ISSN 2348-1218 (print) International Journal of Interdisciplinary Research and Innovations ISSN 2348-1226 (online) Vol. 8, Issue 4, pp: (62-67), Month: October - December 2020, Available at: www.researchpublish.com
The effect of Geographical Space and Policy Shocks on Urban House Prices Gao- lu Zou College of Tourism, Economic, and Culture, Chengdu University, Chengdu, China
Abstract: Located in Southwest China, Guiyang and Chengdu are two spatially close cities. Hence, their housing markets may move together due to similar macro-regulative policies, short geographical distance, and close trade ties. This paper tested for structural breaks and long-run equilibria for the new housing markets in Guiyang and Chengdu. Data were monthly house price indices over the period from January 2007 to December 2018. We conducted ADF, PP tests, and Perron tests (Model C). Cointegration tests used the Engle-Granger and Johansen methods. We found a long-run relationship, which may be attributed to busy business exchanges and frequent population migration. Guiyang’s home prices were weakly exogenous. In the long run, the 1% change in the price in Guiyang leads to a 0.43% growth in Chengdu. A uni-directional causal effect was suggested running from Chengdu to Guiyang. In the short run, the 1% change in the price in Chengdu leads to a 0.16% growth in Guiyang. Both in the long and the short run, home investors may not gain from a portfolio across these two cities. Evidence shows that policy shocks can change price trends. Keywords: House price, long run, market, dynamic, Granger causality, ECM model.
I. INTRODUCTION Located in Southwest China, Guiyang and Chengdu are the capitals of Guizhou Province and Sichuan Province, respectively. The distance between these two cities is 520 km. One can take a high-speed train to shuttle between these two cities, three hours are taken. Investments in housing properties in both cities have attracted many people. However, policy shocks (risks) exist. For example, since 2015, buying homes in non-residential cities are not allowed by the Central Government. Literature shows that urban and regional housing markets impact each other [1-12]. This paper tested for structural breaks and long-run equilibria for the new housing markets in Guiyang and Chengdu.
II. METHODS We conducted cointegration tests to examine long-run relations between housing markets [13-17]. The Johansen test used the following vector autoregressive model (VAR): (1) We estimated . Given that variables were cointegrated, we estimated a valid linear error-correction model (ECM) between I(1) variables. We conducted the Granger causality test in estimated ECMs; Wald-χ2 tests were applied [18-21]. We tested for unit roots using the augmented Dickey-Fuller (ADF) [22-24], Phillips-Perron (PP) [25]. We tested for a structural shift using the following Perron IO Model C [26-28]: ∑
(2)
III. DATA Data was the monthly new commodity house price index as compared with the same of last year. for the period from January 2007 to December 2018. Two time series are new house prices in Chengdu (HP_CHENGDU) and new house prices in Guiyang (HP_GUIYANG). Data were from NBSC [29]. We seasonally adjusted monthly series using the X-13
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