Note: The figure includes all individuals regardless of whether or not they are attending school and those who worked at any point during the previous 12 months. Proportions may not add up to 100 percent because figures are rounded.

education levels, are on average nine years younger, and are more likely to be students, to be wageworkers rather than self-employed, and to work in highvalue occupations. Although one-third of the missing group use English at work, 6 percent of those with no English literacy do. Furthermore, almost three-quarters (72 percent) of those with no English did not complete any formal education, whereas only 18 percent of the missing group has no education and 17 percent completed at least SHS. Also a lower percentage of those with no English reported using their reading and writing skills compared to those in the missing group.

Reading Components The Reading Components section evaluates the extent to which participants can recognize the printed forms of common objects (print vocabulary), comprehend sentences of varying levels of complexity (sentence processing), and comprehend the literal meaning of connected text (basic passage comprehension). Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Figure 6.13 Distribution of Reading Component and Core Literacy Test Respondents percent No English, 21 Answered test, 62

Missing, 17

Note: This figure includes only those who are currently in school.

The overall performance is low in all three sections (figure 6.14). Sentence processing has the highest percentage of correct answers (41 percent) at all education levels, age groups, and levels of self-reported use of skills. However, it is also the section with the highest percentage of nonresponse (19 percent) compared to 11 percent in print vocabulary and 9 percent in passage comprehension. In passage comprehension only 38 percent of the items are answered correctly. The lowest performance is in print vocabulary with only 21 percent correct answers. Respondents reporting to be medium- to high-intensity readers or writers answer a higher percentage of correct answers in both the sentence processing and passage comprehension tests. The only exception is for the print vocabulary component, which does not vary much across groups (figure 6.15, panels a and b). The percentage of correct answers increased with the education level achieved (figure 6.16, panel a), and younger cohorts performed better than older age groups (figure 6.16, panel b). Those with no formal education answered fewer than 24 percent of the questions in each section correctly. Even though the results improve across all levels of education, there is a more noticeable difference between junior high school (JHS) and SHS graduates. Those with a primary or a JHS education answered less than one-third of the test questions correctly, whereas those with an SHS or a tertiary education answered about 44 percent of the passage questions and 46 percent of the sentence questions correctly. However, even among those with tertiary education, the scores on the print vocabulary section are low, with an average of only 23 percent correct answers—only 4 percentage points Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Figure 6.14 Performance on the Reading Component 100

Answer (%)

Passage

Sentence Nonreponse

Vocabulary

Incorrect

Correct

Note: This figure excludes the 38 percent of the sample that did not take these tests and includes people currently attending school. Proportions may not add up to 100 percent because figures are rounded.

Figure 6.15 Performance According to the Self-Reported Use of Reading and Writing Skills b. Writing 80

Correct answers (%)

a. Reading 80

Skill not used

Low

Medium

High Passage

Sentence

Skill not used

Low

Medium

Vocabulary

Note: This figure excludes the 17 percent of the sample that did not take these tests. Includes people currently attending school.

higher than those in primary education. Younger generations are more likely to perform better in the sentence and passage comprehension tests than older age groups (figure 6.16, panel b). This might suggest an improvement of the literacy level over time or might simply reflect a greater familiarity of the younger generations with taking assessment tests. Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

High

The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Figure 6.16 Performance According to Age Group and Education Level b. Education level

Correct answers (%)

a. Age group (years)

15–19

20–24

25–34

35–44

45–64 Passage

Sentence

None

Primary

JHS

SHS

Tertiary

Vocabulary

Note: This figure excludes the 17 percent of the sample that did not take these tests and includes people currently attending school. JHS = junior high school; SHS = senior high school.

Core Literacy Test The Core Literacy Test contains eight basic literacy questions and is designed to identify those with a minimum level of literacy, namely those who can answer at least three of the eight questions correctly. Only 42 percent of the respondents pass this threshold; 17 percent do not answer because they are unable to read the questions, and 22 percent are missing for other reasons. When taking out the missing group and adding those with no English to the group that did not pass the Core Literacy Test, the data show that only half of the population passed the Core threshold (figure 6.17, panel a). The distribution of correct answers has a U shape: about 15 percent of the sample answered all questions correctly, and 14 percent had no correct answer. The median value is about three to four correct answers (figure 6.17, panel b). This section provides a profile of those who pass and those who fail the test (considering together those who failed and the “No English” subgroup) in terms of gender, age, education level, language, labor and employment status, self-reported use of skills, socioemotional characteristics, and performance on the Reading Components and Core Literacy Tests. Full results are reported in appendix D. Young men with at least an SHS education are most likely to pass the test. More than half of those who pass the exam were male and seven years younger than the average. Ninety-three percent of those who failed the test had a JHS education or lower (42 percent have no formal education and 33 percent attended JHS), whereas about 57 percent of those who passed the test had at least an SHS education and about 21 percent have tertiary education. Notably, about 81 percent of those who passed the exam had received early childhood education compared with 47 percent of those who failed. Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Figure 6.17 Core Literacy Test Performance percent a. Sample distribution

b. Correct answer distribution 40

No English, 25 Passed, 50 Adults (%)

Failed, 24

20 10 0 No 0 English

Total correct answers in core Note: This figure excludes the 17 percent of the sample that did not take these tests and includes people currently attending school. Proportions may not add up to 100 percent because figures are rounded.

The variables for socioeconomic status (SES) and whether English was the respondent’s main language are both highly correlated with the probability of passing the test. About 30 percent of those who failed the test have been poor during their adolescence, and only 15 percent of them passed the Core Literacy Test. Although English is Ghana’s official language, only 1 percent of all respondents reported speaking English at home and 40 percent at work. Because the reading test was in English, it is not surprising that a higher percentage of those who passed the test than of those who failed reported English as the main language at home and at work. Among those who passed the test, 73 percent use English at work compared with 17 percent of those failing the test. Furthermore, the probability of succeeding is higher for those working in the formal sector and in high-skilled and better-paid occupations. Within the employed group, 81 percent of those who failed the test are self-employed and only 3 percent are formal wageworkers. More than half work in mid-skilled occupations and only 3 percent are in high-skilled jobs. In contrast, 38 percent of those who passed the exam were self-employed and 34 percent were formal wageworkers. One-third worked in high-skilled occupations and earn on average 274 GHS (approximately US$80) more per month than those who failed the test. Self-reported measures of the use and intensity of use of reading and writing skills is highly correlated with the results of the Core Literacy Test. Nevertheless, a significant number of people who reported using their skills regularly failed the test. Indeed, of those who did not pass the test, about 42 and 38 percent, respectively, reported using their reading and writing skills. The (self-reported) intensity of use of reading and writing skills is a better predictor of the test results. Indeed, 41 percent of those who pass the test are regular (high-intensive) readers compared to Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

The Use of Cognitive Skills, Job-Specific Skills, and Literacy

only 12 percent of those who fail the test. Similarly, 83 percent of those who fail the test self-report being low-intensity writers, and the percentage of low-intensity writers is lower (63 percent) among those who did not pass the test. The differences among respondents are more significant when we compare those who successfully pass the Core Literacy Test with those who do not answer any questions correctly. On average the latter have lower education (half of them have not completed any formal education); only 5 percent speak English at work and none of them use it at home. Eighty percent of these respondents are employed and most of them (79 percent) are self-employed. Fewer than one-third of them report using their reading skills (only 9 percent of them are high-intensive readers) or their writing skills (only 2 percent of them are high-intensive writers).

Literacy Exercise Booklets Those who succeed in the Core Literacy Test are asked to take the Literacy Exercise Booklets, which provide a more in-depth evaluation of reading skills. The Literacy Booklets are scored on a scale that ranges from 0 to 500 and includes six literacy levels from “below level 1” to level 5. The description of the literacy competencies for each one of the levels is provided in table 3.2. The “below level 1” includes those who failed the Core test (half of the original sample) and an imputed score for those who did not answer (about 17 percent of the eligible sample).3 The average performance on the Literacy Exercise Booklets is very poor. Most of the population (61 percent) is below level 1, 18 percent reach level 1, 17 percent reach level 2, only 4 percent of the respondents reach level 3 or level 4 (reported together in figure 6.18), and no one is in level 5. The level achieved is positively correlated with the number of correct answers in the Core Literacy Test. Those with a reading proficiency below level 1 are those who did not reach the minimum threshold set for the Core Literacy Test (three correct answers) (about 33 percent) and the group with no English literacy (34 percent). However, 11 percent of those below level 1 passed the Core test but performed poorly in the subsequent assessment. On the other hand, those in level 3 and 4 answered correctly at least six of the Core test questions. Indeed, 93 percent of them correctly answered seven or more questions in the Core test (figure 6.19). Like those passing the Core test, those scoring high in the literacy assessment are younger, have higher education (SHS or tertiary), and are more likely to work in the formal sector, to use their reading and writing skills more intensively, and to use English more frequently at work and at home (figure 6.20). Performance on the Literacy Exercise Booklets is correlated with the selfreported reading intensity as well. For example, among those who passed the Core Literacy Test with three to six correct answers, more of those who self-reported using their reading skills with high intensity reached level 1 than did those who read with low intensity (52 percent versus 43 percent) and level 2 (25 percent versus 14 percent) (figure 6.21). Similarly, among those who completed the whole Core Literacy Test correctly, 27 percent of the high-intensity readers reached levels 3 and 4 on the Literacy Exercise Booklets versus only 7 percent of those who selfreported reading with low intensity. Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Figure 6.18 Performance on Literacy Exercise Booklets: Proficiency Levels percent Level 3/4, 4

Level 2, 17

Below level 1, 61

Level 1, 18

Note: The “below level 1” portion includes those who failed the core test (half of the original sample) and an imputed score for those who did not answer (about 17 percent of the eligible sample).

Figure 6.19 Distribution of Core Literacy Test Results, by Proficiency Levels Achieved on Literacy Exercise Booklets 100

Urban adults (%)

Below level 1

Level 1 Illiterate Score 3, 4, 5, 6

Level 2 Level 3/4 Missing Score 0, 1, 2 Score 7, 8

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The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Figure 6.20 Literacy Level According to Gender, Education Level, Age Group, Reading Intensity, Labor Status, and Employment Status b. Education

Level 2: 226 to 275 points Level 1: 176 to 225 points

Male

Level 3: 276 to 325 points Level 2: 226 to 275 points Level 1: 176 to 225 points

None Primary JHS

Level 2: 226 to 275 points Level 1: 176 to 225 points

Skill not used

Low

Medium

SHS Tertiary

300 275 250 225 200 175 150 125 100 75 50 25 0

e. Labor status

Reading proficiency score

d. Reading intensity 300 275 250 225 200 175 150 125 100 75 50 25 0

c. Age group (years)

High

300 275 250 225 200 175 150 125 100 75 50 25 0

Level 2: 226 to 275 points Level 1: 176 to 225 points

Employed

Unemp- NEET loyed

Level 1: 176 to 225 points

15–19 20–24 25–34 35–44 45–64 f. Employment status

Reading proficiency score

Female

300 275 250 225 200 175 150 125 100 75 50 25 0

Reading proficiency score

a. Gender 300 275 250 225 200 175 150 125 100 75 50 25 0

Inactive at school

300 275 250 225 200 175 150 125 100 75 50 25 0

Level 2: 226 to 275 points Level 1: 176 to 225 points

Formal

Informal employees

Informal selfemployees

Note: JHS = junior high school; NEET = Not in Education, Employment, or Training; SHS = senior high school.

Figure 6.21 Differences in Proficiency Levels, by Self-Reported Reading Intensity 100

Urban adults (%)

80 60 40 20 0 Low intensity

High intensity

Low intensity

ETS Score 3–6 Below level 1

High intensity

ETS Score 7–8 Level 1

Level 2

Level 3/4

Note: ETS = Educational Testing Service.

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Developing Skills beyond Education: Training and Apprenticeships In Ghana 32 percent of the adult population living in urban areas continue their skills development by participating in skills training courses, by achieving industry- or government-recognized certificates, and through informal apprenticeships. Apprenticeship is the most common: in the 12 months prior the survey, 25 percent of adults participated in an apprenticeship, whereas only 6 percent received a recognized training certificate and less than 7 percent participated in a formal training course of at least 30 hours. It is worth noting that, although apprenticeship is more common for older age cohorts (figure 6.22, panel b) and among those with JHS or lower education, training is more common for those with tertiary education (figure 6.22, panel a). After completing each level of formal education, students might continue with the next level of formal education or leave the education system and take an apprenticeship instead. As shown in figure 6.23, apprenticeship does not replace formal education. Indeed, most of people who complete an education level either decide to drop out of school or continue in formal education. Among those completing primary education, only 4 percent left the education system for an apprenticeship, 65 percent start JHS, and 10 percent drop out. The percent of those opting for an apprenticeship is the highest among those completing JHS: 13 percent of them choose an apprenticeship while 30 percent continue to SHS. Formal workers generally have more training outside the formal education system, whereas apprenticeship is more common among the self-employed. Twenty-six percent of formal workers participated in work-related or personalrelated skill training courses, 25 percent participated in apprenticeships, and 14 percent achieved an industry- or government-recognized certificate. About 38 percent of the self-employed participate in an apprenticeship (figure 6.24). Apprenticeships are also more common among those working in low-skilled occupations and in the manufacturing sector (figure 6.25). The most common

Figure 6.22 Certificate, Training, and Apprenticeship, by Education Level and Age Group a. Education level

b. Age group (years) 60 Urban adults (%)

Urban adults (%)

60 40 20 0

40 20 0

None

Junior Senior Tertiary Primary education high school high school education Certificate

Training courses

15–19

20–24

Apprenticeship

Note: The figure excludes those who are currently at school.

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25–34

35–44

45–64

The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Figure 6.23 Are Students Choosing Apprenticeship Instead of Formal Education? 100

Percent

0 None

Primary education

Junior high school

+ Higher education level

No more

Senior high school

Tertiary

+ Apprenticeship

Note: The figure excludes those who are currently at school. The subgroup “+ Higher education level” includes those who, after completing a certain education level, continue with the next level of education. The subgroup “+ Apprenticeship” includes those who complete a certain education level, drop out, and opt for an apprenticeship. The subgroup “No more” includes those who, after completing a certain education level, left school without completing another level of education.

Figure 6.24 Certificate, Training, and Apprenticeship, by Employment Status 80

Urban adults (%)

0 Formal employee Certificate

Informal employee Training courses

Self-employed Apprenticeship

Note: The figure excludes those who are currently at school.

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The Use of Cognitive Skills, Job-Specific Skills, and Literacy

Figure 6.25 Certificate, Training, and Apprenticeship, by Occupation and Economic Sector b. Economic sector

Urban adults (%)

a. Occupation

Low-skilled

Mid-skilled

High-skilled

Certificate

Agriculture, ManufacLow-tofishing, and turing mid-valuemining added

Training courses

Apprenticeship

Note: The figure excludes those who are currently at school.

field of apprenticeship is personal service, retail, and related (65 percent), where the category barber, hairdresser, hair stylist, and cosmetologist accounted for close to 40 percent of the apprenticeships.

Notes 1. See appendix B for a definition of skills use and intensity of use variables. 2. This group includes for example those refusing to begin the test booklet (because of time constraints, not wanting to bother, or other general refusal), those who began the booklet but refused to continue, or those who were unable to continue because of an unusual circumstance. 3. The literacy proficiency is modeled using the item response theory in a scale that ranges from 0 to 500. Each point in the 500-point scale has a probability of completing the tested item. The higher the score for a given individual, the more proficient the individual is. The design divides the test into partially linked booklets so that only a portion of the entire battery of items is administered to a single individual. Otherwise, the assessment would be too long if every individual had to take the entire battery of items. In order to estimate the proficiency level, multiple literacy proficiency scores (plausible values) are estimated for each individual on the basis of response to the items as well as some background information. Only those who passed the Core had to respond to this booklet, providing a finer evaluation of reading skills for the most literate respondents. However, imputation allows estimating the reading proficiency level for all respondents.

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Highvalueadded

The Use of Cognitive Skills, Job-Specific Skills, and Literacy

References Leuven, E., H. Oosterbeek, and H. van Ophem. 2004. “Explaining International Differences in Male Skill Wage Differentials by Differences in Demand and Supply of Skill.” The Economic Journal 114 (495): 466–86. Tyler, John H. 2004. “Basic Skills and the Earnings of Dropouts.” Economic of Education Review 23 (3): 221–35. World Bank. 2014. “STEP Skills Measurement Program.” World Bank, Washington, DC. http://microdata.worldbank.org/index.php/catalog/step/about.

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Chapter 7

The Returns to Education and Skills: Building the Job-Relevant Skills That Employers Demand

Introduction This section discusses the payoffs of education and skills in term of earnings and job opportunities. This section answers the following questions in detail: To what extent does education explain better labor market opportunities and higher earnings? (And at which educational level does further investment in education not generate a premium?) Do skilled workers have higher earnings? Which skills yield the best labor market opportunities and higher earnings? The analysis carried out in this section involves descriptive statistics and two multivariate regression models. The first model is a Mincer equation for earnings. The second is an employment participation model. These models look at the correlation between education and/or skills and monthly earnings and employment status, respectively. For the two models we tried different specifications. The first specification reported in the figures and tables below does not include any controls and reports only the “pure” correlation between monthly earnings (or self-employment status) and the education variables (either years of education or education levels where those with no formal education or incomplete primary are used as a reference category). In the second model, we control for a core set of sociodemographic variables including age, gender, work experience, economic sectors, and regional dummies. Then we include a set of controls one at time to see how education returns vary when taking into account (i) the results of the proficiency assessment test (the number of correct answers in the Core Literacy Test and the percentage of correct answers on the Reading Components); (ii) individual personality traits; (iii) the intensity of the use of cognitive skills; (iv) the intensity of the use of job-specific skills (cognitive challenges, physical work, autonomy and repetitiveness,

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The Returns to Education and Skills: Building the Job-Relevant Skills That Employers Demand

presentation skills, supervision skills, and the use of computer at work); and (v) all of the controls together. All control variables are defined in appendix C and full results are reported in appendixes D and E.1

Returns to Education and Skills Our data show some returns for continued education. An additional year of education increases monthly earnings by 3–7 percent (figure 7.1). Notably, primary education has no distinguishable premium in terms of earnings, considering those with no formal education or incomplete primary education as a base category. We also found that market rewards for primary education and junior high school (JHS) are lower than those for senior high school (SHS) and higher levels of education.2 For higher education, the premium is between 16 and 63 percent for SHS graduates and between 77 and 156 percent for tertiary graduates compared to workers with no formal education or incomplete primary education. The premium for JHS is much lower (between 10 and 40 percent). Faced with uncertain and binding constraints, people are more likely to drop out of school before SHS. In fact, as mentioned above, the majority of the population (66 percent) leaves the education system before SHS.

Figure 7.1 Returns to Education 156*** 7***

156*** 7***

141*** 6***

Return of level of education (%)

140

131*** 6***

120

116*** 5***

100

111***

5***

77*** 4

80 63***

63***

60 40 20

3***

43***

50*** 39*** 17

40*** 28**

45*** 38***

36*** 26***

12**

3 2

21**16 15

Return of years of education (%)

160

1 0

Al lc on tro ls

Lit

ifi

lls

ills

y na

lit Us

as ac y

Pe rs o

en t

ic on om ec

cio

co nt ro ls

Primary

Junior high school

Senior high school

Tertiary

Years of education

Note: All models are estimated using ordinary least squares. The estimated coefficients for each education level (bars) and for the years of education (dotted line) are reported in the figure. ***p < .01, **p < .05, *p < 0.1.

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

The Returns to Education and Skills: Building the Job-Relevant Skills That Employers Demand

Overall skills are an important determinant of earnings beyond education. In fact the returns of any additional year of education decrease by 2 percentage points after all skills have been controlled for. The best-paid jobs are those that require intensive writing and job-specific skills such as the use of the computer and also involve cognitive challenges and supervision responsibilities. Out of the “Big Five” personality traits (openness, conscientiousness, extraversion, agreeableness, and stability), only the estimated coefficient for conscientiousness is statistically significant (see appendix E). Notably, even after accounting for all skills (cognitive, socioemotional, and job-specific skills), SHS and tertiary education have a significantly higher earnings premium. The returns to education and skills vary a great deal according to types of employment, with the lowest returns among self-employed and the highest among formal wageworkers. One additional year of education increases the monthly earnings of the self-employed by 1–5 percent, those of informal wageworkers by 4–6 percent, and those of formal wageworkers by 7–10 percent (see figure 7.2 and appendix E). Earnings differentials are a typical feature of labor market segmentation. More specifically, an earnings gap between informal sector workers and equally qualified formal wage and salaried employees can be interpreted as a measure of the degree of labor market segmentation (Schultz 1961; Becker 1962; and Mincer 1962). In countries such as Ghana, the formal economy is not capable of

Figure 7.2 Returns to Education, by Type of Employment a. The self-employed 154***

142***

Return of level of education (%)

140

9 127***

120

113***

100 80

154***

5***

5*** 60***

5***

60***

40 38***

38***

20 13

53***

3***

38***

37*** 8

3***

33** 30**

34** 23*

25** 15

68**

4***

1 17 11

2 1

ifi

ki lls Al lc on tro ls

ills sk

ity Us

na l so Pe r

en t sm es

er ac Lit

cio

ya ss

co nt ro ls No

Return of years of education (%)

160

figure continues next page

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The Returns to Education and Skills: Building the Job-Relevant Skills That Employers Demand

Figure 7.2 Returns to Education (continued) b. Informal wageworkers

Return of level of education (%)

140 120 100

132*** 119***

119***

6***

112***

106***

7***

6***

90***

5***

80 60

75*** 64***

39*** 29

40 39*** 29

53**

5 4**

58***

53***

32* 24

90*** 6

5***

4***

64***

48**

40*** 33

34** 21

27* 12

4 3 2

Return of years of education (%)

160

cs ifi

Pe r

lls Al lc on tro ls

ills sk

lit na so

sm es ss

ya Lit

en t

ic om on ec

cio

co nt ro ls

c. Formal sector wageworkers 140

100

114***

9***

104*** 7**

9 96** 9*** 8

82*

60 40

12 10

10***

29 24

4 28

30 16

2 1

Al lc on tro ls

sp ec

Us e

ifi

lls

ills sk

y na lit Pe rs o

Lit

cio

en t

co nt ro ls No

Return of years of education (%)

Return of level of education (%)

125*** 120

Primary

Senior high school

Junior high school

Tertiary

Years of education

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The Returns to Education and Skills: Building the Job-Relevant Skills That Employers Demand

providing enough good, high-wage jobs. The majority of self-employment consists of informal income-earning activities and small businesses pursued by individuals who are unable to secure (formal) wage employment. The key to accessing the formal wage sector is once again education (figure 7.3). About 44 percent of workers employed in the formal sector have a tertiary education and 32 percent have graduated from SHS, whereas only 24 percent have a JHS education or less. In Ghana the formal sector mainly consists of high-value-added service companies, which require a highly qualified labor force. Only tertiary education has a significant premium in the formal sector given the selection bias. This means, for example, that individuals with higher ability and motivation are more likely to choose and complete tertiary education and receive higher earnings. Graduates of SHS and JHS and those who have completed primary education all have the same probability as workers with no formal education of being self-employed (figure 7.4). Furthermore, self-employed workers use their numeracy skills more intensively than all other employees and perform fewer repetitive tasks and use the computer less. With respect to socioemotional skills, only grit is positively correlated with being self-employed (see appendix E).

Figure 7.3 Level of Education, by Employment Status 100

Urban adults (%)

80 60 40 20 0 Formal employee Tertiary

Informal employee

Senior high school

Junior high school

Self-employed Primary

None

Note: The figure excludes people currently attending school. Proportions may not add up to 100 percent because figures have been rounded.

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The Returns to Education and Skills: Building the Job-Relevant Skills That Employers Demand

Figure 7.4 Linear Probability Model of Being Self-Employed 20 10

Percent

–8** –1

1 3

1 1

–2

–4

–5

–10

8.2*

3 5

–8

–9**

–12*** –20 –30 –40 –41***

ls on Al

sm es ss ya ac er Lit

tro

ls ec sp b-

ifi

kil

ills

ity al on rs Pe

ec cio So

–50

Primary

Junior high school

Senior high school

Tertiary

Note: All models are estimated using linear probability model. The estimated coefficients for each education level (bars) are reported in the figure. See appendix E for full results. ***p < .01, **p < .05, *p < 0.1.

Returns to Education: Is There a Gender Premium? The returns to an additional year of education are very similar—between 3 and 5 percent for men and between 3 and 6 percent for women (figure 7.5). The returns to primary education are not significantly different from zero for both men and women. For males only tertiary education guarantees a premium, whereas for women education starts to pay off starting from JHS. The market reward is always higher for women than for men. In fact, after controlling for all skills, the returns to tertiary education are 98 percent for females and 73 percent for men. This gender gap might be misleading because it does not take into account that both labor market participation and educational attainments are lower for women.

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

The Returns to Education and Skills: Building the Job-Relevant Skills That Employers Demand

Figure 7.5 The Returns to Education a. Male workers

140 120 100 80 60

9 109***

117***

109***

97***

8 95***

6***

5***

66*** 4***

73*** 6 5

5**

3 1

–40

Lit

ifi

na so

Pe r

es ss ya

y lit

en t sm

om on ec

cio So

lls Al lc on tro ls

–20

ills

Return of years of education (%)

co nt ro ls

Return of level of education (%)

160

b. Female workers 156***

155***

10 142***

Return of level of education (%)

140

128***

120 100

6***

8 98***

6*** 5***

5***

80 60

38** 27**

33* 24**

33***

3**

3 2 1

Lit er a

ec -sp Jo b

Al lc on tro ls

lls ifi cs

sk of e Us

ills

ity al

Pe rs

en t

se ss

no ec o

cio So

co nt ro ls No

52***

38***

35***

40 35***

5***

58***

56***

123***

Return of years of education (%)

160

Primary

Senior high school

Junior high school

Tertiary

Years of education

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The Returns to Education and Skills: Building the Job-Relevant Skills That Employers Demand

Notes 1. We recognize the possible limitations of this estimation procedure in terms of possible multi-collinearity. Furthermore, a causal interpretation of the finding shown in the following sections is not either legitimate or claimed. 2. This is consistent with recent studies for many low-income countries showing that the returns to primary education are lower than those for the secondary level—see Mwabu and Schultz (2000) for South Africa, Kingdon (1997) for India, Siphambe (2000) for Botswana, among others. For example, Moll (1996) argues that a decline in school quality and changes in demand and supply factors largely account for the low returns to primary schooling in South Africa.

References Becker, Gary S. 1962. “Investment in Human Capital: A Theoretical Analysis.” Journal of Political Economy 70 (5, Part 2): 9–49. Kingdon, Geeta Gandhi. 1997. “Does the Labour Market Explain Lower Female Schooling in India?” LSE Research Online Documents of Economics 6715, London School of Economics and Political Science. Mincer, Jacob. 1962. “On-the-Job Training: Costs, Returns, and Some Implications.” Journal of Political Economy 70 (5, Part 2): 50–79. Moll, Peter G. 1996. “The Collapse of Primary Schooling Returns in South Africa 1960–90.” Oxford Bulletin of Economics and Statistics 58 (1): 185–209. Mwabu, Germano, and T. Paul Schultz. 2000. “Wage Premiums for Education and location of South African Workers, by Gender and Race.” Economic Development and Cultural Change 48 (2) 307–34. Schultz, Theodore W. 1961. “Investment in Human Capital.” American Economic Review 51 (1): 1–17. Siphambe, Happy Kufigwa. 2000. “Rates of Return to Education in Botswana.” Economics of Education Review 19 (3): 291–300.

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Chapter 8

Mismatch of Skills: A Measurement Issue and Unexploited Potential at Work

Mismatch between Self-Reported Skills and Core Literacy Test Results: Does Language Matter? Several of the cognitive and job-specific skills captured in the Skills Toward Employment and Productivity (STEP) survey are self-reported. These selfreported measures relate to the intensity of use of these skills at work or outside work. The self-reported reading skill measure can capture a subjective assessment of the mastery and usefulness of the skill, but a key question is how well these assessments fit in with some objective measures such as the Core Literacy Test. If subjective and objective measures reflected a real ability, those reporting that they read frequently should also be able to pass the Core test. However, although 69 percent of adults reported reading regularly, only 42 percent of the population passed the Core test. This considerable mismatch is due to both the high nonresponse rate for the objective literacy assessment (in contrast to low missing values for the subjective measurements) and the difficulties encountered in the Core test because of the language used. As a consequence, the Core test is more likely to be a measure of the individual’s English literacy than of his or her general reading skills. Notably, the self-reported assessment of the use of skills does not specify a particular language, and respondents might indeed take it to mean any of the local languages widely used not only in the rural Ghana but also in urban areas. There is a considerable mismatch between the self-reported and the assessed reading skills (that is, between those reporting that they read and those passing the Core test). Indeed, about 26 percent of those who reported reading did not pass the Core test. Still, those not passing the Core test and reporting reading are 41 percentage points more likely to speak English at work (74 percent use English at work whereas 33 percent do not) and slightly more likely to speak English at home (close to 2 percentage points). Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Mismatch of Skills: A Measurement Issue and Unexploited Potential at Work

The mismatch between self-reported and measured literacy is not randomly distributed (see appendix F). Those who failed the Core test and reported being able to read are more likely to be women, to be less educated, to work in low-skilled occupations and less in high-value-added sectors, and to earn about 41 percent less than those who report being able to read and also pass the Core test. The difference in the intensity of use of reading skills might definitively explain the skills mismatch between self-reported and objective measures of skills. The intensity of use of the skill is a more closely related measure to the Core test. Among those who self-reported reading with low intensity, 66 percent failed the text and 30 percent passed it. Only 14 percent of those who failed indicated reading frequently.

Are There Unexploited Skills in the Workforce? Among the employed population, a group of individuals reported using their cognitive skills and computer skills in their daily life (that is, using skills outside the realm of a paid job, including a family business) but not at work. This group of people might represent unexploited human capital that the labor market is not able to absorb. In this section, we analyze the profile of those who report using their skills only outside work and those who use their skills at work. Women—more frequently than men—are likely to be literate but employed in occupations not requiring the use of reading and writing skills. Similarly, there is an unexploited potential among the youngest generations who are able to use computers but work in jobs where this skill is not demanded. Being able to use their computer skills at work would guarantee them a monthly income 38 percent higher than they receive in their current occupations. Those using a skill only at home are less likely to work at a high-skilled occupation and in a high-value-added sector and are more likely to work at a mid-skilled occupation and a low- to mid-value-added sector. The greatest unexploited potential, as expected, is among those in low-skilled occupations and low-value-added sectors. For example, about 34 percent of the self-employed read at home but never use their reading skills at work. Conversely, only 6 percent of employees in the formal sector have a skills mismatch. The level of education seems to be closely related to the use of certain skills at work. The level of education of those who read, write, or use computers only at home is lower than for those using their skills at work. The latter are predominantly senior high school (SHS) graduates. The fact that the mismatch of skills occurs more at lower levels of education than SHS might suggest that SHS provides students with the right skills demanded by the labor market and that SHS education provides a clear signal to employers of the cognitive skills potential employees have.

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Mismatch of Skills: A Measurement Issue and Unexploited Potential at Work

To a certain extent the mismatch of skills used at home but remaining unused at work does reflect the quality of those skills rather than an unexploited potential. Indeed, on average those using their (reading, writing, and computer) skills only at home performed worse on both the Reading Component and the Core test than those who also use them at work. To sum up, there is a clear connection between the availability of skills and the use of skills at work, whether the skills are cognitive or work related. Moreover, the use of the skills at work appears to explain the difference between objectively measured and self-reported skills. Those who work in low-skilled occupations are more likely to report higher skills than are measured objectively through the literacy assessment.

Conclusions and Looking Forward In conclusion, the study has provided evidence in a number of areas that are relevant for policy makers, for setting government investment priorities and also for continued diagnostic work. The study demonstrated the positive impact of early childhood education on schooling, on jobs, and on earnings. The country continues to demonstrate progress in education attainment at all levels, but there is also evidence of persistent disparities in attainment by income, gender, and geographical location. There are also continued difficulties with delayed education, dropout, and low completion rate—mostly for the poor, given the high opportunity costs. Importantly, improved education attainment did not bring about comparable improvements in cognitive skills as measured by the adult literacy assessment. The labor market also shows persistent segregation between employment in higher-value sectors, where employees have higher attainment and education pays off, and employment in sectors such as agriculture, fishing, and mining, where there appears to be an equilibrium of low education and low income. In the first group, employees demonstrate and report higher skills. There is a clear connection between the availability of skills and the use of skills at work, whether the skills are cognitive or work related. Moreover, the use of the skills at work appears to explain the difference between objectively measured and self-reported skills. Those who work in low-skilled occupations are more likely to report higher skills than are measured objectively through the literacy assessment. These findings offer some priorities and options for policy and investment. For the country, investment and scaled-up access and quality in early childhood education would lead to sustained long-term growth and shared prosperity. For education policy, continued investment into improved literacy and also improved socioemotional and work skills helps build the country’s human capital (increasing demand for postbasic, postsecondary education) and improved labor force. Sustainable forms of skills development should incentivize demand and supply of skills through both formal and on-the-job training.

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Mismatch of Skills: A Measurement Issue and Unexploited Potential at Work

The study also offers options for continued diagnostic work. The household survey data could help carry out more in depth analysis on the return to education and skills (and the role of training), on skills formation (and how cognitive and noncognitive skills correlate), and cross-countries comparison with other similar datasets. Finally, this research could be complemented with a STEP employer survey that focuses on the demand for education and both cognitive and noncognitive skills by both public and private employers in Ghana’s key economic sectors.

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Appendix A

Summary of Statistics

Table A.1 Summary of Statistics from the STEP Survey Sample observations

Mean

Min

Max

Female (%) Age range (years) (%) 15–19 20–24 25–34 35–44 45–64

2,987 2,987 2,987 2,987 2,987 2,987 2,987

58 33 14 18 28 19 21

49 13 35 38 45 39 40

0 15 0 0 0 0 0

100 64 100 100 100 100 100

Education (%) No education Primary education Junior high school Senior high school Tertiary education Received early childhood education

2,987 2,987 2,987 2,987 2,987 2,948

21 14 36 20 10 64

40 35 48 40 29 48

0 0 0 0 0 0

100 100 100 100 100 100

Socioeconomic status (%) Low Middle High

2,960 2,960 2,960

23 56 21

42 50 41

0 0 0

100 100 100

Region (%) Western Central Greater Accra Volta Eastern Ashanti Brong-Ahafo Northern Upper East

2,987 2,987 2,987 2,987 2,987 2,987 2,987 2,987 2,987

9 11 26 5 6 22 10 7 2

29 31 44 22 24 41 31 26 15

0 0 0 0 0 0 0 0 0

100 100 100 100 100 100 100 100 100

table continues next page

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Summary of Statistics

Table A.1 Summary of Statistics from the STEP Survey (continued) Sample observations

Mean

Labor status (%) Employed Unemployed NEET Inactive

2,981 2,981 2,981 2,981

62 5 10 23

48 22 30 42

0 0 0 0

100 100 100 100

Employment status (%) Formal employee Informal employee

1,973 1,973

15 20

Self-employed

1,973

35 40 48

0 0 0

100 100 100

1,973 1,973 1,973

12 10 61

1,973

33 30 49 37

0 0 0 0

100 100 100 100

1,973 1,973

39 48

1,973 1,993

13 516

49 50 34

0 0 0

100 100 100

1,580

34,800

Language spoken at work (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

2,344 2,344 2,344 2,344 2,344 2,344

80 8 13 8 40 12

49 27 33

0 0 0

100 100 100

27 49 32

0 0 0

100 100 100

Language spoken at home (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

2,972 2,972 2,972 2,972 2,972 2,972

63 8 7 8 1 13

48 27 26 28 10 33

0 0 0 0 0 0

100 100 100 100 100 100

Economic sector (%) Agriculture, fishing, and mining Manufacturing Low- to mid-value-added High-value-added

Min

Max

Occupation (%)

Low-skilled occupation Mid-skilled occupation High-skilled occupation Monthly earnings (in GHS)

Note: Variables are described in appendix C. NEET = not in employment, education, or training; STEP = Skills Toward Employment and Productivity.

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Summary of Statistics

Table A.2 Sampling Procedure Comparison of STEP, GLSS 5, and GLSS 6 GLSS 5, 2005–06 Sampling frame Target population

Sample design

Sample size

2000 PHC All noninstitutionalized persons living in private dwellings

Sample design

Two-stage stratified

Sample unit

PSU: EA SSU: household

Number of PSUs Number of household

580

Observations of urban population

GLSS 6, 2012–13

STEP, 2011–13

2010 PHC 2010 PHC All noninstitutionalized All noninstitutionalized persons living in persons living in private private dwellings dwellings in urban areas of the country at the time of data collection Two-stage stratified Four-stage (implicit stratified) PSU: EA PSU: EA SSU: household Second stage sample unit: PSU partition Third stage sample unit: household Fourth stage sample unit: individual 1,200 201

8,700

18,000

3,015

4,074

11,538

2,987

Note: EA = Census Enumeration Area; GLSS = Ghana Living Standards Survey; PHC = Population and Housing Census; PSU = primary sample unit; SSU = secondary sample unit; STEP = Skills Toward Employment and Productivity.

Table A.3 Regional PSU Sample Size Comparison of STEP, GLSS 5, and GLSS 6 GLSS 5 Region Western Central Greater Accra Volta Eastern Ashanti Brong-Ahafo Northern Upper East Upper West Total

GLSS 6

STEP

20 17 73 13 22 53 20 14 5 3 240

8 7 30 5 9 22 8 6 2 1

51 55 130 39 56 90 52 35 21 16 545

9 10 24 7 10 17 10 6 4 3

16 17 57 12 18 47 16 12 4 2 201

8 8 28 6 9 23 8 6 2 1

Note: GLSS = Ghana Living Standards Survey; PSU = primary sample unit; STEP = Skills Toward Employment and Productivity.

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Appendix B

Skills Definitions, Survey Questions, and Aggregation Strategy

Self-Reported Reading, Writing, and Numeracy Survey Questions Self-reported reading “Do you read anything [in daily life/at this work], including very short notes or instructions that are only a few sentences long?” “Among the things that you normally read [in daily life/at this work], what is the size of the longest document that you read?” Self-reported writing “Do you ever have to write anything (else) [in daily life/at work], including very short notes, lists, or instructions that are only a few sentences long?” “Thinking about all the things you normally write (wrote) [in daily life/at work], what is the longest document that you write (wrote)?” Aggregation: Does not do read/write Reads/writes documents of 5 pages or less Reads/writes documents of 6 to 25 pages Reads/writes documents of more than 25 pages

Intensity of use = = = =

Does not use Low Medium High

Level 0 1 2 3

Self-reported numeracy “[As a normal part of this work /in daily life], do you do any of the following...?” Aggregation: Does no math Measures or estimates sizes, weights, distances Calculates prices or costs Performs any other multiplication or division Uses or calculates fractions, decimals or percentages Uses more advanced math such as algebra, geometry, trigonometry

Complexity of use

Level

Does not use

Low

= =

Medium High

2 3

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Skills Definitions, Survey Questions, and Aggregation Strategy

Specific On-the-Job Skills Survey Questions Computer use “As a part of your work do you (did you) use a computer?” “As a part of your life [outside of work as (OCCUPATION)] have you used a computer in the past 3 months?” Aggregation

Intensity of use

Does not use a computer/use a computer almost never Uses computer less than three times per week Uses computer three times or more per week Uses computer every day

= = = =

Does not use Low Medium High

Level 0 1 2 3

External interpersonal skills “As part of this work, do you (did you) have any contact with people other than co-workers, for example with customers, clients, students, or the public?” Using any number from 1 to 10, where 1 is little involvement (…) and 10 means much of the work involves meeting or interacting (…) what number would you use to rate this work? Aggregation Does not have any contacts with clients Involvement scale ranges from 1 to 4 Involvement scale ranges from 5 to 7 Involvement scale ranges from 8 to 10

Intensity of use = = = =

Does not use Low Medium High

Level 0 1 2 3

Physical tasks “Using any number from 1 to 10 where 1 is not at all physically demanding (such as sitting at a desk answering a telephone) and 10 is extremely physically demanding (such as carrying heavy loads, construction worker, etc), what number would you use to rate how physically demanding your work is?” Aggregation Not at all physically demanding Physical demand scale ranges from 2 to 4 Physical demand scale ranges from 5 to 6 Physical demand scale ranges from 7 to 10

Intensity of use = = = =

Does not use Low Medium High

Level 0 1 2 3

Cognitive challenge: average of two indicators “Some tasks are pretty easy and can be done right away or after getting a little help from others. Other tasks require more thinking to figure out how they should be done. As part of this work as [OCCUPATION], how often do you have to undertake tasks that require at least 30 minutes of thinking?” Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Skills Definitions, Survey Questions, and Aggregation Strategy

Aggregation

Intensity of use

Never Less than once per month Less than once a week but at least once a month OR at least once a week but not every day Every day

Level

= =

Does not use Low

0 1

= =

Medium High

2 3

“How often does (did) this work involve learning new things?” Aggregation

Intensity of use

Rarely At least 2–3 months or at least once a month At least once a week Every day

= = = =

Level

Does not use Low Medium High

0 1 2 3

Autonomy and repetitiveness: average of two indicators “Still thinking of your work as [OCCUPATION] how much freedom do you (did you) have to decide how to do your work in your own way, rather than following a fixed procedure or a supervisor’s instructions? Use any number from 1 to 10 where 1 is no freedom and 10 is complete freedom.” Aggregation

Intensity

Decision freedom scale from 1 to 2 Decision freedom scale from 3 to 6 Decision freedom scale from 7 to 9 Decision freedom scale 10

= = = =

Level

Close to none Low Medium High

0 1 2 3

“How often does (did) this work involve carrying out short, repetitive tasks?” Aggregation Almost all the time More than half the time Less than half the time Almost never

Intensity = = = =

Close to none Low Medium High

Level 0 1 2 3

Job learning time: based on three questions “What minimum level of formal education do you think would be required before someone would be able to carry out this work? How many years of work experience in other related work do you think would be required before someone with [FILL Q22] would be able to carry out this work? About how long would it take someone to learn to do this work well if they had [FILL Q22] education and [FILL Q23] years of related work experience?” Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Skills Definitions, Survey Questions, and Aggregation Strategy

Socioemotional Skills Survey Questions Scale Almost never Some of the time Most of the time Almost always

1 2 3 4

Openness - Do you come up with ideas other people haven’t thought of before? - Are you very interested in learning new things? - Do you enjoy beautiful things, like nature, art, and music? Conscientiousness - When doing a task, are you very careful? - Do you prefer relaxation more than hard work? - Do you work very well and quickly? Extraversion - Are you talkative? - Do you like to keep your opinions to yourself? - Are you outgoing and sociable? For example, do you make friends very easily? Agreeableness - Do you forgive other people easily? - Are you very polite to other people? - Are you generous to other people with your time or money? Emotional stability (neuroticism) - Are you relaxed during stressful situations? - Do you tend to worry? - Do you get nervous easily? Grit - Do you finish whatever you begin? - Do you work very hard? For example, do you keep working when others stop to take a break? - Do you enjoy working on things that take a very long time (at least several months) to complete? Hostile bias - Do people take advantage of you? - Are people mean/not nice to you? Decision making - Do you think about how the things you do will affect you in the future? - Do you think carefully before you make an important decision? - Do you ask for help when you don’t understand something? Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Appendix C

Definitions of Variables Used in the Analysis

Definition Female Age

A dummy variable equal to 1 if respondent is female, and 0 otherwise. Age of respondents: a dummy variable for each one of the following age groups: 15–19 years; 20–24 years; 25–34 years; 35–44 years; 45–64 years Education level A dummy variable for each one of the following education levels completed: None (equal to 1 if respondent has not completed any formal education level. Takes value 0 if respondent completed at least primary education); primary education (1 for those whose highest level of education completed is primary education); junior high school (1 for those whose highest level of education completed is junior high school); senior high school (1 for those whose highest level of education completed is senior high school); tertiary education (1 for those whose highest level of education completed is tertiary education) Early childhood A dummy variable equal to 1 if the respondent attended early childhood education (%) education, and 0 otherwise. Low socioeconomic A dummy variable equal to 1 if the respondent classified him or herself as having status (%) belonged to the three first income deciles at age 15 years, and 0 otherwise. Middle socioeconomic A dummy variable equal to 1 if the respondent classified themselves as having status (%) belonged to the 4th to 6th income deciles at age 15 years, and 0 otherwise. High socioeconomic A dummy variable equal to 1 if the respondent classified themselves as having status (%) belonged to the 7th to 10th income deciles at age 15 years, and 0 otherwise. Region A dummy variable equal to 1 if the respondent lives in this region, and 0 otherwise. Labor status Employed (%) Unemployed (%) NEET (%) Inactive (%)

A dummy variable equal to 1 if the respondent is employed and not in education, and 0 otherwise. A dummy variable equal to 1 if the respondent is unemployed and not in education, and 0 otherwise. A dummy variable equal to 1 if the respondent is inactive and not in education, or training or is retired, and 0 otherwise. A dummy variable equal to 1 if the respondent is inactive and not NEET, and 0 otherwise. table continues next page

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Definitions of Variables Used in the Analysis

Definition Employment status only defined for employed population Formal employee (%) A dummy variable equal to 1 if the respondent is a wageworker and does have social security, and 0 otherwise. Informal A dummy variable equal to 1 if the respondent is a wageworker and does not employee (%) have social security, and 0 otherwise. Self-employed (%) A dummy variable equal to 1 if the respondent is self-employed or an unpaid family worker, and 0 otherwise. Economic sector defined only for employed population following Economic sector coded to 2 digits, ISIC rev.4 Agriculture, fishing, A dummy variable equal to 1 if economic sector is agriculture, fishing, and and mining (%) mining and 0 otherwise. Manufacturing (%) A dummy variable equal to 1 if economic sector is manufacturing Low- to mid-valueA dummy variable equal to 1 if economic sector is electricity, gas, steam and air added (%) conditioning supply; water supply; sewerage, waste management, and remediation activities; construction; wholesale and retail trade; repair of motor vehicles and motorcycles; transportation and storage; accommodation and food service activities; information and communication; arts, entertainment and recreation; other service activities; activities of households; extraterritorial organizations and bodies, and 0 otherwise. High-value-added (%) A dummy variable equal to 1 if economic sector is 64–66 financial and insurance activities; real estate activities; professional, scientific and technical activities; administrative and support service activities; public administration and social security; education; human health and social work activities, and 0 otherwise. Occupation defined only for employed population Low-skilled A dummy variable equal to 1 if occupation is skilled agricultural, forestry, and occupation (%) fishery worker; craft and related trades worker; plant and machine operator and assembler; elementary occupations and 0 otherwise. Mid-skilled A dummy variable equal to 1 if occupation is technician and associate occupation (%) professional; clerical support worker; service and sales worker, and 0 otherwise. High-skilled A dummy variable equal to 1 if occupation is manager or professional and 0 occupation (%) otherwise. Monthly earnings Considering the main and second occupation (in GHS) Language Language at work Language at home

A dummy variable equal to 1 if the respondent speaks this language at work, and 0 otherwise. A dummy variable equal to 1 if the respondent speaks mainly this language at home, and 0 otherwise.

Note: NEET = not in employment, education, or training.

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Appendix D

Differences in Mean

Table D.1 Difference in Mean of Those Passing the Core Literacy Test Threshold and Those Failing the Core Y1: Failed Core test

Y2: Passed Core test

Obs

Mean

Obs

Mean

Difference: Y2 – Y1

Female (%)

1,274

70.06

45.82

1,193

43.16

49.55

−26.897***

Socioeconomic status (%) Low Middle High

1,265 1,265 1,265

29.92 51.23 18.84

45.81 50.00 39.12

1,192 1,192 1,192

14.69 61.81 23.50

35.42 48.61 42.42

−15.233*** 10.576*** 4.657**

Age range (years) (%) 15–19 20–24 25–34 35–44 45–64

1,274 1,274 1,274 1,274 1,274 1,274

35.55 9.15 12.51 29.25 25.28 23.80

12.73 28.85 33.10 45.51 43.48 42.61

1,193 1,193 1,193 1,193 1,193 1,193

28.85 23.23 25.69 26.25 10.79 14.05

12.27 42.25 43.71 44.02 31.03 34.76

−6.695*** 14.080*** 13.171*** −3.002 −14.491*** −9.759***

Education (%) No education Primary education Junior high school Senior high school Tertiary education Received early childhood education

1,274 1,274 1,274 1,274 1,274 1,260

42.14 18.56 32.75 6.25 0.30 47.09

49.40 38.89 46.95 24.22 5.45 49.94

1,193 1,193 1,193 1,193 1,193 1,184

0.60 9.44 32.42 36.81 20.72 81.25

7.75 29.25 46.83 48.25 40.55 39.04

−41.540*** −9.116*** −0.324 30.558*** 20.422*** 34.162***

Language spoken at work (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

1,077 1,077 1,077 1,077 1,077 1,077

79.04 6.60 9.51 12.10 16.72 16.30

40.72 24.84 29.35 32.62 37.33 36.96

837 837 837 837 837 837

77.88 7.10 14.81 3.09 73.28 7.82

41.53 25.69 35.54 17.31 44.28 26.87

−1.161 0.495 5.299*** −9.006*** 56.559*** −8.480***

Language spoken at home (%) Akan Ewe Ga-Adangme

1,274 1,274 1,274

58.43 5.98 3.55

49.30 23.72 18.50

1,193 1,193 1,193

65.35 9.03 9.75

47.60 28.67 29.68

6.925*** 3.048** 6.204*** table continues next page

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Differences in Mean

Table D.1 Difference in Mean of Those Passing the Core Literacy Test Threshold and Those Failing the Core (continued)

Y1: Failed Core test

Y2: Passed Core test

Obs

Mean

Obs

Difference: Y2 – Y1

1,274 1,274 1,274

12.86 0.23 18.96

33.48 4.79 39.21

1,193 1,193 1,193

5.42 1.98 8.47

22.65 13.92 27.86

−7.438*** 1.745*** −10.483***

1,274 1,274 1,274 1,274

73.31 4.05 11.97 10.67

44.25 19.72 32.47 30.89

1,193 1,193 1,193 1,193

45.84 6.39 7.74 40.03

49.85 24.46 26.74 49.02

−27.472*** 2.337* −4.226*** 29.362***

964

3.29

964 964

15.62 81.09

17.85

611

33.81

47.34

30.517***

36.32 39.18

611 611

28.03 38.17

44.95 48.62

12.404*** −42.922***

Occupation (%) Low-skilled occupation Mid-skilled occupation High-skilled occupation

964 964 964

44.74 52.75 2.52

49.75 49.95 15.67

611 611 611

25.04 41.42 33.54

43.36 49.30 47.25

−19.695*** −11.326*** 31.021***

Economic sector (%) Agriculture, fishing, and mining Manufacturing Low-to mid-value-added High-value-added

964 964 964 964

17.20 10.04 68.61 4.15

37.76 30.07 46.43 19.94

611 611 611 611

5.22 8.82 47.40 38.55

22.26 28.39 49.97 48.71

−11.981*** −1.220 −21.208*** 34.409***

Earnings Monthly earnings

928

388.33

1,213.30

674

662.31

2,046.88

273.980**

Socioemotional skills Extraversion (score) Missing extraversion Conscientiousness (score) Missing conscientiousness Openness (score) Missing openness Emotional stability (score) Missing stability Agreeableness (score) Missing agreeableness

437 1,274 431 1,274 432 1,274 426 1,274 430 1,274

2.43 67.27 2.93 67.37 2.82 67.45 2.65 67.93 2.79 67.47

0.60 46.94 0.64 46.90 0.63 46.88 0.59 46.69 0.69 46.87

1,175 1,193 1,175 1,193 1,175 1,193 1,173 1,193 1,175 1,193

2.58 1.53 3.31 1.53 3.22 1.53 2.75 1.87 3.15 1.53

0.60 12.26 0.53 12.26 0.52 12.26 0.55 13.56 0.58 12.26

0.149*** −65.742*** 0.375*** −65.844*** 0.395*** −65.920*** 0.097** −66.052*** 0.363*** −65.944***

Self-reported skills Reading Use reading skill Read with low intensity Read with medium intensity Read with high intensity

1,274 546 546 546

41.71 68.68 19.12 12.20

49.33 46.42 39.36 32.76

1,193 1,131 1,131 1,131

96.66 30.46 28.23 41.31

17.97 46.04 45.03 49.26

54.957*** −38.220*** 9.111*** 29.109***

Mole-Dagbani English Others

Mean

Labor status (%) Employed Unemployed NEET Inactive Employment status (%) Formal employee Informal employee Self-employed

table continues next page

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Differences in Mean

Table D.1 Difference in Mean of Those Passing the Core Literacy Test Threshold and Those Failing the Core (continued)

Y1: Failed Core test Writing Use writing skill Write with low intensity Write with medium intensity Write with high intensity Numeracy Use numeracy skill Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity Computer Use computer skill Computer with low intensity Computer with medium intensity Computer with high intensity Literacy assessment Reading proficiency

Y2: Passed Core test

Obs

Mean

Obs

Mean

Difference: Y2 – Y1

1,274 506 506 506

38.02 82.98 9.95 7.07

48.56 37.62 29.96 25.66

1,193 1,096 1,096 1,096

93.31 63.43 19.82 16.74

25.00 48.18 39.89 37.35

55.294*** −19.545*** 9.873*** 9.672***

1,274 1,201 1,201 1,201

93.71 44.55 53.01 2.44

24.28 49.72 49.93 15.43

1,193 1,134 1,134 1,134

95.82 11.94 62.01 26.05

20.01 32.44 48.56 43.91

2.110* −32.616*** 9.007*** 23.610***

1,274 70 70 70

6.63 45.36 12.67 41.97

24.90 50.14 33.50 49.71

1,193 643 643 643

56.37 32.73 18.12 49.14

49.61 46.96 38.55 50.03

49.736*** −12.623 5.456 7.168

1,274

77.11

1,193

221.68

144.571***

Note: NEET = not in employment, education, or training; Obs = number of observations. ***p < .01, **p < .05, *p < 0.1.

Table D.2 Difference in Mean of Those Passing the Core Literacy Test Threshold and Those English Illiterate Y1: English illiterate SD

Y2: Passed Core test

Obs

Mean

Obs

Mean

Female (%) Socioeconomic status (%) Low Middle High

659

75.12

43.27

1,193

43.16

SD 49.55

Difference: Y2 – Y1 −31.956***

656 656 656

36.07 48.08 15.84

48.06 50.00 36.54

1,192 1,192 1,192

14.69 61.81 23.50

35.42 48.61 42.42

−21.379*** 13.723*** 7.656***

Age range (years) (%) 15–19 20–24 25–34 35–44 45–64

659 659 659 659 659 659

39.33 2.43 7.48 28.61 30.33 31.15

12.18 15.41 26.33 45.23 46.00 46.35

1,193 1,193 1,193 1,193 1,193 1,193

28.85 23.23 25.69 26.25 10.79 14.05

12.27 42.25 43.71 44.02 31.03 34.76

−10.474*** 20.804*** 18.201*** −2.358 −19.541*** −17.106***

Education (%) No education Primary education Junior high school Senior high school Tertiary education Received early childhood education

659 659 659 659 659 651

72.14 13.41 13.85 0.60 0.00 30.96

44.87 34.10 34.57 7.74 0.00 46.27

1,193 1,193 1,193 1,193 1,193 1,184

0.60 9.44 32.42 36.81 20.72 81.25

7.75 29.25 46.83 48.25 40.55 39.04

−71.534*** −3.967** 18.572*** 36.209*** 20.720*** 50.288***

table continues next page

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Differences in Mean

Table D.2 Difference in Mean of Those Passing the Core Literacy Test Threshold and Those English Illiterate (continued)

Y1: English illiterate Obs

Mean

Language spoken at work (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

570 570 570 570 570 570

70.99 6.82 10.90 17.46 5.77 21.33

Language spoken at home (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

659 659 659 659 659 659

Labor status (%) Employed Unemployed NEET Inactive

Y2: Passed Core test Obs

Mean

Difference: Y2 – Y1

45.42 25.22 31.19 38.00 23.34 41.00

837 837 837 837 837 837

77.88 7.10 14.81 3.09 73.28 7.82

41.53 25.69 35.54 17.31 44.28 26.87

6.890** 0.279 3.916* −14.373*** 67.508*** −13.508***

45.85 6.68 3.70 18.43 0.07 25.27

49.87 24.98 18.89 38.80 2.68 43.49

1,193 1,193 1,193 1,193 1,193 1,193

65.35 9.03 9.75 5.42 1.98 8.47

47.60 28.67 29.68 22.65 13.92 27.86

19.500*** 2.355* 6.049*** −13.013*** 1.903*** −16.795***

659 659 659 659

81.53 3.67 12.64 2.17

38.84 18.81 33.25 14.57

1,193 1,193 1,193 1,193

45.84 6.39 7.74 40.03

49.85 24.46 26.74 49.02

−35.690*** 2.716* −4.896** 37.869***

Employment status (%) Formal employee Informal employee Self-employed

539 539 539

0.76 13.93 85.31

8.68 34.66 35.43

611 611 611

33.81 28.03 38.17

47.34 44.95 48.62

33.049*** 14.095*** −47.143***

Occupation (%) Low-skilled occupation Mid-skilled occupation High-skilled occupation

539 539 539

45.81 51.91 2.28

49.87 50.01 14.93

611 611 611

25.04 41.42 33.54

43.36 49.30 47.25

−20.771*** −10.490*** 31.261***

Economic sector (%) Agriculture, fishing, and mining Manufacturing Low- to mid-value-added High-value-added

539 539 539 539

20.89 9.43 67.81 1.87

40.69 29.26 46.76 13.56

611 611 611 611

5.22 8.82 47.40 38.55

22.26 28.39 49.97 48.71

−15.666*** −0.609 −20.410*** 36.685***

Earnings Monthly earnings

519

409.79

1,442.84

674

662.31

2,046.88

Socioemotional skills Extraversion (score) Missing extraversion Conscientiousness (score) Missing conscientiousness Openness (score) Missing openness

28 659 27 659 26 659

2.38 96.43 3.12 96.53 2.55 96.59

0.51 18.57 0.56 18.31 0.70 18.16

1,175 1,193 1,175 1,193 1,175 1,193

2.58 1.53 3.31 1.53 3.22 1.53

0.60 12.26 0.53 12.26 0.52 12.26

252.526* 0.203** −94.905*** 0.187* −95.008*** 0.664*** −95.065***

table continues next page

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Differences in Mean

Table D.2 Difference in Mean of Those Passing the Core Literacy Test Threshold and Those English Illiterate (continued)

Y1: English illiterate

Emotional stability (score) Missing stability Agreeableness (score) Missing agreeableness

Self-reported skills Reading Use reading skill Read with low intensity Read with medium intensity Read with high intensity Writing Use writing skill Write with low intensity Write with medium intensity Write with high intensity Numeracy Use numeracy skill Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity Computer Use computer skill Computer with low intensity Computer with medium intensity Computer with high intensity Literacy assessment Reading proficiency

Obs

Mean

25 659 26 659

2.85 96.83 2.55 96.62

659 98 98 98

Obs

Mean

0.72 17.54 0.69 18.10

1,173 1,193 1,175 1,193

2.75 1.87 3.15 1.53

0.55 13.56 0.58 12.26

−0.100 −94.956*** 0.605*** −95.089***

13.19 81.36 13.57 5.07

33.87 39.15 34.43 22.06

1,193 1,131 1,131 1,131

96.66 30.46 28.23 41.31

17.97 46.04 45.03 49.26

83.471*** −50.899*** 14.663*** 36.236***

659 90 90 90

11.83 89.48 10.52 0.00

32.32 30.85 30.85 0.00

1,193 1,096 1,096 1,096

93.31 63.43 19.82 16.74

25.00 48.18 39.89 37.35

81.481*** −26.051*** 9.307** 16.744***

659 611 611 611

91.56 53.60 46.16 0.24

27.82 49.91 49.89 4.85

1,193 1,134 1,134 1,134

95.82 11.94 62.01 26.05

20.01 32.44 48.56 43.91

4.263** −41.665*** 15.853*** 25.813***

659

0.59 50.79 0.00 49.21

7.65 61.23 0.00 61.23

1,193 643 643 643

56.37 32.73 18.12 49.14

49.61 46.96 38.55 50.03

55.783*** −18.053 18.124*** −0.071

104.82

1,193

221.68

116.864***

3 3 3 659

Y2: Passed Core test SD

Difference: Y2 – Y1

Note: NEET = not in employment, education, or training; Obs = number of observations. *** p < 0.01, ** p < 0.05, * p < 0.1.

Table D.3 Difference in Mean of Those Answering Core Literacy Test and Those Who Did Not Answer It Y1: Did not answer Core Obs

Mean

Female (%) Socioeconomic status (%) Low Middle High SES

1,179

70.37

1,159 1,159 1,159

Age range (years) (%) 15–19 20–24

1,179 1,179 1,179

Y2: Answered Core Obs

Mean

Difference: Y2 – Y1

45.68

1,808

50.26

50.01

−20.110***

30.85 50.72 18.43

46.21 50.02 38.79

1,801 1,801 1,801

17.60 59.42 22.99

38.09 49.12 42.09

−13.248*** 8.693*** 4.555**

38.27 3.76 9.13

12.32 19.04 28.81

1,808 1,808 1,808

29.78 20.88 23.06

12.29 40.66 42.14

−8.493*** 17.117*** 13.938***

table continues next page

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Differences in Mean

Table D.3 Difference in Mean of Those Answering Core Literacy Test and Those Who Did Not Answer It (continued) Y1: Did not answer Core Obs

Mean

1,179 1,179 1,179

29.40 27.77 29.94

Education (%) No education Primary education JHS education SHS education Tertiary education Received ECE

1,179 1,179 1,179 1,179 1,179 1,155

Language spoken at work (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

Y2: Answered Core Obs

Mean

45.58 44.81 45.82

1,808 1,808 1,808

27.45 13.83 14.78

44.64 34.53 35.50

−1.954 −13.942*** −15.159***

47.55 13.58 30.74 5.93 2.20 44.52

49.96 34.28 46.16 23.63 14.67 49.72

1,808 1,808 1,808 1,808 1,808 1,793

4.14 14.14 38.85 28.72 14.14 75.50

19.94 34.86 48.76 45.26 34.86 43.02

−43.401*** 0.559 8.111*** 22.784*** 11.947*** 30.983***

1,000 1,000 1,000 1,000 1,000 1,000

77.15 9.20 13.43 12.19 17.70 15.38

42.01 28.92 34.11 32.73 38.19 36.09

1,344 1,344 1,344 1,344 1,344 1,344

81.67 6.82 12.24 4.25 56.54 8.92

38.70 25.22 32.79 20.17 49.59 28.52

4.527** −2.382 −1.188 −7.945*** 38.836*** −6.457***

Language spoken at home (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

1,164 1,164 1,164 1,164 1,164 1,164

55.04 8.74 5.88 12.37 0.48 17.50

49.77 28.25 23.53 32.93 6.92 38.01

1,808 1,808 1,808 1,808 1,808 1,808

67.30 7.80 7.67 5.98 1.46 9.79

46.93 26.83 26.62 23.72 11.99 29.72

12.255*** −0.935 1.794 −6.382*** 0.977*** −7.709***

Labor status (%) Employed Unemployed NEET Inactive

1,173 1,173 1,173 1,173

79.48 3.72 11.32 5.48

40.40 18.93 31.70 22.77

1,808 1,808 1,808 1,808

52.07 5.75 8.90 33.28

49.97 23.28 28.48 47.14

−27.410*** 2.029* −2.423 27.803***

Employment status (%) Formal employee Informal employee Self-employed

937 937 937

5.80 15.41 78.79

23.39 36.13 40.90

1,036 1,036 1,036

22.70 23.86 53.44

41.91 42.64 49.91

16.901*** 8.443*** −25.344***

Occupation (%) Low-skilled occupation Mid-skilled occupation High-skilled occupation

937 937 937

46.89 48.98 4.13

49.93 50.02 19.90

1,036 1,036 1,036

32.50 46.47 21.03

46.86 49.90 40.77

−14.391*** −2.507 16.898***

Economic sector (%) Agriculture, fishing, and mining Manufacturing Low- to mid-value-added High-value-added

937 937 937 937

16.26 10.83 66.05 6.87

36.92 31.09 47.38 25.31

1,036 1,036 1,036 1,036

8.17 9.64 56.46 25.73

27.41 29.53 49.60 43.74

−8.085*** −1.185 −9.591*** 18.861***

25–34 35–44 45–64

Difference: Y2 – Y1

table continues next page

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Differences in Mean

Table D.3 Difference in Mean of Those Answering Core Literacy Test and Those Who Did Not Answer It (continued) Y1: Did not answer Core Obs Earnings Monthly earnings Socioemotional skills Extraversion (score) Missing extraversion Conscientiousness (score) Missing conscientiousness Openness (score) Missing openness Emotional stability (score) Missing stability Agreeableness (score) Missing agreeableness Self-reported skills Reading Use reading skill Read with low intensity Read with medium intensity Read with high intensity Writing Use writing skill Write with low intensity Write with medium intensity Write with high intensity Numeracy Use numeracy skill Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity Computer Use computer skill Computer with low intensity Computer with medium intensity Computer with high intensity Literacy assessment Reading Proficiency

Y2: Answered Core

Mean

Obs

Mean

910

477.44

1,421.51

1,083

549.53

1,702.99

336 1,179 333 1,179 327 1,179 320 1,179 323 1,179

2.50 72.99 3.11 73.33 2.90 73.58 2.71 74.03 2.90 73.85

0.65 44.42 0.59 44.24 0.67 44.11 0.58 43.87 0.67 43.96

1,584 1,808 1,579 1,808 1,581 1,808 1,574 1,808 1,579 1,808

2.55 13.26 3.22 13.29 3.13 13.32 2.72 13.79 3.07 13.33

0.60 33.92 0.58 33.95 0.57 33.99 0.56 34.49 0.62 34.00

0.044 −59.736*** 0.103** −60.045*** 0.228*** −60.264*** 0.010 −60.237*** 0.168*** −60.526***

1,172 444 444 444

37.08 73.13 15.66 11.21

48.32 44.38 36.38 31.58

1,808 1,579 1,579 1,579

88.24 39.89 26.11 34.00

32.22 48.98 43.94 47.39

51.163*** −33.245*** 10.452*** 22.792***

1,172 415 415 415

34.27 86.94 8.39 4.67

47.48 33.74 27.76 21.13

1,808 1,512 1,512 1,512

84.00 68.08 17.30 14.62

36.67 46.63 37.84 35.35

49.732*** −18.858*** 8.906*** 9.952***

1,172 1,093 1,093 1,093

92.27 44.80 53.33 1.87

26.73 49.75 49.91 13.55

1,808 1,724 1,724 1,724

95.85 19.71 61.26 19.03

19.94 39.79 48.73 39.27

3.588*** −25.084*** 7.923*** 17.161***

1,168 67 67 67

5.20 39.31 17.97 42.71

22.22 49.21 38.69 49.84

1,808 710 710 710

42.14 33.90 17.65 48.46

49.39 47.37 38.15 50.01

36.936*** −5.418 −0.326 5.744

90.66

1,808

165.16

74.498***

1,179

Note: NEET = not in employment, education, or training; Obs = number of observations. *** p < 0.01, ** p < 0.05, * p < 0.1.

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Difference: Y2 – Y1 72.094

Differences in Mean

Table D.4 Difference in Mean of Those Missing and Those English Illiterate Y1: Missing Obs

Mean

Female (%) Socioeconomic status (%) Low Middle High

520

Y2: English illiterate SD

Obs

Mean

Difference: Y2 – Y1

64.61

47.86

659

75.12

43.27

10.505***

503 503 503

24.30 54.03 21.67

42.93 49.89 41.24

656 656 656

36.07 48.08 15.84

48.06 50.00 36.54

11.774*** −5.946 −5.828**

Age range (years) (%) 15–19 20–24 25–34 35–44 45–64

520 520 520 520 520 520

36.99 5.38 11.12 30.36 24.68 28.46

12.37 22.59 31.47 46.03 43.16 45.17

659 659 659 659 659 659

39.33 2.43 7.48 28.61 30.33 31.15

12.18 15.41 26.33 45.23 46.00 46.35

2.340** −2.953** −3.634* −1.752 5.648* 2.691

Education (%) No education Primary education Junior high school Senior high school Tertiary education Received early childhood education

520 520 520 520 520 504

17.72 13.80 51.23 12.40 4.86 61.33

38.22 34.52 50.03 32.98 21.53 48.75

659 659 659 659 659 651

72.14 13.41 13.85 0.60 0.00 30.96

44.87 34.10 34.57 7.74 0.00 46.27

54.422*** −0.390 −37.375*** −11.793*** −4.863*** −30.369***

Language spoken at work (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

430 430 430 430 430 430

85.02 12.25 16.67 5.44 32.98 7.76

35.73 32.83 37.31 22.71 47.07 26.79

570 570 570 570 570 570

70.99 6.82 10.90 17.46 5.77 21.33

45.42 25.22 31.19 38.00 23.34 41.00

−14.033*** −5.437** −5.771** 12.020*** −27.205*** 13.571***

Language spoken at home (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

505 505 505 505 505 505

66.54 11.32 8.60 4.78 0.99 7.78

47.23 31.71 28.06 21.35 9.92 26.81

659 659 659 659 659 659

45.85 6.68 3.70 18.43 0.07 25.27

49.87 24.98 18.89 38.80 2.68 43.49

−20.685*** −4.640** −4.898*** 13.652*** −0.921* 17.492***

Labor status (%) Employed Unemployed NEET Inactive

514 514 514 514

76.97 3.78 9.71 9.54

42.15 19.09 29.64 29.41

659 659 659 659

81.53 3.67 12.64 2.17

38.84 18.81 33.25 14.57

4.561 −0.111 2.925 −7.375***

Employment status (%) Formal employee Informal employee Self-employed

398 398 398

12.34 17.34 70.32

32.93 37.91 45.74

539 539 539

0.76 13.93 85.31

8.68 34.66 35.43

−11.580*** −3.407 14.987***

Occupation (%) Low-skilled occupation

398

48.29

50.03

539

45.81

49.87

−2.480

table continues next page

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Differences in Mean

Table D.4 Difference in Mean of Those Missing and Those English Illiterate (continued) Y1: Missing Obs

Mean

398 398

Economic sector (%) Agriculture, fishing, and mining Manufacturing Low- to mid-value-added High-value-added

Y2: English illiterate SD

Obs

Mean

45.18 6.53

49.83 24.73

539 539

51.91 2.28

50.01 14.93

6.732 −4.252**

398 398 398 398

10.25 12.63 63.77 13.35

30.37 33.26 48.13 34.06

539 539 539 539

20.89 9.43 67.81 1.87

40.69 29.26 46.76 13.56

10.634*** −3.197 4.044 −11.482***

Earnings Monthly earnings

391

564.52

1,390.53

519

409.79

1,442.84

308 520 306 520 301 520 295 520 297 520

2.51 44.56 3.11 45.19 2.93 45.67 2.70 46.37 2.93 46.24

0.66 49.75 0.59 49.82 0.66 49.86 0.57 49.92 0.66 49.91

28 659 27 659 26 659 25 659 26 659

2.38 96.43 3.12 96.53 2.55 96.59 2.85 96.83 2.55 96.62

0.51 18.57 0.56 18.31 0.70 18.16 0.72 17.54 0.69 18.10

−0.134 51.874*** 0.008 51.343*** −0.374** 50.919*** 0.145 50.462*** −0.382*** 50.374***

513 346 346 346

66.38 71.12 16.17 12.71

47.29 45.39 36.87 33.35

659 98 98 98

13.19 81.36 13.57 5.07

33.87 39.15 34.43 22.06

−53.189*** 10.234* −2.599 −7.635*

513 325 325 325

61.79 86.35 7.90 5.76

48.64 34.39 27.01 23.33

659 90 90 90

11.83 89.48 10.52 0.00

32.32 30.85 30.85 0.00

−49.965*** 3.138 2.618 −5.756***

513 482 482 482

93.13 34.18 61.98 3.84

25.32 47.48 48.59 19.24

659 611 611 611

91.56 53.60 46.16 0.24

27.82 49.91 49.89 4.85

−1.569 19.426*** −15.821*** −3.605***

509 64 64 64

10.92 38.87 18.66 42.46

31.22 49.13 39.27 49.82

659 3 3 3

0.59 50.79 0.00 49.21

7.65 61.23 0.00 61.23

−10.332*** 11.913 −18.664*** 6.750

73.49

659

Mid-skilled occupation High-skilled occupation

520

Note: NEET = not in employment, education, or training; Obs = number of observations. *** p < 0.01, ** p < 0.05, * p < 0.1.

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104.82

Difference: Y2 – Y1

−154.735

31.3294***

100

Differences in Mean

Table D.5 Difference in Mean of Those Answering the Socioemotional Section and Those Who Did Not Y1: Did not answer socioemotional section

Y2: Answered socioemotional section

Obs

Mean

Obs

Mean

Female (%)

1,045

73.60

44.10

1,930

49.32

50.01

−24.281***

Socioeconomic status (%) Low Middle High

1,038 1,038 1,038

35.69 48.58 15.73

47.93 50.00 36.43

1,922 1,922 1,922

15.44 60.27 24.29

36.15 48.95 42.89

−20.245*** 11.692*** 8.553***

Age range (years) (%) 15–19 20–24 25–34 35–44 45–64

1,045 1,045 1,045 1,045 1,045 1,045

37.79 3.91 9.21 30.09 28.49 28.30

12.02 19.40 28.93 45.89 45.16 45.07

1,930 1,930 1,930 1,930 1,930 1,930

30.41 20.12 22.45 27.05 13.98 16.41

12.75 40.10 41.74 44.43 34.68 37.04

−7.378*** 16.206*** 13.245*** −3.046 −14.514*** −11.891***

Education (%) No education Primary education JHS education SHS education Tertiary education Received ECE

1,045 1,045 1,045 1,045 1,045 1,029

54.16 16.41 27.35 2.05 0.03 41.24

49.85 37.06 44.60 14.18 1.63 49.25

1,930 1,930 1,930 1,930 1,930 1,907

2.33 12.66 40.34 29.87 14.81 76.03

15.07 33.26 49.07 45.78 35.53 42.70

−51.833*** −3.755** 12.986*** 27.819*** 14.783*** 34.783***

907 907 907 907 907 907

80.06 6.17 9.16 11.22 10.17 14.96

39.98 24.08 28.86 31.57 30.25 35.68

1,436 1,436 1,436 1,436 1,436 1,436

79.52 8.97 15.20 5.18 60.39 9.44

40.37 28.59 35.91 22.18 48.93 29.24

−0.544 2.799** 6.037*** −6.032*** 50.213*** −5.518***

Language spoken at home (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

1,045 1,045 1,045 1,045 1,045 1,045

60.78 5.61 3.92 11.84 0.04 17.81

48.85 23.02 19.41 32.32 2.06 38.28

1,927 1,927 1,927 1,927 1,927 1,927

63.73 9.54 8.68 6.49 1.66 9.89

48.09 29.39 28.16 24.65 12.79 29.85

2.952 3.936*** 4.765*** −5.347*** 1.621*** −7.928***

Labor status (%) Employed Unemployed NEET Inactive

1,045 1,045 1,045 1,045

79.95 3.64 11.72 4.69

40.05 18.73 32.18 21.15

1,930 1,930 1,930 1,930

52.85 5.73 8.76 32.67

49.93 23.25 28.28 46.91

−27.108*** 2.092** −2.960** 27.976***

Employment status (%) Formal employee Informal employee Self-employed

838 838 838

1.88 14.64 83.48

13.60 35.37 37.16

1,131 1,131 1,131

25.00 24.00 51.00

43.32 42.73 50.01

23.119*** 9.362*** −32.481***

Occupation (%) Low-skilled occupation

838

48.34

50.00

1,131

32.17

46.73

Language spoken at work (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

Difference: Y2 – Y1

−16.174*** table continues next page

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Differences in Mean

Table D.5 Difference in Mean of Those Answering the Socioemotional Section and Those Who Did Not (continued) Y1: Did not answer socioemotional section Obs

Mean

838 838

49.56 2.09

Economic sector (%) Agriculture, fishing, and mining Manufacturing Low- to mid-value-added High-value-added

838 838 838 838

Earnings Monthly earnings

Mid-skilled occupation High-skilled occupation

Self-reported skills Reading Don’t use read skill Read with low intensity Read with medium intensity Read with high intensity Writing Don’t use writing skill Write with low intensity Write with medium intensity Write with high intensity Numeracy Don’t use numeracy skill Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity Computer Don’t use computer skill Computer with low intensity Computer with medium intensity Computer with high intensity Literacy assessment Reading Component (average) Sentence missing (%) Sentence correct answers (%) Passage correct answers (%) Vocabulary correct answers (%) Core Score Core Test Passed Core Test Literacy assessment Reading Proficiency

Y2: Answered socioemotional section Obs

Mean

50.03 14.32

1,131 1,131

46.11 21.72

49.87 41.26

−3.458 19.633***

19.71 9.70 67.58 3.01

39.80 29.61 46.83 17.10

1,131 1,131 1,131 1,131

5.72 10.68 55.75 27.84

23.23 30.90 49.69 44.84

−13.985*** 0.984 −11.831*** 24.832***

804

402.45

1,217.70

1,184

602.31

1,803.02

1,040 1,040 1,040 1,040

72.62 21.96 3.59 1.84

44.61 41.42 18.60 13.44

1,901 1,901 1,901 1,901

8.85 37.50 23.44 30.21

28.41 48.43 42.37 45.93

−63.768*** 15.542*** 19.854*** 28.372***

1,043 1,043 1,043 1,043

75.34 22.34 1.71 0.61

43.13 41.67 12.99 7.77

1,911 1,911 1,911 1,911

12.94 60.03 14.65 12.38

33.57 49.00 35.37 32.95

−62.401*** 37.688*** 12.938*** 11.776***

1,045 1,045 1,045 1,045

6.93 43.97 48.68 0.42

25.41 49.66 50.01 6.44

1,930 1,930 1,930 1,930

4.74 18.28 58.73 18.26

21.25 38.66 49.24 38.64

−2.195* −25.699*** 10.055*** 17.840***

1,044 1,044 1,044 1,044

98.23 0.60 0.00 1.16

13.18 7.75 0.00 10.73

1,897 1,897 1,897 1,897

58.63 14.17 7.48 19.72

49.26 34.88 26.32 39.80

−39.600*** 13.562*** 7.482*** 18.555***

1,045 218 218 218

77.44 19.77 14.50 13.67

41.82 18.41 17.11 8.46

1,930 1,590 1,590 1,590

15.99 43.60 41.20 21.90

36.66 12.33 12.38 3.81

−61.450*** 23.827*** 26.704*** 8.230***

218 847

0.59 2.15

1.31 14.50

1,590 1,620

4.95 75.00

2.71 43.31

4.357*** 72.856***

77.54

1,930

169.10

91.556***

1,045

Note: NEET = not in employment, education, or training; Obs = number of observations. *** p < 0.01, ** p < 0.05, * p < 0.1.

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Difference: Y2 – Y1

199.860**

Appendix E

Returns to Education and Skills

Table E.1 Returns to Years of Education (Mincer Equation), Controlling for Skills No controls Years of education

Literacy Job-specific Socioeconomic assessment Personality Use of skills skills All controls

0.1019*** (0.0111)

0.0898*** (0.0180)

0.0956*** (0.0135)

0.0802*** (0.0135)

0.0017 (0.1460) 0.4564** (0.1915) 0.1216 (0.1955) 0.0430 (0.2930) −0.0304 (0.1988) 0.0479 (0.1503)

0.0843*** (0.0126)

0.0632*** (0.0168) 0.0228 (0.1387) 0.2193 (0.2118) 0.0110 (0.1820) 0.0589 (0.2870) 0.0138 (0.1958) 0.0085 (0.1711)

−0.2853 (0.1742) −0.3427* (0.2007) −0.4598** (0.2241)

−0.2766* (0.1655) −0.4154** (0.2037) −0.5218** (0.2185) table continues next page

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104

Returns to Education and Skills

Table E.1 Returns to Years of Education (Mincer Equation), Controlling for Skills (continued) No controls

Literacy Job-specific Socioeconomic assessment Personality Use of skills skills All controls

Writing Write with low intensity Write with medium intensity Write with high intensity Numeracy Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity

0.4973*** (0.1578) 0.8394*** (0.1913) 0.8989*** (0.2746)

0.4204** (0.1746) 0.8296*** (0.2183) 0.8828*** (0.3125)

0.0310 (0.1996) 0.3047** (0.1510) 0.3670 (0.2665)

−0.0623 (0.1991) 0.1953 (0.1636) 0.2565 (0.2658)

Job-specific skills Cognitive challenge Low think and learn Medium think and learn High think and learn Physical Low physical demand Medium physical demand High physical demand Autonomy and repetitiveness Low autonomy and repetitive Medium autonomy and repetitive High autonomy and repetitive Make presentations Supervise others

−0.0004 (0.1358) 0.1657 (0.1380) 0.0314 (0.1851)

−0.0649 (0.1252) 0.1059 (0.1359) 0.0003 (0.1615)

−0.1321 (0.1782) −0.0698 (0.1842) 0.0529 (0.1730)

−0.0895 (0.1969) −0.0717 (0.1907) 0.1037 (0.1801)

0.0838 (0.1580) 0.1405 (0.2023) −0.0986 (0.2574) −0.0138 (0.2261) 0.2121 (0.1297)

0.0747 (0.1274) 0.1079 (0.1703) −0.0269 (0.2419) −0.1471 (0.2226) 0.2407** (0.1131)

table continues next page

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Returns to Education and Skills

Table E.1 Returns to Years of Education (Mincer Equation), Controlling for Skills (continued) No controls

Literacy Job-specific Socioeconomic assessment Personality Use of skills skills All controls

Computer use at work (relative to no use) Computer work with low intensity Computer work with medium intensity Computer work with high intensity Reading proficiency Sentence correct answers (%) Passage correct answers (%) Vocabulary correct answers (%) Passed Core test Failed Core test Number of observations R2

675 0.228

−0.0040 (0.0058) 0.0116* (0.0067) −0.0044 (0.0141) −0.0220 (0.2915) −0.0846 (0.2127) 675 0.239

675 0.235

675 0.283

0.0272 (0.2801) 0.4043 (0.2760) 0.3084 (0.2124)

−0.0526 (0.2717) 0.3359 (0.2886) 0.2992 (0.1873)

675 0.265

−0.0063 (0.0054) 0.0096 (0.0063) 0.0072 (0.0137) −0.0915 (0.2664) −0.1091 (0.1990) 675 0.329

Note: All models estimated using ordinary least squares. Excluding self-employed. Robust standard errors are in parentheses. Controls include experience, experience squared, gender, economic sector and dummies for region. For all skills dummies of nonresponse (missing) were created and included in the regression, but they are not displayed in the table. Dependent variable is monthly earning considering main and second occupation. *** p < 0.01, ** p < 0.05, * p < 0.1.

Table E.2 Returns to Education Level (Mincer Equation), Controlling for Skills No controls Education level (relative to none) Primary education (%) 0.3186* (0.1834) Junior high school (%) 0.5921*** (0.1548) Senior high school (%) 0.7882*** (0.2160) Tertiary education (%) 1.7174*** (0.1681)

Socioeconomic

Literacy assessment

Personality

Use of skills

0.3186* (0.1834) 0.5921*** (0.1548) 0.7882*** (0.2160) 1.7174*** (0.1681)

0.2609 (0.1989) 0.4815*** (0.1640) 0.5513* (0.2978) 1.4883*** (0.2584)

0.2408 (0.1937) 0.4413*** (0.1537) 0.5791** (0.2353) 1.4939*** (0.2040)

0.1857 (0.1683) 0.4197*** (0.1487) 0.5097** (0.2057) 1.3415*** (0.2050)

Job-specific skills All controls 0.3176* (0.1829) 0.5858*** (0.1558) 0.6962*** (0.2132) 1.5899*** (0.2082)

0.1388 (0.1872) 0.3525** (0.1523) 0.2917 (0.2465) 1.1183*** (0.2618)

table continues next page

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Returns to Education and Skills

Table E.2 Returns to Education Level (Mincer Equation), Controlling for Skills (continued) No controls

Socioeconomic

Socioemotional skills (relative to score 2 or lower) Extraversion>2 Conscientiousness>2 Openness>2 Stability>2 Agreeableness>2 Grit>2 Cognitive skills (relative to skill not used) Reading Read with low intensity Read with medium intensity Read with high intensity Writing Write with low intensity Write with medium intensity Write with high intensity Numeracy Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity

Literacy assessment

Personality

Use of skills

Job-specific skills All controls

−0.0158 (0.1370) 0.4631** (0.1987) 0.0709 (0.1968) 0.0593 (0.3046) −0.0460 (0.1975) 0.0008 (0.1480)

0.0338 (0.1327) 0.2422 (0.2141) −0.0060 (0.1836) 0.0872 (0.2903) 0.0049 (0.2018) −0.0430 (0.1547)

−0.2164 (0.1581) −0.2754 (0.1824) −0.3958** (0.2013)

−0.2617* (0.1561) −0.3666* (0.1906) −0.4742** (0.2002)

0.5616*** (0.1515) 0.8029*** (0.1921) 0.9096*** (0.2677)

0.4663*** (0.1691) 0.7854*** (0.2151) 0.8858*** (0.2894)

0.0125 (0.1921) 0.2467 (0.1598) 0.1919 (0.2668)

−0.0881 (0.1912) 0.1257 (0.1702) 0.1478 (0.2586)

Job-specific skills (relative to score 0) Cognitive challenge Low think and learn Medium think and learn

0.0172 (0.1349)

−0.0554 (0.1217)

0.1504 (0.1377)

0.0822 (0.1345)

table continues next page

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Returns to Education and Skills

Table E.2 Returns to Education Level (Mincer Equation), Controlling for Skills (continued) No controls

Socioeconomic

Literacy assessment

Personality

Use of skills

High think and learn Physical Low physical demand Medium physical demand High physical demand Autonomy and repetitiveness Low autonomy and repetitive Medium autonomy and repetitive High autonomy and repetitive Make presentations Supervise others Computer use at work (relative to no use) Computer use with low intensity Computer use with medium intensity Computer use with high intensity Reading proficiency Sentence correct answers (%) Passage correct answers (%) Vocabulary correct answers (%) Passed Core test Failed Core test Number of observations R2

675 0.270

−0.0072 (0.0057) 0.0137** (0.0064) 0.0012 (0.0136) −0.0134 (0.2965) −0.0098 (0.2288) 675 0.286

675 0.281

675 0.320

Job-specific skills All controls −0.0431 (0.1782)

−0.0686 (0.1563)

−0.0731 (0.1816) 0.0414 (0.1878) 0.1540 (0.1677)

−0.0208 (0.1943) 0.0441 (0.1879) 0.2231 (0.1737)

0.0327 (0.1379) 0.0177 (0.1740) −0.1011 (0.2393) −0.0298 (0.2309) 0.2123* (0.1259)

0.0274 (0.1149) −0.0071 (0.1538) −0.0259 (0.2214) −0.1428 (0.2146) 0.2320** (0.1084)

0.0029 (0.2832) 0.2490 (0.2935) 0.1793 (0.1855)

−0.0624 (0.2744) 0.1699 (0.3049) 0.1872 (0.1708)

675 0.298

−0.0088 (0.0055) 0.0117* (0.0061) 0.0099 (0.0133) −0.0607 (0.2764) −0.0526 (0.2163) 675 0.364

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Returns to Education and Skills

Table E.3 Returns to Years of Education (Mincer Equation) for Informal Wageworkers, Controlling for Skills

Years of education

No controls

Socioeconomic

Literacy assessment

Use of skills

Job-specific skills

All controls

0.0591*** (0.0132)

0.0667*** (0.0163)

0.0513*** (0.0157)

0.0431*** (0.0142)

0.0508*** (0.0132)

0.0392*** (0.0153)

0.2324* (0.1401) 0.3148 (0.2440) 0.0927 (0.2083) 0.1037 (0.2398) 0.0063 (0.2609) (−0.1268) (0.1511)

0.2113** (0.1384) 0.1219 (0.2126) 0.1104 (0.2005) 0.0595 (0.2302) 0.0704 (0.2514) (−0.2334) (0.1461)

−0.3320** (0.1696) −0.3557** (0.2048) −0.3564* (0.2127)

−0.2426 (0.1685) −0.2863 (0.2059) −0.3573 (0.2050)

0.5207*** (0.1568) 0.6020*** (0.2254) 1.2538*** (0.3060)

0.4269*** (0.1701) 0.5452*** (0.2230) 1.2017*** (0.3337)

−0.0310 (0.1867) 0.0421 (0.1753) −0.1045 (0.2778)

−0.2354* (0.1883) −0.1644 (0.1915) −0.1206 (0.2866)

−0.0847 (0.1224) 0.0201 (0.1491) 0.1683 (0.1781)

−0.1587 (0.1164) −0.0215 (0.1535) 0.1503 (0.1705)

table continues next page

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Table E.3 Returns to Years of Education (Mincer Equation) for Informal Wageworkers, Controlling for Skills (continued)

No controls

Socioeconomic

Literacy assessment

Use of skills

Physical Low physical demand Medium physical demand High physical demand Autonomy and repetitiveness Low autonomy and repetitive Medium autonomy and repetitive High autonomy and repetitive Make presentations Supervise others Computer use at work (relative to no use) Computer use with low intensity Computer use with medium intensity Computer use with high intensity Reading proficiency Sentence correct answers (%)

All controls

0.0114 (0.1843) 0.1611 (0.2098) 0.4199 (0.1748)

0.0691 (0.2108) 0.1819 (0.2256) 0.4646 (0.2112)

−0.0737 (0.1043) −0.1788 (0.1860) −0.3558 (0.1866) −0.1404 (0.2063) 0.3356* (0.1327)

−0.0447 (0.1072) −0.1817 (0.1923) −0.1763 (0.2018) −0.1978* (0.1868) 0.3211** (0.1298)

0.4667 (0.3951) 0.2478 (0.3652) 0.1323** (0.2700)

0.3215 (0.3338) −0.1337 (0.5208) 0.0676* (0.2438)

(−0.0037) (0.0068) (0.0101) (0.0073) (−0.0090) (0.0161) (−0.2260) (0.3442) −0.0133 (0.2371)

Passage correct answers (%) Vocabulary correct answers (%) Passed Core test Failed Core test Number of observations R2

Job-specific skills

(−0.0100) (0.0068) (0.0112) (0.0078) (0.0029) (0.0157) (−0.2427) (0.3458) 0.0380 (0.2401)

387

0.098

0.108

0.125

0.186

0.192

0.300

Note: All models estimated using ordinary least squares. Robust standard errors are in parentheses. Controls include experience, experience squared, gender, economic sector, and dummies for region. For all skills dummies of nonresponse (missing) were created and included in the regression, but they are not displayed in the table. Dependent variable is monthly earning considering main and second occupation. *** p < 0.01, ** p < 0.05, * p < 0.1.

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Table E.4 Returns to Education Level (Mincer Equation) for Informal Wageworkers, Controlling for Skills No controls Education level (relative to none) Primary education (%) 0.2856 (0.1899) Junior high school (%) 0.3940*** (0.1469) Senior high school (%) 0.6408*** (0.1699) Tertiary education (%) 1.1907*** (0.3063)

Socioeconomic Literacy assessment Use of skills 0.2883 (0.1945) 0.4268*** (0.1499) 0.7543*** (0.2173) 1.3209*** (0.3383)

0.2390 (0.2090) 0.3244* (0.1716) 0.5273** (0.2092) 1.0638*** (0.3128)

0.2093 (0.1734) 0.3360** (0.1590) 0.5258*** (0.1920) 0.8967*** (0.2973)

0.2066 (0.1347) 0.3094 (0.2498) 0.0463 (0.2094) 0.1368 (0.2640) −0.0205 (0.2606) −0.1343 (0.1531)

Job-specific skills All controls 0.3256* (0.1895) 0.3970*** (0.1436) 0.5829*** (0.1789) 1.1197*** (0.2869)

0.1215 (0.2034) 0.2673* (0.1585) 0.4845** (0.2154) 0.9016*** (0.2699) 0.1925 (0.1365) 0.1052 (0.2156) 0.0944 (0.2016) 0.0888 (0.2385) 0.0504 (0.2586) −0.2493* (0.1469)

−0.3387** (0.1611) −0.3869* (0.2032) −0.4016* (0.2137)

−0.2445 (0.1637) −0.2993 (0.2064) −0.3925* (0.2040)

0.5317*** (0.1556) 0.6135*** (0.2270) 1.1775*** (0.3292)

0.4376*** (0.1669) 0.5278** (0.2191) 1.1263*** (0.3317)

−0.0352 (0.1904)

−0.2713 (0.1874) table continues next page

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Returns to Education and Skills

Table E.4 Returns to Education Level (Mincer Equation) for Informal Wageworkers, Controlling for Skills (continued)

No controls

Socioeconomic Literacy assessment Use of skills

Numeracy with medium intensity

0.0155 (0.1785) −0.1288 (0.2807)

Numeracy with high intensity Job-specific skills (relative to score 0) Cognitive challenge Low think and learn Medium think and learn High think and learn Physical Low physical demand Medium physical demand High physical demand Autonomy and repetitiveness Low autonomy and repetitive Medium autonomy and repetitive High autonomy and repetitive Make presentations Supervise others Computer use at work (relative to no use) Computer use with low intensity Computer use with medium intensity Computer use with high intensity Reading proficiency Sentence correct answers (%)

Job-specific skills All controls

−0.0038 (0.0068)

−0.2245 (0.1911) −0.1731 (0.2806)

−0.0825 (0.1193) 0.0005 (0.1493) 0.1528 (0.1736)

−0.1535 (0.1146) −0.0370 (0.1548) 0.1491 (0.1663)

0.0552 (0.1880) 0.2426 (0.2072) 0.4886*** (0.1771)

0.1066 (0.2030) 0.2305 (0.2161) 0.5131** (0.2024)

−0.0889 (0.1035) −0.1960 (0.1909) −0.3438* (0.1905) −0.1499 (0.2114) 0.3106** (0.1278)

−0.0595 (0.1039) −0.1992 (0.1969) −0.1597 (0.2027) −0.2023 (0.1891) 0.3119** (0.1301)

0.3657 (0.3604) 0.1611 (0.4063) 0.0307 (0.2671)

0.2876 (0.3321) −0.2094 (0.5478) −0.0090 (0.2430) −0.0104 (0.0069)

table continues next page

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Returns to Education and Skills

Table E.4 Returns to Education Level (Mincer Equation) for Informal Wageworkers, Controlling for Skills (continued)

No controls Passage correct answers (%)

Job-specific skills All controls

0.0086 (0.0072) −0.0046 (0.0159) −0.2775 (0.3481) 0.0203 (0.2392)

Vocabulary correct answers (%) Passed Core test Failed Core test Number of observations R2

Socioeconomic Literacy assessment Use of skills

387 0.116

387 0.126

0.0110 (0.0079) 0.0051 (0.0158) −0.2738 (0.3502) 0.0681 (0.2489) 387 0.142

387 0.194

387 0.207

387 0.310

Note: All models estimated using ordinary least squares. Robust standard errors are in parentheses. Controls include experience, experience squared, gender, economic sector and dummies for region. For all skills dummies of non-response (missing) were created and included in the regression, but they are not displayed in the table. Dependent variable is monthly earning considering main and second occupation. JHS = junior high school; SHS = senior high school. *** p < 0.01, ** p < 0.05, * p < 0.1.

Table E.5 Returns to Years of Education (Mincer Equation) for Formal Wageworkers, Controlling for Skills No controls Socioeconomic Literacy assessment Use of skills Years of education

0.0944*** (0.0273)

0.0749** (0.0359)

0.1025*** (0.0268)

0.0918*** (0.0319)

−0.3074* (0.1859) 0.6214* (0.3329) −0.1851 (0.2369) −0.1854 (0.4990) −0.2409 (0.2402) 0.3177 (0.2913)

Job-specific skills

All controls

0.0946*** (0.0353)

0.0914*** (0.0320) −0.3692* (0.2155) 0.3945 (0.4364) −0.1046 (0.2385) −0.0490 (0.4707) −0.3834 (0.2700) 0.3255 (0.2965)

−0.0587 (0.3558)

−0.2557 (0.3472) table continues next page

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Table E.5 Returns to Years of Education (Mincer Equation) for Formal Wageworkers, Controlling for Skills (continued)

No controls Socioeconomic Literacy assessment Use of skills Read with medium intensity Read with high intensity Writing Write with low intensity Write with medium intensity Write with high intensity Numeracy Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity

Job-specific skills

All controls

−0.1809 (0.3793) −0.3465 (0.3646)

−0.4497 (0.4015) −0.5582 (0.3905)

0.2104 (0.2699) 0.4048 (0.2860) 0.3263 (0.3529)

−0.0757 (0.3083) 0.1047 (0.3381) 0.1177 (0.3707)

−0.0341 (0.3980) 0.5189** (0.2194) 0.3131 (0.3604)

0.0043 (0.3314) 0.3861 (0.2554) 0.2708 (0.3435)

0.1443 (0.2725) 0.2753 (0.2501) −0.2385 (0.3188)

0.2795 (0.2631) 0.4169* (0.2508) 0.0778 (0.2652)

0.0282 (0.2477) −0.0172 (0.2335) −0.1174 (0.2795)

−0.1511 (0.2695) −0.2942 (0.2392) −0.2737 (0.2728)

0.2523 (0.2804) 0.2755 (0.3134)

0.2650 (0.2098) 0.2476 (0.2647)

table continues next page

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Returns to Education and Skills

Table E.5 Returns to Years of Education (Mincer Equation) for Formal Wageworkers, Controlling for Skills (continued)

No controls Socioeconomic Literacy assessment Use of skills High autonomy and repetitive Make presentations Supervise others Computer use at work (relative to no use) Computer use with low intensity Computer use with medium intensity Computer use with high intensity Reading proficiency Sentence correct answers (%) Passage correct answers (%) Vocabulary correct answers (%) Passed Core test Failed Core test Number of observations R2

288 0.093

Job-specific skills

All controls

0.7046 (0.4544) −0.0052 (0.3045) 0.0980 (0.1961)

0.9453** (0.4556) −0.0519 (0.2646) 0.1014 (0.1496)

−0.2233 (0.3276) 0.4662** (0.1962) 0.1477 (0.2220)

−0.1649 (0.3313) 0.5208** (0.2286) 0.0986 (0.2147)

−0.0115 (0.0079) 0.0107 (0.0089) 0.0043

−0.0108 (0.0084) 0.0048 (0.0099) 0.0181

(0.0175) 0.4454 (0.4625) 0.0791 (0.4179)

(0.0193) 0.2707 (0.4119) −0.1837 (0.3463)

288 0.134

288 0.125

288 0.158

288 0.170

288 0.277

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Table E.6 Returns to Education Level (Mincer Equation) for Formal Wageworkers, Controlling for Skills

No controls Education level (relative to none) Primary education (%) 0.2928 (0.4344) JHS education (%) 0.4450 (0.3439) SHS education (%) 0.2360 (0.4336) Tertiary education (%) 1.1384*** (0.3398)

Socioeconomic

Literacy assessment

Use of skills

0.0374 (0.6760) 0.1683 (0.3831) −0.1607 (0.5481) 0.7088 (0.4805)

0.2616 (0.4813) 0.2855 (0.3214) 0.1456 (0.4459) 1.0394*** (0.3549)

−0.0484 (0.4963) 0.2182 (0.3345) −0.0278 (0.4512) 0.8243* (0.4251)

Socioemotional skills (relative to score 2 or lower) Extraversion>2 Conscientiousness>2 Openness>2 Stability>2 Agreeableness>2 Grit>2 Cognitive Skills (relative to skill not used) Reading Read with low intensity

−0.2490 (0.1744) 0.4825* (0.2737) −0.3270 (0.2264) −0.1719 (0.4698) −0.1443 (0.2345) 0.2738 (0.2522)

Job-specific skills 0.4489 (0.5645) 0.4958 (0.3275) 0.2834 (0.3710) 1.2545*** (0.3818)

All controls 0.1584 (0.6628) 0.3042 (0.3958) 0.1042 (0.4470) 0.9646** (0.4473) −0.2514 (0.1946) 0.2224 (0.3698) −0.2816 (0.2647) −0.0512 (0.4299) −0.2504 (0.2619) 0.2488 (0.2557)

0.1837 (0.3971) 0.1256 (0.4144) −0.0101 (0.3943)

−0.1505 (0.3778) −0.2512 (0.4191) −0.3388 (0.4239)

Write with high intensity

0.2481 (0.2696) 0.3944 (0.2878) 0.4449 (0.3438)

0.0166 (0.2880) 0.1636 (0.3235) 0.2797 (0.3437)

Numeracy Numeracy with low intensity

0.0016 (0.3639)

0.0034 (0.3262)

Read with medium intensity Read with high intensity Writing Write with low intensity Write with medium intensity

table continues next page

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Returns to Education and Skills

Table E.6 Returns to Education Level (Mincer Equation) for Formal Wageworkers, Controlling for Skills (continued)

No controls

Socioeconomic

Numeracy with medium intensity

Use of skills

Job-specific skills

0.5156** (0.2395) 0.2631 (0.3622)

Literacy assessment

−0.0129 (0.0086)

All controls 0.3465 (0.2675) 0.2520 (0.3446)

0.2136 (0.2573) 0.2371 (0.2395) −0.3254 (0.2974)

0.2547 (0.2456) 0.3076 (0.2403) −0.0825 (0.2671)

0.1116 (0.2456) 0.1269 (0.2557) 0.0359 (0.2729)

−0.0010 (0.2631) −0.1099 (0.2496) −0.0434 (0.2704)

0.1599 (0.2377) 0.0943 (0.2618) 0.5873 (0.3939) 0.0141 (0.2859) 0.1955 (0.1844)

0.1615 (0.1891) 0.0690 (0.2359) 0.7399* (0.3807) −0.0667 (0.2522) 0.1946 (0.1543)

−0.1210 (0.3586) 0.2826 (0.1787) 0.0900 (0.1963)

−0.1003 (0.3482) 0.3083 (0.1962) 0.0659 (0.1986) −0.0117 (0.0081)

table continues next page

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Table E.6 Returns to Education Level (Mincer Equation) for Formal Wageworkers, Controlling for Skills (continued)

No controls Passage correct answers (%)

Literacy assessment

Use of skills

Job-specific skills

All controls

0.0183* (0.0101) −0.0015 (0.0165) 0.3477 (0.4756) 0.0700 (0.4205)

Vocabulary correct answers (%) Passed Core test Failed Core test Number of observations R2

Socioeconomic

288 0.157

288 0.208

0.0103 (0.0096) 0.0138 (0.0178) 0.2030 (0.4121) −0.1231 (0.3474) 288 0.182

288 0.216

288 0.236

288 0.322

Table E.7 Returns to Years of Education (Mincer Equation) for Male Workers, Controlling for Skills No controls Socioeconomic Years of education

0.0821*** (0.0156)

0.0686*** (0.0258)

Literacy assessment

Use of skills

Job-specific skills

All controls

0.0944*** (0.0174)

0.0806*** (0.0173)

0.0662*** (0.0172)

0.0624*** (0.0220)

−0.0059 (0.1703) 0.4383* (0.2357) −0.0065 (0.1801) −0.1271 (0.3880) −0.2579 (0.1941) 0.1604 (0.2199)

0.0422 (0.1637) −0.0224 (0.3114) −0.0437 (0.1831) −0.2001 (0.3785) −0.2465 (0.2005) 0.1718 (0.2288)

−0.3859* (0.2260)

−0.3590 (0.2206) table continues next page

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Table E.7 Returns to Years of Education (Mincer Equation) for Male Workers, Controlling for Skills (continued) No controls Socioeconomic Read with medium intensity Read with high intensity Writing Write with low intensity Write with medium intensity Write with high intensity Numeracy Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity Job-specific skills (relative to score 0) Cognitive challenge Low think and learn Medium think and learn High think and learn Physical Low physical demand Medium physical demand High physical demand Autonomy and repetitiveness Low autonomy and repetitive Medium autonomy and repetitive High autonomy and repetitive

Literacy assessment

Use of skills

Job-specific skills

All controls

−0.5224** (0.2427) −0.6218** (0.2819)

−0.5639** (0.2752) −0.5933** (0.2924)

0.4664** (0.2058) 0.6412** (0.2591) 0.8619** (0.3523)

0.5645** (0.2307) 0.7750** (0.3042) 0.9770** (0.3977)

0.2629 (0.2687) 0.4744** (0.1892) 0.4698 (0.3668)

0.2190 (0.2606) 0.3842* (0.2289) 0.2906 (0.3631)

−0.0341 (0.1921) 0.1034 (0.1757) −0.1847 (0.2354)

−0.0369 (0.1693) 0.1151 (0.1699) −0.1343 (0.2000)

−0.1036 (0.2332) −0.0518 (0.2431) −0.0943 (0.2201)

−0.1291 (0.2360) −0.1612 (0.2422) −0.1206 (0.2239)

0.1612 (0.2188) 0.2790 (0.2492) 0.0510 (0.3501)

0.1707 (0.1815) 0.2713 (0.2115) 0.1784 (0.3418)

table continues next page

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Table E.7 Returns to Years of Education (Mincer Equation) for Male Workers, Controlling for Skills (continued) No controls Socioeconomic

Literacy assessment

Use of skills

Make presentations Supervise others Computer use at work (relative to no use) Computer use with low intensity

Computer use with high intensity

Passage correct answers (%) Vocabulary correct answers (%) Passed Core test Failed Core test Number of observations R2

429 0.142

All controls

−0.0657 (0.2940) 0.2440 (0.1547)

−0.1311 (0.2691) 0.2224* (0.1307)

0.1596 (0.3874) 0.5847** (0.2976) 0.3244 (0.2750)

Computer use with medium intensity

Reading proficiency Sentence correct answers (%)

Job-specific skills

−0.0068 (0.0064) 0.0091 (0.0075) 0.0064 (0.0168) 0.0079 (0.3671) −0.0972 (0.2759) 429 0.154

429 0.157

429 0.195

429 0.194

0.1160 (0.3717) 0.4686 (0.3126) 0.3399 (0.2454) −0.0074 (0.0064) 0.0070 (0.0074) 0.0197 (0.0156) −0.0787 (0.3641) −0.2103 (0.2484) 429 0.271

Note: All models estimated using ordinary least squares. Robust standard errors are in parentheses. Controls include experience, experience squared, gender, economic sector, and dummies for region. For all skills dummies of nonresponse (missing ) were created and included in the regression, but they are not displayed in the table. Dependent variable is monthly earning considering main and second occupation. *** p < 0.01, ** p < 0.05, * p < 0.1.

Table E.8 Returns to Education Level (Mincer Equation) for Male Workers, Controlling for Skills No controls Education level (relative to none) Primary education (%) 0.0169 (0.2009) Junior high school (%) 0.3425** (0.1645) Senior high school (%)

0.3803 (0.2696)

Socioeconomic

Literacy assessment

Use of skills

Job-specific skills

All controls

−0.0538 (0.2217) 0.1980 (0.1802)

0.0343 (0.2200) 0.3531** (0.1716)

−0.0514 (0.2000) 0.3072* (0.1788)

0.0684 (0.2066) 0.3531** (0.1687)

0.0198 (0.2194) 0.2752 (0.1900)

0.1119 (0.3837)

0.4190 (0.2924)

0.3132 (0.2594)

0.3598 (0.2601)

0.1930 (0.3096)

table continues next page

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Table E.8 Returns to Education Level (Mincer Equation) for Male Workers, Controlling for Skills (continued) No controls Tertiary education (%)

1.3544*** (0.1928)

Socioeconomic 1.1057*** (0.3225)

Literacy assessment 1.3990*** (0.2354)

Use of skills

Job−specific skills

All controls

1.3153*** (0.2526)

1.3461*** (0.2648)

1.1786*** (0.3298)

0.0021 (0.1588) 0.3845* (0.2291) −0.0416 (0.1734) −0.1689 (0.3825) −0.2124 (0.1873) 0.0783 (0.2118)

0.0786 (0.1556) −0.0435 (0.2742) −0.0800 (0.1782) −0.2126 (0.3580) −0.2296 (0.1970) 0.0887 (0.2013)

−0.2334 (0.2209) −0.3417 (0.2295) −0.4847* (0.2579)

−0.2992 (0.2153) −0.4566* (0.2540) −0.5189* (0.2686)

0.4947** (0.2058) 0.5499** (0.2516) 0.8401** (0.3374)

0.5589** (0.2312) 0.6607** (0.2985) 0.9446** (0.3696)

0.2834 (0.2392) 0.4737** (0.2014) 0.2603 (0.3515)

0.2168 (0.2483) 0.3465 (0.2385) 0.1549 (0.3530) table continues next page

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Table E.8 Returns to Education Level (Mincer Equation) for Male Workers, Controlling for Skills (continued) No controls

Socioeconomic

Literacy assessment

Use of skills

Job-specific skills (relative to score 0) Cognitive challenge Low think and learn Medium think and learn High think and learn Physical Low physical demand Medium physical demand High physical demand Autonomy and repetitiveness Low autonomy and repetitive Medium autonomy and repetitive High autonomy and repetitive Make presentations Supervise others Computer use at work (relative to no use) Computer use with low intensity Computer use with medium intensity Computer use with high intensity Reading proficiency Sentence correct answers (%) Passage correct answers (%)

−0.0112 (0.0069) 0.0149* (0.0078)

Job−specific skills

All controls

−0.0205 (0.1968) 0.1175 (0.1746) −0.2634 (0.2307)

−0.0157 (0.1684) 0.1261 (0.1655) −0.1828 (0.1932)

0.0281 (0.2289) 0.1739 (0.2480) 0.1060 (0.2077)

0.0124 (0.2245) 0.0532 (0.2398) 0.0863 (0.2173)

0.1165 (0.1886) 0.1580 (0.2116) 0.0369 (0.3103) −0.0655 (0.2923) 0.2130 (0.1505)

0.1432 (0.1605) 0.1665 (0.1890) 0.1470 (0.2957) −0.0975 (0.2533) 0.1847 (0.1231)

0.0905 (0.3887) 0.3364 (0.3220) 0.1473 (0.2261)

0.0623 (0.3746) 0.2039 (0.3327) 0.1806 (0.2148) −0.0097 (0.0067) 0.0106 (0.0074)

table continues next page

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Returns to Education and Skills

Table E.8 Returns to Education Level (Mincer Equation) for Male Workers, Controlling for Skills (continued) No controls Vocabulary correct answers (%)

Literacy assessment

Use of skills

Job−specific skills

0.0092 (0.0155) −0.0174 (0.3760) −0.0572 (0.2890)

Passed Core test Failed Core test Number of observations R2

Socioeconomic

All controls 0.0208 (0.0148) −0.1081 (0.3545) −0.1977 (0.2551)

429

0.205

0.228

0.214

0.256

0.243

0.319

Table E.9 Returns to Years of Education (Mincer Equation) for Female Workers, Controlling for Skills No controls Years of education

Socioeconomic

0.1248*** (0.0122)

0.1260*** (0.0173)

Literacy assessment 0.1092*** (0.0183)

Use of skills 0.0939*** (0.0180)

0.0796 (0.1718) −0.0219 (0.3320) −0.0474 (0.3065) 0.3484 (0.3328) 0.6757* (0.3852) −0.1010 (0.1875)

Job-specific skills 0.1103*** (0.0170)

All controls 0.0886*** (0.0204) 0.0980 (0.1541) −0.2704 (0.3749) −0.4414 (0.3278) 0.5365* (0.3052) 0.7056* (0.3919) −0.3204* (0.1941)

−0.0896 (0.2482) −0.0275 (0.3582) −0.1740 (0.3050)

−0.1866 (0.2422) −0.0439 (0.3606) −0.2822 (0.2868) table continues next page

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Returns to Education and Skills

Table E.9 Returns to Years of Education (Mincer Equation) for Female Workers, Controlling for Skills (continued) No controls Writing Write with low intensity Write with medium intensity Write with high intensity Numeracy Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity

Socioeconomic

Literacy assessment

Use of skills

Job-specific skills

0.2225 (0.2531) 0.8702*** (0.2724) 0.5741 (0.3906)

0.1639 (0.2464) 0.8462*** (0.2701) 0.4050 (0.3540)

−0.2961 (0.1958) −0.0280 (0.1865) 0.1788 (0.2565)

All controls

−0.3563* (0.1955) −0.0250 (0.1906) 0.2868 (0.2959)

−0.0188 (0.1904) 0.1362 (0.1929) 0.2075 (0.2390)

−0.0368 (0.1543) 0.0164 (0.1665) 0.1928 (0.2169)

−0.1409 (0.2323) −0.2135 (0.2664) 0.1024 (0.2267)

−0.1024 (0.2868) −0.1550 (0.2870) 0.1532 (0.2643)

−0.0378 (0.1500) −0.1028 (0.2240) −0.3109 (0.2452) 0.1021 (0.2217) 0.0606 (0.2088)

0.0739 (0.1250) −0.1493 (0.2157) −0.1523 (0.3167) −0.0914 (0.1969) 0.2123 (0.1690)

table continues next page

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Returns to Education and Skills

Table E.9 Returns to Years of Education (Mincer Equation) for Female Workers, Controlling for Skills (continued) No controls

Socioeconomic

Literacy assessment

Use of skills

Computer use at work (relative to no use) Computer use with low intensity Computer use with medium intensity Computer use with high intensity Reading proficiency Sentence correct answers (%)

All controls

−0.1790 (0.3608) −0.5476 (0.4123)

−0.3520 (0.4408) −0.6718 (0.4293)

0.2913 (0.2810)

0.3859* (0.2111)

−0.0073 (0.0098) 0.0110 (0.0102) −0.0088 (0.0202) −0.0018 (0.4059) −0.0935 (0.3014)

Passage correct answers (%) Vocabulary correct answers (%) Passed Core test Failed Core test Number of observations R2

Job-specific skills

246 0.401

246 0.413

−0.0126 (0.0084) 0.0120 (0.0104) −0.0052 (0.0190) 0.0561 (0.3695) 0.0858 (0.3175) 246 0.445

246 0.462

246 0.439

246 0.559

Table E.10 Returns to Education Level (Mincer Equation) for Female Workers, Controlling for Skills No controls Education Level (relative to none) Primary education (%) 0.2825 (0.2219) Junior high school (%) 0.5477*** (0.2013) Senior high school (%) 1.0766*** (0.2110) Tertiary education (%) 1.9808*** (0.2128)

Socioeconomic

Literacy assessment

Use of skills

Job-specific skills

All controls

0.2438 (0.2306) 0.5532** (0.2158) 1.1053*** (0.2679) 2.0489*** (0.2928)

0.1458 (0.2219) 0.4536** (0.2198) 0.9449*** (0.2714) 1.8514*** (0.2755)

0.3042 (0.2485) 0.4565** (0.2105) 0.8253*** (0.2605) 1.6017*** (0.2955)

0.2806 (0.2328) 0.5437*** (0.2003) 1.0569*** (0.2487) 1.9526*** (0.2808)

0.0419 (0.2410) 0.4290* (0.2272) 0.7940*** (0.3078) 1.6394*** (0.3437)

table continues next page

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Returns to Education and Skills

Table E.10 Returns to Education Level (Mincer Equation) for Female Workers, Controlling for Skills (continued) No controls

Socioeconomic

Literacy assessment

Use of skills

0.0386 (0.1643) −0.2087 (0.3219) −0.2421 (0.2903) 0.4671 (0.3625) 0.5900 (0.3774) −0.0939 (0.1880)

Job-specific skills

All controls

0.1002 (0.1574) −0.4056 (0.3695) −0.4383 (0.3224) 0.6062* (0.3330) 0.6056 (0.3996) −0.3274* (0.1909)

−0.1334 (0.1876) −0.1886 (0.3042) −0.2695 (0.2808) 0.3236 (0.2136) 0.8419*** (0.2622) 0.5962 (0.4008) −0.3490* (0.1895) −0.1930 (0.1857) −0.0451 (0.2632)

−0.2002 (0.2046) −0.2094 (0.3423) −0.3422 (0.2672) 0.2774 (0.2065) 0.8777*** (0.2356) 0.4322 (0.3281) −0.4421** (0.1827) −0.1827 (0.1776) 0.1409 (0.2830) table continues next page

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Returns to Education and Skills

Table E.10 Returns to Education Level (Mincer Equation) for Female Workers, Controlling for Skills (continued) No controls

Socioeconomic

−0.0082 (0.0091) 0.0077 (0.0095) −0.0047 (0.0211)

Literacy assessment

Use of skills

Job-specific skills

All controls

−0.0642 (0.1707) −0.0388 (0.1736) 0.0030 (0.2210)

−0.0479 (0.1434) −0.0624 (0.1660) 0.0947 (0.2173)

−0.0583 (0.2353) −0.1113 (0.2470) 0.1334 (0.2232)

−0.1043 (0.2800) −0.1502 (0.2757) 0.1088 (0.2528)

−0.0761 (0.1450) −0.2425 (0.2162) −0.2488 (0.2571) 0.0234 (0.2496) 0.0740 (0.1935)

0.0210 (0.1274) −0.2699 (0.2214) −0.1428 (0.3168) −0.1881 (0.2210) 0.2096 (0.1548)

−0.2007 (0.3747) −0.6498 (0.6101) 0.1299 (0.2855)

−0.3515 (0.4651) −0.9862* (0.5453) 0.3077 (0.2136) −0.0148* (0.0082) 0.0119 (0.0096) −0.0075 (0.0191)

table continues next page

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Returns to Education and Skills

Table E.10 Returns to Education Level (Mincer Equation) for Female Workers, Controlling for Skills (continued) No controls Passed Core test

Literacy assessment

Use of skills

Job-specific skills

0.0648 (0.4226) 0.2063 (0.3268)

Failed Core test Number of observations R2

Socioeconomic

246 0.457

246 0.462

All controls 0.1867 (0.3835) 0.3686 (0.3355)

246 0.500

246 0.496

246 0.481

246 0.590

Table E.11 Linear Probability Model of Self-Employment, Controlling for Skills

No controls Education Level (relative to none) Primary education (%) −0.0803** (0.0381) Junior high school (%) −0.1164*** (0.0264) Senior high school (%) −0.3106*** (0.0333) Tertiary education (%) −0.6318*** (0.0328)

Socioeconomic

Literacy assessment

Use of skills

Job-specific skills

All controls

0.0051 (0.0347) 0.0073 (0.0266) −0.0411 (0.0345) −0.2107*** (0.0387)

0.0135 (0.0350) 0.0244 (0.0302) −0.0114 (0.0406) −0.1804*** (0.0452)

−0.0003 (0.0350) −0.0002 (0.0310) −0.0560 (0.0398) −0.2207*** (0.0468)

0.0064 (0.0334) −0.0036 (0.0243) −0.0345 (0.0318) −0.2283*** (0.0409)

0.0187 (0.0338) 0.0232 (0.0298) 0.0074 (0.0393) −0.1812*** (0.0488)

Socioemotional Skills (relative to score 2 or lower) Extraversion score >2 Conscientiousness >2 Openness>2 Stability>2 Agreeableness>2

−0.0148 (0.0277) −0.0233 (0.0653) 0.0070 (0.0453) −0.0277 (0.0367) 0.0101 (0.0406)

0.0003 (0.0254) 0.0023 (0.0571) 0.0102 (0.0408) −0.0396 (0.0348) −0.0100 (0.0395) table continues next page

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Returns to Education and Skills

Table E.11 Linear Probability Model of Self-Employment, Controlling for Skills (continued) No controls Cognitive skills (relative to skill not used) Reading Read with low intensity Read with medium intensity Read with high intensity Writing Write with low intensity Write with medium intensity Write with high intensity Numeracy Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity Cognitive challenge Low think and learn Medium think and learn High think and learn Physical Low physical demand Medium physical demand High physical demand Autonomy and repetitiveness Low autonomy and repetitive Medium autonomy and repetitive

Socioeconomic

Literacy assessment

Use of skills

Job-specific skills

All controls

−0.0150 (0.0316) −0.0033 (0.0403) −0.0039 (0.0426)

0.0078 (0.0296) 0.0119 (0.0375) 0.0300 (0.0388)

0.0395 (0.0290) 0.0104 (0.0430) −0.0137 (0.0561)

0.0521* (0.0268) 0.0139 (0.0401) −0.0030 (0.0528)

0.1551*** (0.0424) 0.1625*** (0.0412) 0.1508** (0.0625)

0.1147*** (0.0409) 0.1134*** (0.0398) 0.1005* (0.0591) 0.0471** (0.0220) 0.0598** (0.0247) 0.1071*** (0.0304) 0.0146 (0.0388) 0.0260 (0.0394) −0.0080 (0.0396)

0.2061*** (0.0314) 0.4185*** (0.0323)

0.0483** (0.0222) 0.0603** (0.0247) 0.1085*** (0.0307) 0.0156 (0.0380) 0.0236 (0.0386) −0.0118 (0.0387)

0.2105*** (0.0307) 0.4231*** (0.0314)

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Returns to Education and Skills

Table E.11 Linear Probability Model of Self-Employment, Controlling for Skills (continued) No controls

Socioeconomic

Literacy assessment

Use of skills

High autonomy and repetitive Make presentations Supervise others Computer use at work (relative to no use) Computer use with low intensity

Computer use with high intensity 1,963 0.159

All controls

0.4370*** (0.0391) 0.0048 (0.0318) 0.0060 (0.0218)

0.4398*** (0.0383) 0.0131 (0.0320) 0.0043 (0.0221)

−0.1850** (0.0741) 0.0994 (0.1026) −0.0567 (0.0401)

Computer use with medium intensity

Number of observations R2

Job-specific skills

1,963 0.390

1,963 0.392

1,963 0.399

1,963 0.477

−0.1853** (0.0738) 0.1025 (0.1007) −0.0664* (0.0383) 1,963 0.487

Note: All models estimated using ordinary least squares. Robust standard errors are in parentheses. Controls include gender, economic sector, and dummies for region. For all skills dummies of nonresponse (missing) were created and included in the regression, but they are not displayed in the table. Dependent variable is monthly earning considering main and second occupation. Y = 1 if self-employed and 0 if wage employed. *** p < 0.01, ** p < 0.05, * p < 0.1.

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Appendix F

Mismatch of Skills and Unexploited Potential Tables

Table F.1 Difference in Mean of Self-Reported Readers Who Passed and Who Failed the Reading Assessment Core Literacy Test Y1: Read and passed Core

Y2: Read and failed Core

Obs

Mean

Obs

Mean

Difference: Y2–Y1

Female (%) Low SES (%) Middle SES (%) High SES (%)

1,150 1,149 1,149 1,149

42.59 14.16 62.36 23.48

49.47 34.88 48.47 42.40

457 452 452 452

62.56 19.62 52.76 27.62

48.45 39.76 49.98 44.76

19.970*** 5.463** −9.605*** 4.142

Age range (years) (%) 15–19 years 20–24 years 25–34 years 35–44 years 45–64 years

1,150 1,150 1,150 1,150 1,150 1,150

28.86 23.64 25.29 26.08 10.95 14.04

12.32 42.51 43.49 43.93 31.24 34.75

457 457 457 457 457 457

30.98 17.68 16.59 32.11 18.70 14.92

12.16 38.20 37.24 46.74 39.04 35.67

2.119** −5.957** −8.701*** 6.022** 7.755*** 0.882

Education (%) No education Primary education JHS education SHS education Tertiary education Received ECE

1,150 1,150 1,150 1,150 1,150 1,141

0.62 9.44 31.52 37.03 21.39 81.54

7.88 29.25 46.48 48.31 41.02 38.81

457 457 457 457 457 453

5.67 23.18 54.44 15.87 0.85 70.84

23.15 42.24 49.86 36.58 9.19 45.50

5.043*** 13.737*** 22.920*** −21.159*** −20.541*** −10.699***

806 806 806 806 806 806

78.92 7.34 14.84 2.83 74.40 7.83

40.81 26.10 35.57 16.60 43.67 26.88

370 370 370 370 370 370

88.20 7.83 9.65 3.60 33.14 9.48

32.30 26.90 29.57 18.65 47.14 29.34

9.278*** 0.486 −5.191** 0.767 −41.256*** 1.658

Language spoken at work (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

table continues next page

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132

Mismatch of Skills and Unexploited Potential Tables

Table F.1 Difference in Mean of Self-Reported Readers Who Passed and Who Failed the Reading Assessment Core Literacy Test (continued)

Y1: Read and passed Core Obs

Mean

Language spoken at home (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

1,150 1,150 1,150 1,150 1,150 1,150

Labor status (%) Employed Unemployed NEET Inactive

Y2: Read and failed Core

Obs

Mean

Difference: Y2–Y1

65.56 9.04 9.67 5.22 2.04 8.47

47.54 28.69 29.57 22.25 14.15 27.85

457 457 457 457 457 457

72.80 6.54 3.34 5.00 0.25 12.08

44.55 24.75 17.98 21.82 4.99 32.63

7.239** −2.504 −6.338*** −0.217 −1.794*** 3.615*

1,150 1,150 1,150 1,150

45.20 6.40 7.52 40.88

49.79 24.49 26.38 49.18

457 457 457 457

62.44 3.38 9.93 24.26

48.48 18.08 29.93 42.91

17.235*** −3.029** 2.411 −16.617***

Employment status (%) Formal employee Informal employee Self-employed

587 587 587

35.46 27.71 36.83

47.88 44.79 48.28

310 310 310

8.36 17.58 74.06

27.72 38.13 43.90

−27.103*** −10.125*** 37.228***

Occupation (%) Low-skilled occupation Mid-skilled occupation High-skilled occupation

587 587 587

23.85 41.11 35.04

42.65 49.24 47.75

310 310 310

46.61 49.80 3.59

49.97 50.08 18.64

22.758*** 8.690** −31.448***

Economic sector (%) Agriculture fishing, and mining Manufacturing Low- to mid-value-added High-value-added

587 587 587 587

5.18 8.82 45.55 40.44

22.18 28.39 49.84 49.12

310 310 310 310

10.10 13.76 66.55 9.60

30.18 34.50 47.26 29.51

4.916* 4.935 20.993*** −30.844***

Earnings Monthly earnings

648

678.52

2,091.11

304

401.69

970.30

1,135 1,150 1,135 1,150 1,135 1,150 1,133 1,150 1,135 1,150

2.59 1.11 3.32 1.11 3.22 1.11 2.75 1.47 3.15 1.11

0.59 10.46 0.52 10.46 0.52 10.46 0.55 12.02 0.58 10.46

344 457 340 457 343 457 340 457 341 457

2.43 27.99 2.96 28.45 2.86 28.11 2.65 28.51 2.81 28.40

0.59 44.95 0.63 45.17 0.62 45.00 0.57 45.20 0.69 45.14

−276.839** −0.163*** 26.887*** −0.361*** 27.343*** −0.359*** 27.000*** −0.099** 27.049*** −0.342*** 27.293*** table continues next page

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Mismatch of Skills and Unexploited Potential Tables

Table F.1 Difference in Mean of Self-Reported Readers Who Passed and Who Failed the Reading Assessment Core Literacy Test (continued)

Y1: Read and passed Core Obs

Mean

Self-reported skills (%) Reading Don’t use reading skill Read with low intensity Read with medium intensity Read with high intensity

1,131 1,131 1,131 1,131

Writing Don’t use writing skill Write with low intensity Write with medium intensity Write with high intensity

Y2: Read and failed Core

Obs

Mean

Difference: Y2–Y1

0.00 30.46 28.23 41.31

0.00 46.04 45.03 49.26

448 448 448 448

0.00 66.28 20.17 13.55

0.00 47.33 40.17 34.26

n.a. 35.822*** −8.061*** −27.761***

1,136 1,136 1,136 1,136

5.26 60.25 18.40 16.08

22.33 48.96 38.77 36.76

455 455 455 455

17.38 67.05 8.78 6.79

37.93 47.05 28.33 25.19

12.120*** 6.800** −9.626*** −9.294***

Numeracy Don’t use numeracy skill Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity

1,150 1,150 1,150 1,150

3.96 10.85 59.51 25.68

19.52 31.12 49.11 43.70

457 457 457 457

4.25 31.45 58.94 5.36

20.21 46.48 49.25 22.55

0.292 20.592*** −0.569 −20.314***

Computer Don’t use computer skill Computer with low intensity Computer with medium intensity Computer with high intensity

1,126 1,126 1,126 1,126

43.00 18.56 10.29 28.16

49.53 38.90 30.39 45.00

453 453 453 453

86.03 6.68 1.10 6.19

34.70 24.99 10.46 24.12

43.038*** −11.882*** −9.183*** −21.973***

Literacy assessment No answer on Reading Component or Core (%)

1,150

0.00

457

0.00

Reading Component (average) (%) Sentence incorrect answers Sentence correct answers Sentence no answers Passage incorrect answers Passage correct answers Passage no answers Vocabulary incorrect answers Vocabulary correct answers Vocabulary no answers

1,150 1,150 1,150 1,150 1,150 1,150 1,150 1,150 1,150

38.47 46.64 14.90 51.28 44.67 4.05 72.85 22.84 4.31

11.30 9.50 11.70 8.87 7.96 6.54 4.42 2.39 5.21

457 457 457 457 457 457 457 457 457

40.62 31.70 27.68 55.51 27.59 16.90 63.37 18.24 18.39

27.96 16.63 18.61 25.16 17.80 17.17 14.12 6.36 18.53

2.156 −14.940*** 12.785*** 4.231*** −17.081*** 12.850*** −9.482*** −4.608*** 14.089***

Core (average) (%) Score Core test Passed Core test

1,150 1,150

6.24 100.00

1.61 0.00

457 457

0.76 0.00

0.85 0.00

−5.478*** −100.00***

Literacy assessment Reading proficiency

1,150

222.86

457

53.02

−169.841***

Note: n.a. = not applicable; NEET = Not in Employment, Education, or Training. *** p < 0.01, ** p < 0.05, * p < 0.1.

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n.a.

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Mismatch of Skills and Unexploited Potential Tables

Table F.2 Unexploited Potential: Reading Skill Y1: Read at home and at work Y2: Read at home but not at work Female (%) Low SES (%) Middle SES (%) High SES (%) Age range (years) (%) 15–19 years 20–24 years 25–34 years 35–44 years 45–64 years Education (%) No education Primary education JHS education SHS education Tertiary education Received ECE Language spoken at work (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others Language spoken at home (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others Labor status (%) Employed Unemployed NEET Inactive Employment status (%) Formal employee Informal employee Self-employed Occupation (%) Low-skilled occupation Mid-skilled occupation High-skilled occupation

Obs

Mean

Obs

Mean

Difference: Y2–Y1

650 646 646 646 650 650 650 650 650 650

36.84 16.24 61.79 21.97 36.47 1.17 14.81 36.81 20.24 26.97

48.28 36.91 48.63 41.44 11.87 10.77 35.55 48.27 40.21 44.41

560 555 555 555 560 560 560 560 560 560

61.41 21.61 56.43 21.96 37.22 2.69 10.70 31.37 30.33 24.92

48.73 41.20 49.63 41.43 11.36 16.19 30.93 46.44 46.01 43.29

24.562*** 5.371* −5.355 −0.015 0.750 1.517 −4.113 −5.446* 10.089*** −2.046

650 650 650 650 650 645

1.92 4.19 27.30 37.13 29.46 69.31

13.72 20.05 44.59 48.35 45.62 46.15

560 560 560 560 560 548

6.35 12.22 57.41 20.80 3.22 66.08

24.41 32.78 49.49 40.62 17.67 47.39

4.438*** 8.031*** 30.106*** −16.336*** −26.240*** −3.237

649 649 649 649 649 649

80.75 7.75 16.14 2.48 76.57 7.74

39.45 26.76 36.82 15.56 42.39 26.74

559 559 559 559 559 559

85.78 12.26 12.44 2.19 31.36 9.89

34.96 32.83 33.03 14.64 46.44 29.87

5.026** 4.509* −3.701 −0.293 −45.205*** 2.149

648 648 648 648 648 648

69.86 7.80 8.83 4.41 2.00 7.10

45.92 26.83 28.40 20.55 14.03 25.70

557 557 557 557 557 557

64.88 12.81 7.33 3.06 0.29 11.63

47.78 33.45 26.09 17.23 5.40 32.09

−4.977 5.013** −1.500 −1.355 −1.713*** 4.532**

650 650 650 650

100.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00

560 560 560 560

100.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00

650 650 650

36.91 24.76 38.32

48.29 43.20 48.66

560 560 560

5.96 21.64 72.40

23.69 41.22 44.74

−30.954*** −3.122 34.076***

650 650 650

29.05 35.78 35.17

45.43 47.97 47.79

560 560 560

40.77 56.52 2.71

49.18 49.62 16.27

11.725*** 20.733*** −32.458***

n.a. n.a. n.a. n.a.

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Mismatch of Skills and Unexploited Potential Tables

Table F.2 Unexploited Potential: Reading Skill (continued) Y1: Read at home and at work Y2: Read at home but not at work Obs

Mean

Obs

Mean

Difference: Y2–Y1

Economic sector (%) Agriculture, fishing, and mining Manufacturing Low- to mid-value-added High-value-added

650 650 650 650

4.42 10.99 42.75 41.84

20.57 31.31 49.51 49.37

560 560 560 560

9.38 11.22 71.56 7.84

29.17 31.59 45.15 26.90

4.956** 0.228 28.815*** −33.998***

Earnings Monthly earnings

626

771.72

2,391.23

540

383.97

669.19

−387.751***

596 650 594 650 595 650 593 650 594 650

2.58 8.40 3.33 8.49 3.14 8.51 2.81 8.60 3.09 8.55

0.57 27.76 0.52 27.89 0.55 27.92 0.55 28.06 0.60 27.98

387 560 385 560 385 560 382 560 383 560

2.45 32.17 3.13 32.46 2.92 32.34 2.73 33.31 2.94 32.64

0.59 46.75 0.61 46.86 0.63 46.82 0.56 47.18 0.69 46.93

−0.131*** 23.773*** −0.198*** 23.973*** −0.219*** 23.826*** −0.078* 24.711*** −0.149*** 24.091***

649 649 649 649

0.00 44.37 24.79 30.84

0.00 49.72 43.21 46.22

547 547 547 547

0.00 70.70 18.29 11.01

0.00 45.55 38.69 31.33

n.a. 26.333*** −6.501** −19.832***

646 646 646 646

3.47 71.84 14.24 10.45

18.32 45.01 34.97 30.62

557 557 557 557

23.72 67.40 6.88 1.99

42.58 46.92 25.34 13.99

20.251*** −4.437 −7.358*** −8.456***

650 650 650 650

2.36 17.32 68.90 11.42

15.20 37.87 46.32 31.82

560 560 560 560

4.81 33.84 59.96 1.39

21.41 47.36 49.04 11.70

2.446* 16.523*** −8.940** −10.029***

641 641 641 641

55.66 9.30 6.50 28.54

49.72 29.07 24.66 45.20

556 556 556 556

90.23 4.08 2.39 3.29

29.72 19.81 15.30 17.86

34.571*** −5.220*** −4.101*** −25.251***

650

18.54

38.89

560

36.87

48.29

18.335***

Self-reported skills (%) Reading Don’t use reading skill Read with low intensity Read with medium intensity Read with high intensity Writing Don’t use writing skill Write with low intensity Write with medium intensity Write with high intensity Numeracy Don’t use numeracy skill Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity Computer Don’t use computer skill Computer with low intensity Computer with medium intensity Computer with high intensity Literacy assessment No answer on Reading Component or Core (%)

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Mismatch of Skills and Unexploited Potential Tables

Table F.2 Unexploited Potential: Reading Skill (continued) Y1: Read at home and at work Y2: Read at home but not at work Reading Component (average) (%) Sentence incorrect answers Sentence correct answers Sentence no answers Passage incorrect answers Passage correct answers Passage no answers Vocabulary incorrect answers Vocabulary correct answers Vocabulary no answers Core (average) Score Core test Passed Core test Literacy assessment Reading proficiency

Obs

Mean

Obs

Mean

Difference: Y2–Y1

527 527 527 527 527 527 527 527 527

39.98 44.30 15.72 52.79 41.61 5.59 71.40 22.24 6.36

15.20 12.34 13.39 13.62 12.54 9.71 8.17 3.63 10.45

353 353 353 353 353 353 353 353 353

42.80 37.26 19.95 56.04 33.54 10.42 68.35 20.54 11.11

24.52 17.06 16.23 21.32 17.82 13.56 12.03 5.42 15.70

2.814 −7.045*** 4.230*** 3.242** −8.074*** 4.832*** −3.052*** −1.698*** 4.750***

527 527

5.29 78.76

2.74 40.94

353 353

2.97 49.42

2.71 50.07

−2.320*** −29.338***

650

176

560

107

−69.405***

Note: n.a. = not applicable; NEET = Not in Employment, Education, or Training. *** p < 0.01, ** p < 0.05, * p < 0.1.

Table F.3 Unexploited Potential: Writing Skill Y1: Write at home and at work

Y2: Write at home but not at work

Difference: Y2–Y1

Obs

Mean

Obs

Mean

Female (%) Low SES (%) Middle SES (%) High SES (%) Age range (years) (%) 15–19 years 20–24 years 25–34 years 35–44 years 45–64 years

812 808 808 808 812 812 812 812 812 812

42.82 17.56 62.38 20.06 37.36 1.21 12.16 34.79 23.65 28.19

49.51 38.07 48.47 40.07 11.81 10.95 32.70 47.66 42.52 45.02

248 245 245 245 248 248 248 248 248 248

55.20 22.07 51.68 26.24 35.29 3.54 13.69 35.76 26.76 20.25

49.83 41.56 50.07 44.08 10.86 18.51 34.44 48.03 44.36 40.27

12.383*** 4.514 −10.700** 6.186 −2.065** 2.325* 1.533 0.974 3.114 −7.946**

Education (%) No education Primary education JHS education SHS education Tertiary education Received ECE

812 812 812 812 812 805

1.93 4.70 34.91 33.94 24.52 67.32

13.75 21.19 47.70 47.38 43.05 46.93

248 248 248 248 248 243

7.56 12.95 53.19 23.25 3.05 62.77

26.49 33.64 50.00 42.33 17.24 48.44

5.633*** 8.243*** 18.276*** −10.684*** −21.467*** −4.555

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Table F.3 Unexploited Potential: Writing Skill (continued) Y1: Write at home and at work

Y2: Write at home but not at work

Difference: Y2–Y1

Obs

Mean

Obs

Mean

Language spoken at work (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

810 810 810 810 810 810

80.21 9.47 17.33 2.38 68.95 8.02

39.86 29.30 37.88 15.25 46.30 27.18

248 248 248 248 248 248

84.73 12.00 11.61 4.91 24.60 10.41

36.04 32.56 32.10 21.65 43.15 30.60

4.516 2.525 −5.724** 2.530 −44.346*** 2.389

Language spoken at home (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

808 808 808 808 808 808

68.53 9.66 9.72 3.49 1.64 6.96

46.47 29.56 29.65 18.37 12.69 25.47

247 247 247 247 247 247

63.61 10.97 5.92 5.72 0.76 13.02

48.21 31.32 23.64 23.26 8.68 33.73

−4.912 1.316 −3.807* 2.222 −0.879 6.060*

Labor status (%) Employed Unemployed NEET Inactive

812 812 812 812

100.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00

248 248 248 248

100.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00

Employment status (%) Formal employee Informal employee Self-employed

812 812 812

31.27 20.55 48.18

46.39 40.43 50.00

248 248 248

4.87 24.75 70.38

21.56 43.24 45.75

−26.403*** 4.203 22.200***

Occupation (%) Low-skilled occupation Mid-skilled occupation High-skilled occupation

812 812 812

32.62 39.66 27.72

46.91 48.95 44.79

248 248 248

43.42 54.58 2.00

49.67 49.89 14.02

10.803** 14.914*** −25.717***

812 812 812 812

4.60 14.54 46.75 34.11

20.95 35.28 49.92 47.44

248 248 248 248

15.44 4.85 72.88 6.83

36.20 21.53 44.55 25.27

10.842*** −9.691*** 26.135*** −27.286***

783

704.36

2,110.72

236

315.79

457.89

−388.565***

698 812 695 812 695

2.56 13.81 3.32 14.10 3.06

0.58 34.52 0.51 34.82 0.60

178 248 176 248 177

2.43 30.64 3.04 31.30 3.03

0.59 46.19 0.67 46.46 0.57

−0.134** 16.837*** −0.281*** 17.198*** −0.030

Economic sector (%) Agriculture, fishing, and mining Manufacturing Low- to mid-value-added High-value-added Earnings Monthly earnings Socioemotional skills Extraversion (score) Missing extraversion Conscientiousness (score) Missing conscientiousness Openness (score)

n.a. n.a. n.a. n.a.

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Table F.3 Unexploited Potential: Writing Skill (continued) Y1: Write at home and at work Missing openness Emotional stability (score) Missing stability Agreeableness (score) Missing agreeableness Self-reported skills (%) Reading Don’t use reading skill Read with low intensity Read with medium intensity Read with high intensity Writing Don’t use writing skill Write with low intensity Write with medium intensity Write with high intensity Numeracy Don’t use numeracy skill Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity Computer Don’t use computer skill Computer with low intensity Computer with medium intensity Computer with high intensity Literacy assessment No answer on Reading Component or Core (%) Reading Component (average) (%) Sentence incorrect answers Sentence correct answers Sentence no answers Passage incorrect answers Passage correct answers Passage no answers Vocabulary incorrect answers Vocabulary correct answers Vocabulary no answers

Y2: Write at home but not at work

Obs

Mean

Obs

Mean

Difference: Y2–Y1

812 693 812 692 812

14.17 2.81 14.27 3.09 14.49

34.90 0.55 34.99 0.61 35.22

248 175 248 176 248

30.86 2.77 32.36 2.93 31.34

46.29 0.54 46.88 0.69 46.48

16.689*** −0.039 18.092*** −0.168** 16.849***

806 806 806 806

4.40 46.12 24.00 25.48

20.52 49.88 42.73 43.60

245 245 245 245

12.69 58.20 19.14 9.98

33.35 49.42 39.42 30.03

8.285*** 12.086*** −4.864 −15.507***

809 809 809 809

0.00 77.14 13.33 9.53

0.00 42.02 34.01 29.38

244 244 244 244

0.00 89.66 9.58 0.76

0.00 30.50 29.49 8.68

n.a. 12.529*** −3.752 −8.777***

812 812

3.06 18.59

17.24 38.92

248 248

4.58 35.98

20.95 48.09

1.519 17.393***

812 812

68.91 9.44

46.31 29.25

248 248

57.71 1.73

49.50 13.08

−11.208** −7.704***

800 800

64.05 8.11

48.01 27.31

247 247

90.57 2.50

29.28 15.63

26.519*** −5.611***

800 800

6.19 21.65

24.11 41.21

247 247

1.62 5.31

12.64 22.48

−4.574*** −16.334***

812

24.30

42.92

248

32.46

46.92

8.157**

611 611 611 611 611 611 611 611 611

40.06 43.51 16.43 53.18 40.93 5.89 71.57 22.18 6.25

15.84 12.83 13.83 14.91 13.37 9.85 7.80 3.67 9.88

165 165 165 165 165 165 165 165 165

42.09 37.73 20.18 55.94 33.52 10.54 68.44 20.46 11.10

24.57 17.31 16.53 21.38 17.78 14.23 10.10 5.42 13.74

2.034 −5.782*** 3.748** 2.755 −7.404*** 4.649*** −3.132*** −1.718*** 4.850***

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Mismatch of Skills and Unexploited Potential Tables

Table F.3 Unexploited Potential: Writing Skill (continued) Y1: Write at home and at work

Y2: Write at home but not at work

Obs

Mean

Obs

Mean

Core (average) Score Core test Passed Core test

611 611

5.01 75.95

2.80 42.77

165 165

2.80 47.20

2.60 50.07

Literacy assessment Reading proficiency

812

164

248

109

Difference: Y2–Y1 −2.207*** −28.749*** −54.538***

Note: n.a. = not applicable; NEET = Not in Employment, Education, or Training. *** p < 0.01, ** p < 0.05, * p < 0.1.

Table F.4 Unexploited Potential: Numeracy Skill Y1: Use mathematics at home and at work

Y2: Use mathematics at home but not at work

Obs

Mean

Obs

Mean

Difference: Y2–Y1

Female (%) Low SES (%) Middle SES (%) High SES (%) Age range (years) (%) 15–19 years 20–24 years 25–34 years 35–44 years 45–64 years

1,603 1,591 1,591 1,591 1,603 1,603 1,603 1,603 1,603 1,603

58.30 25.27 55.57 19.15 37.41 1.80 11.78 32.05 27.47 26.89

49.32 43.47 49.70 39.36 11.61 13.32 32.25 46.68 44.65 44.35

88 88 88 88 88 88 88 88 88 88

39.40 31.19 49.81 19.00 36.92 0.65 13.00 41.38 18.62 26.36

49.14 46.59 50.29 39.46 12.18 8.06 33.82 49.53 39.15 44.31

−18.905*** 5.916 −5.764 −0.152 −0.497 −1.158 1.217 9.329 −8.855* −0.533

Education (%) No education Primary education JHS education SHS education Tertiary education Received ECE

1,603 1,603 1,603 1,603 1,603 1,585

25.58 9.96 34.33 19.54 10.60 55.63

43.64 29.95 47.49 39.67 30.79 49.70

88 88 88 88 88 87

25.16 7.95 27.04 20.46 19.40 56.09

43.64 27.21 44.67 40.57 39.77 49.92

−0.417 −2.003 −7.289 0.911 8.799 0.459

Language spoken at work (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

1,599 1,599 1,599 1,599 1,599 1,599

80.59 6.15 13.17 7.85 38.72 12.16

39.56 24.03 33.83 26.90 48.73 32.70

88 88 88 88 88 88

70.73 17.59 14.51 6.72 48.77 12.14

45.76 38.29 35.43 25.17 50.27 32.85

−9.862 11.435* 1.345 −1.131 10.049 −0.023

Language spoken at home (%) Akan Ewe

1,598 1,598

64.12 6.71

47.98 25.03

88 88

61.81 12.13

48.86 32.84

−2.307 5.420

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Mismatch of Skills and Unexploited Potential Tables

Table F.4 Unexploited Potential: Numeracy Skill (continued) Y1: Use mathematics at home and at work

Y2: Use mathematics at home but not at work

Obs

Mean

Obs

Mean

Difference: Y2–Y1

1,598 1,598 1,598 1,598

6.89 8.00 0.84 13.44

25.34 27.13 9.11 34.12

88 88 88 88

6.04 11.02 0.00 8.99

23.96 31.49 0.00 28.77

−0.847 3.021 −0.835*** −4.451

Labor status (%) Employed Unemployed NEET Inactive

1,603 1,603 1,603 1,603

100.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00

88 88 88 88

100.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00

Employment status (%) Formal employee Informal employee Self-employed

1,603 1,603 1,603

13.44 17.85 68.71

34.12 38.31 46.38

88 88 88

37.91 45.14 16.95

48.79 50.05 37.74

24.468*** 27.282*** −51.750***

Occupation (%) Low-skilled occupation Mid-skilled occupation High-skilled occupation

1,603 1,603 1,603

38.82 48.24 12.93

48.75 49.98 33.57

88 88 88

40.95 28.93 30.12

49.46 45.60 46.14

2.123 −19.314*** 17.191**

Economic sector (%) Agriculture, fishing, and mining Manufacturing Low- to mid-value-added High-value-added

1,603 1,603 1,603 1,603

11.12 11.10 62.73 15.05

31.45 31.42 48.37 35.76

88 88 88 88

11.06 3.29 35.03 50.62

31.55 17.94 47.98 50.28

−0.061 −7.807*** −27.707*** 35.575***

Earnings Monthly earnings

1,560

566.46

1,770.94

315.20

490.52

−251.257***

931 1,603 925 1,603 924 1,603 918 1,603 919 1,603

2.51 44.55 3.23 44.95 3.04 44.91 2.77 45.30 3.02 45.16

0.60 49.72 0.57 49.76 0.60 49.76 0.56 49.79 0.64 49.78

56 88 56 88 56 88 56 88 56 88

2.61 33.74 3.39 33.74 3.05 33.74 2.74 33.74 3.12 33.74

0.54 47.55 0.53 47.55 0.61 47.55 0.57 47.55 0.55 47.55

0.102 −10.818 0.161 −11.218 0.009 −11.180 −0.032 −11.563 0.099 −11.422

Self-reported skills (%) Reading Don’t use reading skill Read with low intensity

1,593 1,593

37.74 35.92

48.49 47.99

88 88

30.28 39.41

46.21 49.15

−7.464 3.489

Ga-Adangme Mole-Dagbani English Others

n.a. n.a. n.a. n.a.

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Mismatch of Skills and Unexploited Potential Tables

Table F.4 Unexploited Potential: Numeracy Skill (continued) Y1: Use mathematics at home and at work Read with medium intensity Read with high intensity Writing Don’t use writing skill Write with low intensity Write with medium intensity Write with high intensity Numeracy Don’t use numeracy skill Numeracy with low intensity Numeracy with medium intensity Numeracy with high intensity Computer Don’t use computer skill Computer with low intensity Computer with medium intensity Computer with high intensity Literacy assessment No answer on Reading Component or Core (%) Reading Component (average) (%) Sentence incorrect answers Sentence correct answers Sentence no answers Passage incorrect answers Passage correct answers Passage no answers Vocabulary incorrect answers Vocabulary correct answers Vocabulary no answers Core (average) Score Core test Passed Core test Literacy assessment Reading proficiency

Y2: Use mathematics at home but not at work

Difference: Y2–Y1

Obs

Mean

Obs

Mean

1,593 1,593

14.01 12.32

34.72 32.88

88 88

12.36 17.95

33.10 38.60

−1.650 5.625

1,596 1,596 1,596 1,596

40.78 48.11 6.98 4.13

49.16 49.98 25.48 19.91

88 88 88 88

32.45 52.27 9.97 5.30

47.09 50.23 30.14 22.53

−8.325 4.160 2.998 1.167

1,603 1,603

0.00 29.59

0.00 45.66

88 88

0.00 43.38

0.00 49.84

n.a. 13.786*

1,603 1,603

65.55 4.86

47.53 21.51

88 88

54.51 2.12

50.08 14.48

−11.044 −2.741

1,590 1,590

81.99 4.26

38.44 20.20

88 88

74.34 4.93

43.92 21.77

−7.650 0.667

1,590 1,590

3.27 10.48

17.79 30.63

88 88

1.49 19.23

12.20 39.64

−1.775 8.758

1,603

46.91

49.92

45.95

50.12

−0.962

843 843 843 843 843 843 843 843 843

43.19 38.34 18.47 55.78 35.11 9.11 67.41 20.20 12.38

23.48 17.12 16.27 20.31 17.65 14.14 14.25 6.12 18.97

51 51 51 51 51 51 51 51 51

44.15 42.38 13.47 54.78 40.02 5.21 69.97 22.05 7.97

19.78 15.53 11.85 17.14 15.18 7.93 11.44 4.09 14.92

0.964 4.038 −5.003** −1.007 4.908* −3.901*** 2.559 1.849*** −4.408*

843 843

3.86 58.99

3.09 49.21

51 51

5.15 83.36

2.52 37.62

1.286*** 24.364***

1,603

120

Note: NEET = Not in Employment, Education, or Training. *** p < 0.01, ** p < 0.05, * p < 0.1.

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24.144**

142

Mismatch of Skills and Unexploited Potential Tables

Table F.5 Unexploited Potential: Computer Skill Y1: Use computer at home and at work

Y2: Use computer at home but not at work

Obs

Mean

Obs

Mean

Difference: Y2–Y1

Female (%) Low SES (%) Middle SES (%) High SES (%)

172 172 172 172

27.59 8.74 60.85 30.41

44.83 28.32 48.95 46.14

190 190 190 190

28.29 18.68 60.05 21.27

45.16 39.08 49.11 41.03

0.706 9.943** −0.801 −9.143

Age (%) 15–19 years 20–24 years 25–34 years 35–44 years 45–64 years

172 172 172 172 172 172

34.81 0.70 17.94 43.71 14.59 23.07

11.41 8.33 38.48 49.75 35.40 42.25

190 190 190 190 190 190

29.81 3.72 30.88 39.11 20.91 5.39

8.94 18.97 46.32 48.93 40.77 22.64

−4.996*** 3.024 12.944** −4.605 6.318 −17.681***

Education (%) No education Primary education JHS education SHS education Tertiary education Received ECE

172 172 172 172 172 170

0.00 0.31 2.25 33.01 64.43 77.06

0.00 5.58 14.88 47.16 48.01 42.17

190 190 190 190 190 187

1.34 4.76 22.63 48.84 22.43 81.95

11.53 21.35 41.95 50.12 41.82 38.56

1.339* 4.451** 20.376*** 15.831** −41.997*** 4.892

Language spoken at work (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

172 172 172 172 172 172

73.33 4.93 17.47 1.42 95.74 8.68

44.36 21.71 38.08 11.86 20.25 28.24

190 190 190 190 190 190

76.25 7.95 19.61 3.29 75.46 7.60

42.67 27.12 39.81 17.87 43.14 26.57

2.928 3.018 2.143 1.867 −20.279*** −1.086

Language spoken at home (%) Akan Ewe Ga-Adangme Mole-Dagbani English Others

172 172 172 172 172 172

69.39 6.90 10.73 3.40 4.25 5.33

46.22 25.42 31.04 18.18 20.22 22.53

190 190 190 190 190 190

58.82 12.73 11.16 7.64 3.07 6.59

49.35 33.42 31.57 26.63 17.31 24.87

−10.570* 5.829 0.424 4.233 −1.173 1.256

Labor status (%) Employed Unemployed NEET Inactive

172 172 172 172

100.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00

190 190 190 190

100.00 0.00 0.00 0.00

0.00 0.00 0.00 0.00

n.a. n.a. n.a. n.a.

Employment status (%) Formal employee Informal employee Self-employed

172 172 172

58.89 20.93 20.18

49.35 40.80 40.25

190 190 190

26.12 40.21 33.67

44.04 49.16 47.38

−32.774*** 19.282*** 13.492**

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Mismatch of Skills and Unexploited Potential Tables

Table F.5 Unexploited Potential: Computer Skill (continued) Y1: Use computer at home and at work

Y2: Use computer at home but not at work

Obs

Mean

Obs

Mean

Difference: Y2–Y1

Occupation (%) Low-skilled occupation Mid-skilled occupation High-skilled occupation

172 172 172

7.31 28.27 64.41

26.11 45.16 48.02

190 190 190

28.23 39.73 32.04

45.13 49.06 46.78

20.921*** 11.458* −32.380***

Economic sector (%) Agriculture, fishing, and mining Manufacturing Low- to mid-value-added High-value-added

172 172 172 172

1.42 4.25 33.74 60.59

11.89 20.22 47.42 49.01

190 190 190 190

3.33 8.52 53.53 34.62

18.00 27.99 50.01 47.70

1.909 4.270 19.795*** −25.975***

Earnings Monthly earnings

163

1,360.81

4,175.78

184

514.12

703.04

171 172 171 172 171 172 171 172 171 172

2.72 0.31 3.40 0.31 3.27 0.31 2.85 0.31 3.19 0.31

0.56 5.58 0.46 5.58 0.48 5.58 0.54 5.58 0.57 5.58

182 190 182 190 182 190 182 190 182 190

2.62 4.25 3.34 4.25 3.18 4.25 2.75 4.25 3.12 4.25

0.54 20.22 0.50 20.22 0.58 20.22 0.52 20.22 0.60 20.22

−0.097 3.937** −0.060 3.937** −0.084 3.937** −0.091 3.937** −0.077 3.937**

172 172 172 172

0.00 20.51 32.86 46.62

0.00 40.50 47.11 50.03

189 189 189 189

4.20 36.49 32.65 26.66

20.12 48.27 47.02 44.33

4.205*** 15.976*** −0.213 −19.967***

170 170 170 170

2.46 50.99 25.82 20.74

15.53 50.14 43.89 40.66

189 189 189 189

9.50 67.14 17.21 6.15

29.40 47.10 37.85 24.09

7.040** 16.153** −8.609* −14.583***

172 172 172 172

4.24 10.67 56.19 28.90

20.22 30.96 49.76 45.46

190 190 190 190

3.45 10.68 77.78 8.08

18.30 30.97 41.68 27.33

−0.795 0.013 21.597*** −20.815***

172 172

0.00 6.75

0.00 25.17

178 178

0.00 42.17

0.00 49.52

n.a. 35.413***

−846.695*

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Mismatch of Skills and Unexploited Potential Tables

Table F.5 Unexploited Potential: Computer Skill (continued)

Computer with medium intensity Computer with high intensity

Y1: Use computer at home and at work

Y2: Use computer at home but not at work

Obs

Mean

Obs

Mean

Difference: Y2–Y1

172 172

8.47 84.78

27.92 36.02

178 178

26.07 31.77

44.02 46.69

17.602*** −53.015***

172

8.15

27.45

190

11.03

31.40

2.871

Literacy assessment No answer on Reading Component or Core (%) Reading Component (average) (%) Sentence incorrect answers Sentence correct answers Sentence no answers Passage incorrect answers Passage correct answers Passage no answers Vocabulary incorrect answers Vocabulary correct answers Vocabulary no answers Core (average) Score Core test Passed Core test

153 153 153 153 153 153 153 153 153

40.62 49.07 10.30 51.48 45.91 2.62 73.63 23.30 3.06

7.64 7.19 10.12 6.76 5.60 5.33 3.87 1.85 4.20

162 162 162 162 162 162 162 162 162

38.19 44.25 17.57 50.63 42.69 6.68 71.35 22.19 6.46

14.12 11.82 14.20 12.24 10.84 12.35 9.03 3.90 11.99

−2.439* −4.825*** 7.264*** −0.846 −3.214*** 4.060*** −2.282** −1.111*** 3.393***

153 153

6.63 95.87

1.72 19.97

162 162

5.65 85.11

2.54 35.71

−0.984*** −10.763***

Literacy assessment Reading proficiency

172

233

190

199

−33.236***

Note: n.a. = not applicable; NEET = Not in Employment, Education, or Training; Obs = number of observations. *** p < 0.01, ** p < 0.05, * p < 0.1.

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

Appendix G

Effect of Socioemotional Skills on Education and Labor Outcomes

Table G.1 Years of Education, Controlling for Socioemotional Skills Time preference Socioemotional skills Time preference (score)

Risk

Hostile bias

Grit

−0.4006*** (0.0964)

Risk aversion (score)

0.2359** (0.0981)

Hostile bias (score)

−0.8940*** (0.1348)

Grit (score)

0.3309* (0.1751)

Openness (score)

0.6430*** (0.1853) 1.0076*** (0.1757) 0.6508*** (0.1502) 0.4639*** (0.1668) 0.2862* (0.1684)

Conscientiousness (score) Extraversion (score) Agreeableness (score) Emotional stability (score) Controls Female (%) Age Middle socioeconomic status (%)

Big five

−0.4034** (0.1992) 0.0812*** (0.0096) 0.7723** (0.3175)

−0.3887* (0.2005) 0.0869*** (0.0094) 0.7370** (0.3092)

−0.3431* (0.1981) 0.0881*** (0.0095) 0.6398** (0.2921)

−0.3654* (0.2002) 0.0841*** (0.0096) 0.7660** (0.3114)

−0.0660 (0.1967) 0.0788*** (0.0094) 0.7546** (0.2966)

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146

Effect of Socioemotional Skills on Education and Labor Outcomes

Table G.1 Years of Education, Controlling for Socioemotional Skills (continued)

High socioeconomic status (%) Mother’s education Primary Secondary Tertiary Dummy for region Number of observations R2

Time preference

Risk

Hostile bias

Grit

Big five

0.8857** (0.3612)

0.8384** (0.3568)

0.7284** (0.3362)

0.8551** (0.3609)

0.6907** (0.3414)

−0.8607 (0.6032) 0.8415** (0.3500) 1.9081*** (0.6603) x

−0.9151 (0.6176) 0.8650** (0.3517) 1.9352*** (0.6487) x

−0.9787 (0.6097) 0.8621** (0.3433) 1.9516*** (0.5916) x

−0.9161 (0.6239) 0.8787** (0.3537) 1.8942*** (0.6696) x

−0.6848 (0.6082) 0.8963** (0.3489) 1.8244*** (0.6760) X

1,868 0.144

1,868 0.137

1,868 0.163

1,868 0.135

1,868 0.209

Note: All models estimated using ordinary least squares. Robust standard errors are in parentheses. Controls include gender, age, socioeconomic status at age 15 years, mother's education, and dummies for region. Dependent variable equals years of education. ***p < 0.01, **p < 0.05, *p < 0.1

Table G.2 Linear Probability Model of Completing SHS or Tertiary Education, Controlling for Socioemotional Skills Time preference Socioemotional skills Time preference (score) Risk aversion (score) Hostile bias (score)

Risk

Hostile bias

Grit

Big five

−0.0515*** (0.0137) 0.0360*** (0.0124) −0.1149*** (0.0193)

Grit (score)

0.0293 (0.0238)

Openness (score) Conscientiousness (score) Extraversion (score) Agreeableness (score) Emotional stability (score)

0.0783*** (0.0255) 0.1410*** (0.0247) 0.0850*** (0.0221) 0.0518** (0.0234) 0.0525** (0.0232) table continues next page

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Effect of Socioemotional Skills on Education and Labor Outcomes

Table G.2 Linear Probability Model of Completing SHS or Tertiary Education, Controlling for Socioemotional Skills (continued)

Controls Female (%) Age Middle socioeconomic status (%) High socioeconomic status (%) Mother’s education Primary Secondary Tertiary Dummy for region Number of observations R2

Time preference

Risk

Hostile bias

Grit

Big five

−0.0499* (0.0282) 0.0074*** (0.0013) 0.0776 (0.0478) 0.0809 (0.0537)

−0.0479* (0.0283) 0.0082*** (0.0013) 0.0729 (0.0468) 0.0742 (0.0532)

−0.0421 (0.0280) 0.0083*** (0.0013) 0.0605 (0.0440) 0.0606 (0.0497)

−0.0461 (0.0283) 0.0079*** (0.0013) 0.0758 (0.0468) 0.0772 (0.0536)

−0.0026 (0.0278) 0.0070*** (0.0013) 0.0759* (0.0435) 0.0557 (0.0504)

−0.0869 (0.0752) 0.0877 (0.0541) 0.1745* (0.0974)

−0.0940 (0.0772) 0.0903* (0.0544) 0.1782* (0.0960)

−0.1021 (0.0760) 0.0904* (0.0535) 0.1801** (0.0899)

−0.0940 (0.0770) 0.0927* (0.0546) 0.1739* (0.0983)

−0.0670 (0.0728) 0.0926* (0.0542) 0.1612 (0.1007)

1,868 0.087

1,868 0.082

1,868 0.106

1,868 0.078

1,868 0.152

Note: All models estimated using ordinary least squares. Robust standard errors in parentheses. Controls include gender, age, socioeconomic status at age 15 years, mother's education, and dummies for region. Dependent variable equals 1 if highest level of education completed is senior high school (SHS) or tertiary, and 0 otherwise. ***p < 0.01, **p < 0.05, *p < 0.1.

Table G.3 Linear Probability Model of Being Employed, Controlling for Socioemotional Skills Time preference Socioemotional skills Time preference (score) Risk aversion (score) Hostile bias (score) Grit (score)

Risk

Hostile bias

Grit

Big five

−0.0108 (0.0150) −0.0047 (0.0130) −0.0023 (0.0201) −0.0194 (0.0240)

Openness (score)

−0.0006 (0.0281) 0.0254 (0.0280)

Conscientiousness (score)

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Effect of Socioemotional Skills on Education and Labor Outcomes

Table G.3 Linear Probability Model of Being Employed, Controlling for Socioemotional Skills (continued)

Time preference

Risk

Hostile bias

Grit

Extraversion (score)

−0.0228 (0.0267) −0.0402* (0.0237) −0.0083 (0.0257)

Agreeableness (score) Emotional stability (score) Controls Female (%) Age Middle socioeconomic status (%) High socioeconomic status (%) Mother’s education Primary Secondary Tertiary Dummy for region Number of observations R2

Big five

−0.1072*** (0.0302) 0.0068*** (0.0015) 0.0677 (0.0483) 0.0795 (0.0518)

−0.1067*** (0.0302) 0.0068*** (0.0015) 0.0677 (0.0483) 0.0794 (0.0517)

−0.1065*** (0.0301) 0.0068*** (0.0015) 0.0673 (0.0479) 0.0785 (0.0512)

−0.1086*** (0.0303) 0.0069*** (0.0015) 0.0654 (0.0469) 0.0794 (0.0517)

−0.1048*** (0.0304) 0.0070*** (0.0015) 0.0690 (0.0480) 0.0816 (0.0526)

−0.1510* (0.0895) −0.0908 (0.0568) −0.2269* (0.1359) x

−0.1518* (0.0906) −0.0889 (0.0564) −0.2259* (0.1360) x

−0.1520* (0.0904) −0.0892 (0.0564) −0.2256* (0.1334) x

−0.1536* (0.0902) −0.0892 (0.0563) −0.2238* (0.1337) x

−0.1592* (0.0893) −0.0929* (0.0558) −0.2247* (0.1365) x

1,362 0.091

1,362 0.092

1,362 0.096

Note: All models estimated using ordinary least squares. Robust standard errors in parentheses. Controls include gender, age, socioeconomic status at age 15 years, mother's education, and dummies for region. Dependent variable equals 1 if employed and 0 if not employed and not in education. ***p < 0.01, **p < 0.05, *p < 0.1.

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Effect of Socioemotional Skills on Education and Labor Outcomes

Table G.4 Linear Probability Model of Being Self-Employed, Controlling for Socioemotional Skills Time preference Socioemotional skills Time preference (score)

Risk

Hostile bias

Grit

−0.0007 (0.0190)

Risk aversion (score)

−0.0408*** (0.0158)

Hostile bias (score)

0.0878*** (0.0223)

Grit (score)

0.0077 (0.0313)

Openness (score)

0.0308 (0.0314) −0.0882*** (0.0342) −0.0712** (0.0282) −0.0328 (0.0297) −0.0516* (0.0307)

Conscientiousness (score) Extraversion (score) Agreeableness (score) Emotional stability (score) Controls Female (%) Age Middle socioeconomic status (%) High socioeconomic status (%) Mother’s education Primary Secondary Tertiary Dummy for region Number of observations R2

Big five

0.2829*** (0.0363) 0.0056*** (0.0018) −0.0159 (0.0478) 0.1039* (0.0554)

0.2805*** (0.0361) 0.0053*** (0.0018) −0.0187 (0.0479) 0.1070* (0.0554)

0.2765*** (0.0362) 0.0053*** (0.0017) −0.0093 (0.0470) 0.1049* (0.0547)

0.2840*** (0.0366) 0.0056*** (0.0018) −0.0160 (0.0478) 0.1026* (0.0557)

0.2621*** (0.0367) 0.0068*** (0.0017) −0.0099 (0.0468) 0.1139** (0.0535)

0.0343 (0.1002) −0.0321 (0.0660) 0.0096 (0.1073) x

0.0332 (0.0993) −0.0377 (0.0644) 0.0167 (0.1037) x

0.0401 (0.0979) −0.0323 (0.0676) 0.0057 (0.1030) x

0.0350 (0.0999) −0.0324 (0.0659) 0.0083 (0.1070) x

0.0272 (0.0979) −0.0219 (0.0658) 0.0264 (0.1025) x

1,089 0.121

1,089 0.128

1,089 0.137

1,089 0.121

1,089 0.144

Note: All models estimated using ordinary least squares. Robust standard errors in parentheses. Controls include gender, age, socioeconomic status at age 15 years, mother's education, and dummies for region. Dependent variable equals 1 if selfemployed and 0 if wage employed. ***p < 0.01, **p < 0.05, *p < 0.1.

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Effect of Socioemotional Skills on Education and Labor Outcomes

Table G.5 Linear Probability Model of Working in a Medium- to High-Skilled Occupation, Controlling for Socioemotional Skills Time preference Socioemotional skills Time preference (score)

Risk

Hostile bias

Grit

Big five

−0.0113 (0.0179)

Risk aversion (score)

0.0144 (0.0153)

Hostile bias (score)

−0.0244 (0.0232)

Grit (score)

0.0388 (0.0286)

Openness (score)

0.0366 (0.0346) 0.0351 (0.0331) 0.0261 (0.0282) 0.0481 (0.0305) 0.0722** (0.0317)

0.2295*** (0.0357) −0.0004 (0.0018) 0.0951* (0.0492) 0.0988* (0.0546)

0.2314*** (0.0355) −0.0002 (0.0018) 0.0957* (0.0492) 0.0970* (0.0545)

0.2323*** (0.0357) −0.0003 (0.0017) 0.0929* (0.0495) 0.0979* (0.0550)

0.2358*** (0.0361) −0.0004 (0.0018) 0.0944* (0.0491) 0.0916* (0.0550)

0.2571*** (0.0353) −0.0011 (0.0018) 0.0898* (0.0509) 0.0784 (0.0565)

−0.0877 (0.0907) −0.0226 (0.0548) −0.1785 (0.1160) x

−0.0841 (0.0918) −0.0179 (0.0541) −0.1808 (0.1146) x

−0.0861 (0.0898) −0.0199 (0.0549) −0.1772 (0.1149) x

−0.0822 (0.0894) −0.0223 (0.0545) −0.1846 (0.1148) x

−0.0718 (0.0848) −0.0289 (0.0532) −0.1919* (0.1071) x

1,089 0.091

1,089 0.092

1,089 0.113

Note: All models estimated using ordinary least squares. Robust standard errors in parentheses. Controls include gender, age, socioeconomic status at age 15 years, mother's education, and dummies for region. Dependent variable equals 1 if working in medium- or high-skilled occupation and 0 if working in low-skilled occupation. ***p < 0.01, **p < 0.05, *p < 0.1.

Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

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Stepping Up Skills in Urban Ghana • http://dx.doi.org/10.1596/978-1-4648-1012-1

The Skills Toward Employment and Productivity (STEP) survey is an initiative of the World Bank in cooperation with other development partners and nongovernmental agencies. STEP was carried out in more than 14 countries globally. In Ghana, the first phase of the survey, focusing on adults in urban communities, was undertaken in partnership with the University of Ghana’s Institute of Statistical, Social, and Economic Research; the Ministry of Education; the Council for Technical and Vocational Education and Training; and the Ghana Statistical Service. Stepping Up Skills in Urban Ghana provides detailed insights from the survey for policy makers. These insights cover areas including investments in early childhood education, the role of improvements in the quality of education, and the creation of incentives for economic actors to invest in on-the-job training to improve Ghana’s competitiveness and the well-being of its citizens.

ISBN 978-1-4648-1012-1

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