Housing Market Spillovers in China via Trading Volume: A Comparison of Two Spillover Indexes

Abstract

Proposing a new spillover/connectedness index based on data-determined structural vector autoregression (SVAR) with non-Gaussian residuals, this paper investigates nationwide housing market spillovers via transaction volumes among China's largest cities. Significant daily information transmission is documented across geographically dispersed cities, with a pattern that the first-tier cities generally play a more important role than others in the spillovers. Economic factors (e.g., income) and human capital (e.g., education) are significant determinants of the spillovers. The pattern based on the new spillover index is also substantially better explained by fundamentals than those based on the widely used Diebold-Yilmaz spillover index.