Although there is a consensus that the housing market is deeply affected by credit policies, little research is available on the impact of credit policies on housing market liquidity. Moreover, housing market liquidity is not scientifically quantified and monitored in China. To improve the government’s intelligence in monitoring the fluctuation of the housing market and make more efficient policies in time, the dynamic relationship between credit policy and housing liquidity needs to be understood fully. On the basis of second-hand housing transaction data in Beijing from 2013 to 2018, this paper uses a time-varying parameter vector autoregressive model and reveals several important results. First, loosening credit policies improves the housing market liquidity, whereas credit tightening reduces the housing market liquidity. Second, both the direction and the duration of the impacts are time-varying and sensitive to the market conditions; when the housing market is downward, the effect of a loose credit policy to improve market liquidity is weak, and when the housing market is upward, market liquidity is more sensitive to monetary policy. Finally, the housing market confidence serves as an intermediary between credit policy and housing market liquidity. These results are of great significance to improve the intelligence and efficiency of the government in monitoring and regulating the housing market. Several policy recommendations are discussed to regulate the housing market and to stabilize market expectations.
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This work was supported by the National Natural Science Foundation of China (No. NSFC71804206).
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