Housing Market Spillovers through the Lens of Transaction Volume : A New Spillover Index Approach

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 China's current government intervention strategy, which mainly focuses on the transaction volume in the housing markets