Real Estate Market Adjustment, Bank Balance Sheets, and Monetary Policy Response
GAO Songyao, WANG Jiaxin, CUI Baisheng
Postdoctoral Research Workstation, Foreign Exchange Research Center, State Administration of Foreign Exchange; Postdoctoral Research Mobile Station, Financial Research Institute, People's Bank of China; HSBC Business School, Peking University; School of Finance and Business, Shanghai Normal University
Summary:
In August 2020, the People's Bank of China, along with the China Banking and Insurance Regulatory Commission and other institutions, introduced the “Three Red Lines” policy targeting the real estate sector. Subsequently, China's real estate market entered a downward trajectory, leading to a contraction in bank credit. Why did this happen? This paper analyzes the transmission mechanisms and pathways through which the real estate market adjustment since 2021 has contributed to an overall decline in social investment. Furthermore, it examines the effectiveness of different monetary policy measures and the combined effects of policy interventions. Empirical evidence reveals that, on one hand, the real estate sector in China is highly intertwined with bank credit. A decline in housing prices leads to a reduction in real estate loans, which, in turn, results in the contraction of commercial banks' balance sheets and a decrease in the scale of credit. On the other hand, falling housing prices lead to a decline in land prices, reducing local government fiscal revenue and subsequently diminishing capital demand from non-real estate sectors. Based on these facts and logical connections, this paper develops a multi-sector dynamic stochastic general equilibrium (DSGE) model that incorporates both real estate and non-real estate sectors. The model introduces local governments to depict land financing behavior and incorporates the banking sector to capture financial frictions. This framework is used to analyze the impact of declining real estate demand on commercial banks' balance sheets, as well as the effectiveness of various policies in improving commercial banks' balance sheets and the broader macroeconomy. Theoretical model results indicate that, on one hand, a decline in real estate demand leads to a decrease in investment in the real estate sector and a drop in asset prices. On the other hand, falling housing prices result in lower land prices, reducing local government land revenues, which in turn decreases capital demand and asset prices in the non-real estate sector. The decline in asset prices across both sectors leads to a reduction in commercial banks' net worth, thereby constraining their credit supply. If the central bank lowers the reserve requirement ratio (RRR), it can improve commercial banks' balance sheets and enhance credit supply. If the central bank reduces the interest rates on existing housing loans, this could help boost household consumption but may also reduce banks' net worth, further constraining credit supply. In this case, it would be necessary to inject additional capital into commercial banks. This paper offers the following policy recommendations. First, in the short term, targeted policies should be implemented to improve the balance sheets of commercial banks, while in the long term, efforts should be made to reduce the dependence of commercial banks on the real estate sector. Second, when reducing interest rates on existing housing loans, it is essential to simultaneously inject capital into commercial banks. Third, fiscal and taxation system reforms should be advanced in a coordinated manner to expand local tax sources. The contributions of this paper are primarily reflected in three aspects. First, although existing literature has explored the connections between the real estate market and commercial banks, the analysis of banks' balance sheets remains insufficient. This paper collects and organizes relevant data to analyze the relationship among the real estate market, commercial banks' balance sheets, and the macroeconomy. It provides a new perspective for understanding the interactions between the real estate market and the financial system, as well as empirical evidence for building theoretical models. Second, previous studies have mostly focused on the crowding-out effect of rising housing prices on the non-real estate sector. However, in the current context of declining housing prices, not only has investment in the non-real estate sector failed to improve, but the overall scale of social credit has also declined. Following Gertler and Karadi (2011), this paper incorporates the banking sector into a DSGE model to analyze the impact of declining housing prices on land financing, while also considering the dual negative effects of banking financial frictions on credit supply. The findings differ from the transmission mechanisms studied during periods of rising housing prices and offer theoretical and practical significance for understanding the impact of declining housing prices on the overall credit scale and macroeconomic fluctuations. Third, there is a relative lack of literature within a general equilibrium framework that examines the effects of reducing the RRR and lowering interest rates on existing housing loans. Given the close ties among China's real estate market, commercial banks, and land financing, this paper introduces three policy tools: reducing the RRR, lowering interest rates on existing housing loans, and injecting capital into commercial banks. It analyzes the transmission pathways and effects of these policy tools on housing price regulation.
[1]董丰、周基航和贾彦东,2023,《资产泡沫与最优货币政策》,《金融研究》第6期,第1~19页。 [2]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。 [3]侯成琪和龚六堂,2014,《货币政策应该对住房价格波动作出反应吗——基于两部门动态随机一般均衡模型的分析》,《金融研究》第10期,第15~33页。 [4]康立、龚六堂和陈永伟,2013,《金融摩擦、银行净资产与经济波动的行业间传导》,《金融研究》第5期,第32~46页。 [5]刘建丰、于雪、彭俞超和许志伟,2020,《房产税对宏观经济的影响效应研究》,《金融研究》第8期,第34~53页。 [6]陆磊和刘学,2020,《违约与杠杆周期——一个带有救助的金融加速器模型》,《金融研究》第5期,第1~20页。 [7]马理和范伟,2021,《促进“房住不炒”的货币政策与宏观审慎“双支柱”调控研究》,《中国工业经济》第3期,第5~23页。 [8]马勇、姜伊晴和郭锐,2023,《经济开放、金融开放与双支柱调控的政策工具组合研究》,《金融研究》第11期,第1~20页。 [9]马勇和姚驰,2021,《双支柱下的货币政策与宏观审慎政策效应——基于银行风险承担的视角》,《管理世界》第6期,第51~69页。 [10]梅冬州、崔小勇和吴娱,2018,《房价变动、土地财政与中国经济波动》,《经济研究》第1期,第35~49页。 [11]孟宪春,2023,《房价对家庭债务和财富分布的影响:理论机制与应对策略》,《经济研究》第4期,第171~189页。 [12]孟宪春、张屹山和李天宇,2018,《有效调控房地产市场的最优宏观审慎政策与经济“脱虚向实”》,《中国工业经济》第6期,第81~97页。 [13]荣昭和王文春,2014,《房价上涨和企业进入房地产——基于我国非房地产上市公司数据的研究》,《金融研究》第4期,第158~173页。 [14]吴迪、张楚然和侯成琪,2022,《住房价格、金融稳定与宏观审慎政策》,《金融研究》第7期,第57~75页。 [15]吴海民,2012,《资产价格波动、通货膨胀与产业“空心化”——基于我国沿海地区民营工业面板数据的实证研究》,《中国工业经济》第1期,第46~56页。 [16]徐海霞和吕守军,2019,《我国货币政策与宏观审慎监管的协调效应研究》,《财贸经济》第3期,第53~67页。 [17]许宪春、贾海、李皎和李俊波,2015,《房地产经济对中国国民经济增长的作用研究》,《中国社会科学》第1期,第84~101页。 [18]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。 [19]朱军和许志伟,2018,《财政分权、地区间竞争与中国经济波动》,《经济研究》第1期,第21~34页。 [20]Bernanke, B. S., M. Gertler and S. Gilchrist, 1999, “The Financial Accelerator in a Quantitative Business Cycle Framework,” Handbook of Macroeconomics, 1(C), pp. 1341~1393. [21]Chang, C., K. Chen, D. F. Waggoner, and T. Zha, 2016, “Trends and Cycles in China's Macroeconomy”, NBER Macroeconomics Annual, 30(1), pp.1~84. [22]Christensen, I. and A. Dib, 2008, “The Financial Accelerator in an Estimated New Keynesian Model”, Review of Economic Dynamics, 11(1), pp.155~178. [23]Gertler, M. and P. Karadi, 2011, “A Model of Unconventional Monetary Policy”, Journal of Monetary Economics, 58(1), pp.17~34. [24]Gertler, M., S. Gilchrist and F. M. Natalucci, 2007, “External Constraints on Monetary Policy and the Financial Accelerator ”, Journal of Money, Credit and Banking, 39(2-3), pp. 295~330. [25]Greenwald, D., 2018, “The Mortgage Credit Channel of Macroeconomic Transmission”, SSRN Working Paper. [26]Guerrieri, L. and M. Iacoviello, 2017, “Collateral Constraints and Macroeconomic Asymmetries ”, Journal of Monetary Economics, 90, pp.28~49. [27]Iacoviello, M., 2005, “House Prices, Borrowing Constraints, and Monetary Policy in the Business Cycle”, American Economic Review, 95(3), pp.739~764. [28]Jiang, S., J. Miao and Y., Zhang, 2022, “China's Housing Bubble, Infrastructure Investment, and Economic Growth”, International Economic Review, 63(3), pp.1189~1237. [29]Leamer, E. E., 2007. “Housing is the Business Cycle”, NBER Working Paper, No.13428. [30]Liu, Z., P. Wang and T. Zha, 2013, “Land‐price Dynamics and Macroeconomic Fluctuations”, Econometrica, 81(3), pp.1147~1184. [31]Mendicino, C. and M. T. Punzi, 2014, “House Prices, Capital Inflows, and Macroprudential Policy”, Journal of Banking and Finance, 49, pp.337~355. [32]Mendicino, C., K. Nikolov, J. Suarez and D. Supera, 2018, “Optimal Dynamic Capital Requirements”, Journal of Money, Credit and Banking, 50(6), pp.1271~1297. [33]Sims, E., and J.C. Wu, 2018, “Evaluating Central Banks Tool Kit: Past, Present, and Future”, Journal of Monetary Economics, 118, pp.135~160. [34]Tavman, Y., 2015, Optimal Policy Before, During and After the Crisis, PhD thesis, University of York.