Housing market spillovers through the lens of transaction volume: A new spillover index approach

Abstract

Proposing and applying a new spillover index approach based on data-determined structural vector autoregression to measure connectedness, we examine the daily housing market information transmission via transaction volume among Chinese city-level housing markets from 2009 to 2018. We document substantial information transmission on Chinese housing markets even within one day and find that the role a city-level housing market may play in the information transmission network resembles a pattern observed on other financial markets, which can be generally classified into three distinctive groups: prime senders, exchange centers, and prime receivers. City hierarchy and some fundamental economic factors, such as GDP per capita and average wage, appear to be significant determinants of such a pattern. The findings extend the existing voluminous literature solely based on housing prices or price volatility spillovers and shed new light on the China’s government intervention strategy on the housing market.