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• W3205116741 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." @default.
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• W3205116741 date "2021-12-01" @default.
• W3205116741 modified "2023-10-16" @default.
• W3205116741 title "Housing market spillovers through the lens of transaction volume: A new spillover index approach" @default.
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• W3205116741 doi "https://doi.org/10.1016/j.jempfin.2021.10.003" @default.
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