House Price Fluctuations, Financial Stability,and Optimal Macroprudential Policies
SI Dengkui, GE Xinyu, ZENG Tao, LI Xiaolin
School of Economics, Qingdao University; Dongwu Business School, Soochow University; School of Economics and Academy of Financial Research, Zhejiang University; School of Economics, Ocean University of China
Summary:
Many of the financial crises that have occurred in recent decades arose from excess credit expansion induced by a rapid, unsustainable growth of house prices. Such an excess credit expansion threatens the stability of the financial system. China, as the world's second largest economy, has been experiencing an unprecedented housing boom accompanied by rapid credit expansion in the wake of the 1998 housing commercialization reform. It is thus a matter of public concern, and of great interest to authorities, how to maintain financial stability by policy interventions. In recent years, there has been a growing consensus among scholars that in addition to monetary instruments, macroprudential instruments might be good alternative candidates for containing the financial imbalances induced by large swings in house prices. However, the design of an appropriate macroprudential tool and the desirable degree of intervention remain matters of academic controversy. Using Chinese data, we develop and estimate a dynamic stochastic general equilibrium (DSGE) model that allows for financial frictions tied to households and financial intermediaries. The model is used to address two sets of issues associated with the Chinese economy. First, we investigate the extent to which the model can account for empirical evidence that house price fluctuations affect investment, loans, and bank leverage ratio over the business cycle. In particular, a positive shock to house prices directly drives up house prices and housing investment, leading to an increase in loans. It then causes a rise in the interest spread and subsequently encourages banks to raise their leverage ratio. In the presence of financial frictions, the effects of housing demand shocks are amplified and propagated over time. In this regard, a rapid growth of house prices may undermine financial stability. Second, we conduct counter-cyclical experiments with macroprudential instruments (loan-to-value ratio and capital adequacy ratio) to examine the extent to which they can stabilize the housing market, the financial system, and the macroeconomy as financial imbalances increase. The contributions of this paper are threefold. First, we build a theoretical model with a rigorous micro-foundation to study the interaction between the financial and housing markets over the business cycle during the housing boom in China. Second, the baseline model with financial frictions is capable of capturing the mechanism by which fluctuations in house prices initiated by an exogenous shock influence the bank's balance sheet and the macroeconomy. Third, it provides a better understanding of the effectiveness of macroprudential tools in alleviating the instability of the financial and housing market under different shocks. The main results of this paper are as follows. With the estimated parameters, the model successfully accounts for the joint behaviors of house prices, investment, loans, and bank leverage ratio observed in the data. More importantly, it captures the mechanism by which fluctuations in house prices affect the bank's balance sheet and the macroeconomy as a whole in response to exogenous shocks to house prices. Moreover, we find that a countercyclical loan-to-value (LTV) requirement that directly responds to the credit gap and house price gap can effectively stabilize the financial and housing markets and improve social welfare in response to a housing preference shock, but it does poorly in response to productivity and time preference shocks. Lastly, a countercyclical capital adequacy requirement that directly responds to the credit gap and house price gap performs well in stabilizing the economy and improving social welfare when productivity and time preference shocks impinge on the economy. This paper not only provides a better understanding of the link between house price fluctuations and financial stability but also reveals the importance of macroprudential policies in maintaining the stability of the financial and housing markets. Our results suggest that macroprudential authorities should distinguish the sources of house price fluctuations when designing and implementing policies. Failure to do so may lead to enormous losses of welfare to society and the economy.
[1]陈彦斌、郭豫媚和陈伟泽,2015:《2008年金融危机后中国货币数量论失效研究》,《经济研究》第4期,第21~35页。 [2]方意,2015:《货币政策与房地产价格冲击下的银行风险承担分析》,《世界经济》第7期,第73~98页。 [3]方意、赵胜民和谢晓闻,2012:《货币政策的银行风险承担分析——兼论货币政策与宏观审慎政策协调问题》,《管理世界》第11期,第9~19页。 [4]何青、钱宗鑫和郭俊杰,2015:《房地产驱动了中国经济周期吗?》,《经济研究》第12期,第41~53页。 [5]康力和龚六堂,2014:《金融摩擦、银行净资产与国际经济危机传导》,《经济研究》第5期,第147~159页。 [6]况伟大和王琪琳,2017:《房价波动、房贷规模与银行资本充足率》,《金融研究》第11期,第34~48页。 [7]陆磊和杨骏,2016:《流动性、一般均衡与金融稳定的“不可能三角”》 ,《金融研究》第1期,第1~13页。 [8]马勇和陈雨露,2013:《宏观审慎政策的协调与搭配:基于中国的模拟分析》,《金融研究》第8期,第57~69页。 [9]王爱俭和王璟怡,2014:《宏观审慎政策效应及其与货币政策关系研究》,《经济研究》第4期,第17~31页。 [10]徐忠,2017:《中国稳健货币政策的实践经验与货币政策理论的国际前沿》,《金融研究》第1期,第1~21页。 [11]张建华和贾彦东,2012:《宏观审慎政策的理论与实践进展》,《金融研究》第1期,第20~35页。 [12]张晓晶和孙涛,2006:《中国房地产周期与金融稳定》,《经济研究》第1期,第23~33页。 [13]赵扶扬、王忏和龚六堂,2017,《土地财政与中国经济波动》,《经济研究》第12期,第46~61页。 [14]Allen, F., and Gale, D.,2000, “Financial Contagion”. Journal of Political Economy, 108(1):1~33. [15]Carroll, C. D., 2006, “The Method of Endogenous Gridpoints for Solving Dynamic Stochastic Optimization Problems”, Economics Letters, 91(3):312~320. [16]Davis, M. A., and Heathcote, J., 2005,“Housing and the Business Cycle” ,International Economic Review, 46(3):751~784. [17]Delis, M. D., and Kouretas, G. P., 2011, “Interest Rates and Bank Risk-taking”. Journal of Banking & Finance, 35(4): 840~855. [18]Fendogˇlu S., 2014, “Optimal Monetary Policy Rules, Financial Amplification, and Uncertain Business Cycles”. Journal of Economic Dynamics and Control, (46):271~305. [19]Gerali, A., Neri, S., Sessa, L., and Signoretti, F. M. ,2010, “Credit and Banking in a DSGE Model of the Euro Area”,Journal of Money, Credit and Banking, 42(s1):107~141. [20]Gertler, M., and Karadi, P. ,2011, “A Model of Unconventional Monetary Policy”,Journal of Monetary Economics, 58(1):17~34. [21]Gertler, M., and Kiyotaki, N. ,2015, “Banking, Liquidity, and Bank Runs in an Infinite Horizon Economy”, American Economic Review, 105(7): 2011~43. [22]Gertler, M., and Kiyotaki, N., 2010, “Financial Intermediation and Credit Policy in Business Cycle Analysis”, In Handbook of Monetary Economics , (3):547~599. [23]Gertler, M., Kiyotaki, N., and Queralto, A., 2012, “Financial Crises, Bank Risk Exposure and Government Financial Policy”,Journal of Monetary Economics, (59):S17~S34. [24]Gervais, M. ,2002, “Housing Taxation and Capital Accumulation”, Journal of Monetary Economics, 49(7):1461~1489. [25]Iacoviello, M. ,2005, “House Prices, Borrowing Constraints, and Monetary Policy in the Business Cycle”,American Economic Review, 95(3): 739~764. [26]Iacoviello, M., and Neri, S. ,2010,“Housing Market Spillovers: Evidence from an Estimated DSGE Model”,American Economic Journal: Macroeconomics, 2(2):125~164. [27]Iacoviello, M., and Pavan, M., 2013, “Housing and Debt Over the Life Cycle and Over the Business Cycle”, Journal of Monetary Economics, 60(2):221~238. [28]Kiley, M. T., and Sim, J., 2017, “Optimal Monetary and Macroprudential Policies: Gains and Pitfalls in a Model of Financial Intermediation”,Journal of Macroeconomics, (54):232~259. [29]Kiyotaki, N., Michaelides, A., and Nikolov, K., 2011, “Winners and Losers in Housing Markets”,Journal of Money, Credit and Banking, 43(2‐3):255~296. [30]Mendicino, C., and Punzi, M. T.,2014, “House Prices, Capital Inflows and Macroprudential Policy”,Journal of Banking & Finance, (49):337~355. [31]Niinimäi, J. P., 2009, “Does Collateral Fuel Moral Hazard in Banking”, Journal of Banking & Finance, (33): 514~521.