Summary:
Many papers, when constructing indices of China's financial cycle, include indicators of real estate market conditions as components. However, although many researchers believe that China's real estate sector and financial sector are closely related, there has been little research on this dynamic relationship.In this paper, we attempt to fill this gap by studying the dynamic impact of China's financial cycle on the real estate price. We do this in two steps. First, we construct an index of China's financial cycle that comprises five financial indicators: stock market performance, interest rate, capital flow, leverage, and money supply. We aggregate the five indicators as a simple average. In the second step, we construct a three-variate vector autoregressive (VAR) model that includes an indicator of real activities, an indicator of real estate price, and our index of China's financial cycles. The VAR model has a few characteristics. First, we allow the regression coefficients to change over time. Second, we allow the size of the economic shocks to vary over time. Third, we use a recursive scheme to identify structural economic shocks. These characteristics are important for the following reasons. First, China's economy is continuously under reform. These reforms could cause structural changes in the dynamic relationship between the real estate and financial sectors, and omitting those structural changes could lead to misleading results. Allowing the coefficients of the VAR to vary over time should capture those structural changes. Second, due to the changing domestic and foreign economic environment, sources of economic uncertainty change over time. As a result, the size of the shocks to our endogenous variables might also change over time. Third, it is well known that simply interpreting the error terms of the reduced-form VAR as economic shocks omits contemporary correlations between endogenous variables, which can lead to misleading conclusions. Therefore, our VAR model is a structural vector autoregressive model with stochastic volatility and time-varying parameters. The variables in the model are entered in the following order: first, the indicator of real activities, second, the indicator of real estate price, and third, our index of China's financial cycle. We estimate our model using quarterly data from 2004 to 2016. When constructing our index of China's financial cycles, we use the Shanghai stock market index as the indicator of stock market performance. We use the 7-day inter-bank market interest rate to represent interest rates; the ratio of fixed assets financed by credit to total fixed assets investment as the indicator of leverage; the ratio of the capital and financial account balance to GDP as the indicator of capital flow; and the year-on-year M2 growth rate as the indicator of money supply. Our indicator of real activities is the year-on-year GDP growth rate. Our indicator of real estate price is the China Quality-Controlled Housing Price Index. The results show that the structural economic shocks to China's economy vary in size over time. The volatility of real activities reached its peak in 2009 and then gradually declined. This suggests that China's macroeconomic policies have helped to stabilize economic growth since the global financial crisis. The volatility of the real estate price also demonstrates a declining trend. However, the trend reversed in 2014 and the real estate price volatility increased until 2016. These results suggest that China's real estate market was developing stably. However, uncertainty has increased in recent years(2015-2016). The volatility of our index of financial cycles gradually increases, suggesting that financial risk during the sample period deserves more attention. The impact of financial cycle on real estate prices has obvious time-varying characteristics. Before 2008, financial market expansion had a stable influence on the promotion of housing prices, but since 2008, the impact has gradually weakened. Similar to financial shocks, the impact of the real economy on housing prices has also gradually decreased since 2008. This shows that regulatory policies have helped to greatly reduce the sensitivity of real estate prices to economic and financial shocks. The finding that the impact of financial cycles on the real estate price has weakened has important policy implications. A finance-led real estate boom is less likely, which means that the transmission from financial expansion to economic growth through the real estate sector has become less effective since 2008; instead, excessive financial risk-taking accumulates systemic risk. Macro-prudential policies regarding the real estate market are necessary.
钱宗鑫, 王芳, 孙挺. 金融周期对房地产价格的影响——基于SV-TVP-VAR模型的实证研究[J]. 金融研究, 2021, 489(3): 58-76.
QIAN Zongxin, WANG Fang, SUN Ting. The Impact of Financial Cycle on Real Estate Prices: An Empirical Study Based on a SV-TVP-VAR Model. Journal of Financial Research, 2021, 489(3): 58-76.
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