ON PRICE CO-MOVEMENT AND VOLATILITY SPILLOVER EFFECTS IN CHINA’S HOUSING MARKETS

Yingliang Weng,Pu Gong

doi:10.3846/1648715x.2016.1271369

Abstract

The soaring property prices in many Chinese cities have recently attracted increasing attention. This study uses the data on housing price indices from January 2005 to December 2014 in 10 large Chinese cities to analyze volatility spillover effects and to identify the determinants of price co-movement across the China’s regional housing markets. This research proposes a novel dynamic spatial panel data model that accounts for multivariate asymmetrical generalized autoregressive conditional heteroskedasticity components in disturbances to address these issues empirically. Results reveal that housing prices in cities are significantly influenced by population, income, mortgage rates, policy factors, and the national macroeconomic situation. The analysis further indicates that the housing returns of regions in China that are in close geographic and economic proximities exhibit strong co-movement and volatility spillovers. Evidence of significantly positive leverage effects in regional housing markets is also determined. This study’s findings have significant implications for academic researchers, financial experts, and policy makers.

Highlights

Housing is often considered a heterogeneous good in finance and economics, and includes physical characteristics and neighborhood characteristics
Regional housing price indices are obtained from China Real Estate Index System (CREIS), which is compiled by SouFun Holdings Limited, a company listed on the New York Stock Exchange
The results in specifications 1 and 2 indicate that both the geographic spatial weight matrix (SWM) and the economic SWM are essential in studying the price co-movement and volatility spillovers across regional housing markets

Summary

Introduction

Housing is often considered a heterogeneous good in finance and economics, and includes physical characteristics (e.g., construction conditions, internal area, and age) and neighborhood characteristics (e.g., accessibility to central business district, distance to subway stations, and behavior of nearby residents). The present study aims to empirically analyze volatility spillover effects and to identify the determinants of the co-movements of housing prices across 10 regional housing markets in China from January 2005 to December 2014. The comovement and volatility spillovers in housing returns are often attributed to the change in demand for properties because of information linkages across regional housing markets and information spillovers resulting from interregional trades. Many factors such as migration, purchasing investment properties, and contagious reactions to information linkages across housing markets can result in spatial interactions and volatility spillovers among regional housing markets. The outbreak of the global financial crisis in 2007–2009 once again showed that global financial markets are more interconnected among cities, states, regions, and countries (Bauwens et al 2006; Gong, Weng 2016; Weng, Gong 2016)

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Results

Conclusion