Abstract:After the 2008 financial crisis, macro-prudential supervision has been generally valued across the world. The People’s Bank of China formally established a Macro Prudential Assessment (MPA) system in 2016, with the macro-prudential capital adequacy ratio as the core, including seven major aspects of capital and leverage, liquidity, asset quality, etc., to prevent and resolve potential systemic risks in the financial system. However, various financial risks have gradually surfaced with the long-term growth of Chinese economy. The real estate industry is over-prosperous, and bank credit has had unbalanced expansion, forming a positive cycle of agglomeration of systemic risks. In order to enhance the banking industry’s ability to defend against the volatility of the real estate market, and in the meanwhile to alleviate the real estate bubble caused by the over-concentration of credit to regulate the financial risks of banking and real estate industry, the People’s Bank of China launched a macro-prudential policy of personal housing loan ratio at the end of 2020 to further enrich the existing MPA system.The existing literature on the research of macro-prudential policy mainly focuses on real estate and banking financial risks, the effect of macro-prudential policy implementation, and the macro-prudential policy of real estate finance. However, there are still some deficiencies: First, no research has been found to quantify the effect of personal housing loan ratio. Even if it is a qualitative study, the understanding of this policy is still purely limited to the regulation of housing prices, and the researchers have not discussed the issue from the macro-prudential perspective of stabilizing financial risks. Second, the indicators for evaluating financial risks are one-sided and can hardly represent comprehensive financial risks. Furthermore, there is a lack of discussion on the impact of policies on the real economy. Third, when evaluating policies, most studies only draw conclusions from numerical simulation results, lacking comprehensive theoretical analysis. In view of these deficiencies, this article constructs a six-sector dynamic stochastic general equilibrium model to discuss the theoretical mechanism whereby the personal housing loan ratio policy regulates Chinese financial risks. This policy is then compared with the traditional loan-to-value ratio policy to examine their pros and cons of the risk mitigation under different shocks.Compared with the existing research, this article has the following marginal contributions: (1) The theoretical model analysis of personal housing loan ratio has filled the gap in the existing research to a certain extent; (2) It has made a comprehensive analysis of the dynamic effect of the policy through the impulse response results of multiple financial risk indicators, and discussed its advantages and disadvantages compared with the LTV policy through welfare analysis; (3) Combined with the results of numerical simulation analysis in policy evaluation, it has analyzed the policy effectiveness of theoretical mechanism, and provided practical support for policy implementation.The research has the following findings: (1) Both macro-prudential policies can regulate real estate and banking financial risks, improve overall social welfare, and stabilize fluctuations in major economic and financial variables; (2) Under the impact of housing preferences and technological progress, LTV policies can better regulate financial risks in the short term, while the personal housing loan ratio has a better long-term inhibitory effect. Under the impact of monetary policies, the personal housing loan ratio performs better than LTV both in the long and short terms, and will not have a significant negative impact on economic output; (3) Welfare analysis shows that under the impact of housing preference, the LTV policy brings the greatest welfare improvement to the patient families and best suppresses the welfare of speculative families. Under the impacts of technological progress and monetary policy, the personal housing loan ratio performs better, and the policy choice targeting variables is decided by the type of impact. Based on the above conclusions, this paper attempts to put forward the following three suggestions: First, we should actively adopt macro-prudential policies to mitigate financial risks and avoid the “pro-cyclicality” of monetary policy and financial risks. Second, in the application of macro-prudential policies in real estate finance and the choice of anchor targets, we should act flexibly and adjust macro-prudential policies and their target variables according to the type of external shocks. Third, we should constantly enrich the macro-prudential management toolbox, follow structural policies more closely, and achieve a win-win situation of “stabilizing growth” and “controlling risks”.
王维安, 谢朱斌, 陈梦涛. 中国金融风险调控范式选择:贷款价值比政策还是个人住房贷款占比政策?[J]. 浙江大学学报(人文社会科学版), 2022, 52(6): 66-85.
Wang Weian, Xie Zhubin, Chen Mengtao. The Paradigm of Choice for Financial Risk Control in China: The Loan-to-Value Ratio Policy or the Personal Housing Loan Ratio Policy?. JOURNAL OF ZHEJIANG UNIVERSITY, 2022, 52(6): 66-85.
杨源源、贾鹏飞、高洁超: 《中国房地产长效调控范式选择:房产税政策还是宏观审慎政策》,《财贸经济》2021年第8期,第53-66页。2 Su C., Cai X. & Qin M. et al., “Can bank credit withstand falling house price in China?” International Review of Economics & Finance, Vol. 71, No. 3 (2021), pp. 257-267.3 刘晓星、石广平: 《杠杆对资产价格泡沫的非对称效应研究》,《金融研究》2018年第3期,第53-70页。4 唐建伟、夏丹: 《强化房地产金融宏观审慎监管》,《中国金融》2021年第2期,第90-91页。5 孟宪春、张屹山: 《家庭债务、房地产价格渠道与中国经济波动》,《经济研究》2021年第5期,第75-90页。6 Miao J., Wang P. & Zhou J., “Asset bubbles, collateral, and policy analysis,” Journal of Monetary Economics, Vol. 76 (2015), pp. 57-70.7 Barrell R., Davis E. & Karim D. et al., “Bank regulation, property prices and early warning systems for banking crises in OECD countries,” Journal of Banking & Finance, Vol. 34, No. 9 (2010), pp. 2255-2264.8 陈学胜: 《违约风险、房地产贷款市场博弈与房地产价格》,《统计研究》2019年第4期,第84-94页。9 Jorda O., Schularick M. & Taylor A., “Leveraged bubbles,” Journal of Monetary Economics, Vol. 76 (2015), pp. 1-20.10 方意: 《宏观审慎政策有效性研究》,《世界经济》2016年第8期,第25-49页。11 Angelini P., Neri S. & Panetta F., “The interaction between capital requirements and monetary policy,” Journal of Money, Credit and Banking, Vol. 46, No. 6 (2014), pp. 1073-1112.12 Mendicino C. & Punzi M., “House prices, capital inflows and macroprudential policy,” Journal of Banking & Finance, Vol. 49, No.7 (2014), pp. 337-355.13 贾鹏飞、范从来、褚剑: 《过度借贷的负外部性与最优宏观审慎政策设计》,《经济研究》2021年第3期,第32-47页。14 Selien S. & Frederic O., “Macroprudential policy and its impact on the credit cycle,” https://doi.org/10.1016/j.jfs.2020.100818, 2021-08-31.15 Franta M. & Gambacorta L., “On the effects of macroprudential policies on Growth-at-Risk,” https://doi.org/10.1016/j.econlet.2020.109501, 2021-08-31.16 周晔、陈亚杰: 《宏观审慎政策工具的有效性检验——基于对114家商业银行的实证分析》,《金融监管研究》2021年第1期,第49-65页。17 戴国强、肖立伟: 《欧盟房地产金融宏观审慎管理框架、经验与启示》,《上海金融》2019年第10期,第41-47页。18 朱红、臧晓伟: 《房地产金融宏观审慎管理:工具、效果及启示》,《新金融》2020年第1期,第59-64页。19 Vandenbussche J., Vogel U. & Detragiache E., “Macroprudential policies and housing prices: a new database and empirical evidence for central, eastern, and southeastern Europe,” Journal of Money, Credit and Banking, Vol. 47, No. S1 (2015), pp. 343-377.20 Kuttner K. & Shim I., “Taming the real estate beast: the effects of monetary and macroprudential policies on housing prices and credit,” https://www.rba.gov.au/publications/confs/2012/pdf/kuttner-shim-disc.pdf, 2021-08-31.21 Iacoviello M., “House prices, borrowing constraints, and monetary policy in the business cycle,” American Economic Review, Vol. 95, No. 3 (2005), pp. 739-764.22 孟宪春、张屹山、李天宇: 《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》2018年第6期,第81-97页。23 Cutler M., Poterba M. & Summers H., “Speculative dynamics and the role of feedback traders,” American Economic Review, Vol. 80, No. 2 (1990), pp. 63-68.24 He Y. & Xia F., “Heterogeneous traders, house prices and healthy urban housing market: a DSGE model based on behavioral economics,” https://doi.org/10.1016/j.habitatint.2019.102085, 2021-08-31.25 Abel A. B., “Asset prices under habit formation and catching up with the Joneses,” American Economic Review, Vol. 80, No. 2 (1990), pp. 38-42.26 Gerali A., Neri S. & Sessa L. et al., “Credit and banking in a DSGE model of the Euro area,” Journal of Money, Credit and Banking, Vol. 42, No. 1 (2010), pp. 107-141.27 苏嘉胜、王曦: 《宏观审慎管理的有效性及其与货币政策的协调》,《财贸经济》2019年第9期,第65-83页。28 王曦、王茜、陈中飞: 《货币政策预期与通货膨胀管理——基于消息冲击的DSGE分析》,《经济研究》2016年第2期,第16-29页。29 杨小海、刘红忠、王弟海: 《中国应加速推进资本账户开放吗?——基于DSGE的政策模拟研究》,《经济研究》2017年第8期,第49-64页。30 李力、温来成、唐遥等: 《货币政策与宏观审慎政策双支柱调控下的地方政府债务风险治理》,《经济研究》2020年第11期,第36-49页。31 Iacoviello M. & Neri S., “Housing market spillovers: evidence from an estimated DSGE model,” American Economic Journal: Macroeconomics, Vol. 2, No. 2 (2010), pp. 125-164.32 Fernández-Villaverde J. & Uribe M., “Optimal fiscal and monetary policy in a medium-scale macroeconomic model,” NBER Macroeconomics Annual, Vol. 20 (2005), pp. 427-444.33 康立、龚六堂: 《金融摩擦、银行净资产与国际经济危机传导——基于多部门DSGE模型分析》,《经济研究》2014年第5期,第147-159页。34 Smets F. & Wouters R., “Shocks and frictions in US business cycles: a Bayesian DSGE approach,” American Economic Review, Vol. 3, No. 3 (2007), pp. 586-606.35 Rubio M. & Carrasco-Gallego A., “Macroprudential and monetary policies: implications for financial stability and welfare,” Journal of Banking & Finance, Vol. 49 (2014), pp. 326-336.36 罗娜、程方楠: 《房价波动的宏观审慎政策与货币政策协调效应分析——基于新凯恩斯主义的DSGE模型》,《国际金融研究》2017年第1期,第39-48页。37 岑磊、谷慎: 《宏观审慎政策效应及其与货币政策的配合》,《财政研究》2016年第4期,第26-38页。38 庄子罐、贾红静、刘鼎铭: 《货币政策的宏观经济效应研究:预期与未预期冲击视角》,《中国工业经济》2018年第7期,第80-97页。39 马理、范伟: 《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》2021年第3期,第5-23页。40 王曦、汪玲、彭玉磊等: 《中国货币政策规则的比较分析——基于DSGE模型的三规则视角》,《经济研究》2017年第9期,第24-38页。41 Iacoviello M., “Household debt and income inequality, 1963-2003,” Journal of Money, Credit and Banking, Vol. 40, No. 5 (2008), pp. 929-965.
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杨源源、贾鹏飞、高洁超: 《中国房地产长效调控范式选择:房产税政策还是宏观审慎政策》,《财贸经济》2021年第8期,第53-66页。2 Su C., Cai X. & Qin M. et al., “Can bank credit withstand falling house price in China?” International Review of Economics & Finance, Vol. 71, No. 3 (2021), pp. 257-267.3 刘晓星、石广平: 《杠杆对资产价格泡沫的非对称效应研究》,《金融研究》2018年第3期,第53-70页。4 唐建伟、夏丹: 《强化房地产金融宏观审慎监管》,《中国金融》2021年第2期,第90-91页。5 孟宪春、张屹山: 《家庭债务、房地产价格渠道与中国经济波动》,《经济研究》2021年第5期,第75-90页。6 Miao J., Wang P. & Zhou J., “Asset bubbles, collateral, and policy analysis,” Journal of Monetary Economics, Vol. 76 (2015), pp. 57-70.7 Barrell R., Davis E. & Karim D. et al., “Bank regulation, property prices and early warning systems for banking crises in OECD countries,” Journal of Banking & Finance, Vol. 34, No. 9 (2010), pp. 2255-2264.8 陈学胜: 《违约风险、房地产贷款市场博弈与房地产价格》,《统计研究》2019年第4期,第84-94页。9 Jorda O., Schularick M. & Taylor A., “Leveraged bubbles,” Journal of Monetary Economics, Vol. 76 (2015), pp. 1-20.10 方意: 《宏观审慎政策有效性研究》,《世界经济》2016年第8期,第25-49页。11 Angelini P., Neri S. & Panetta F., “The interaction between capital requirements and monetary policy,” Journal of Money, Credit and Banking, Vol. 46, No. 6 (2014), pp. 1073-1112.12 Mendicino C. & Punzi M., “House prices, capital inflows and macroprudential policy,” Journal of Banking & Finance, Vol. 49, No.7 (2014), pp. 337-355.13 贾鹏飞、范从来、褚剑: 《过度借贷的负外部性与最优宏观审慎政策设计》,《经济研究》2021年第3期,第32-47页。14 Selien S. & Frederic O., “Macroprudential policy and its impact on the credit cycle,” https://doi.org/10.1016/j.jfs.2020.100818, 2021-08-31.15 Franta M. & Gambacorta L., “On the effects of macroprudential policies on Growth-at-Risk,” https://doi.org/10.1016/j.econlet.2020.109501, 2021-08-31.16 周晔、陈亚杰: 《宏观审慎政策工具的有效性检验——基于对114家商业银行的实证分析》,《金融监管研究》2021年第1期,第49-65页。17 戴国强、肖立伟: 《欧盟房地产金融宏观审慎管理框架、经验与启示》,《上海金融》2019年第10期,第41-47页。18 朱红、臧晓伟: 《房地产金融宏观审慎管理:工具、效果及启示》,《新金融》2020年第1期,第59-64页。19 Vandenbussche J., Vogel U. & Detragiache E., “Macroprudential policies and housing prices: a new database and empirical evidence for central, eastern, and southeastern Europe,” Journal of Money, Credit and Banking, Vol. 47, No. S1 (2015), pp. 343-377.20 Kuttner K. & Shim I., “Taming the real estate beast: the effects of monetary and macroprudential policies on housing prices and credit,” https://www.rba.gov.au/publications/confs/2012/pdf/kuttner-shim-disc.pdf, 2021-08-31.21 Iacoviello M., “House prices, borrowing constraints, and monetary policy in the business cycle,” American Economic Review, Vol. 95, No. 3 (2005), pp. 739-764.22 孟宪春、张屹山、李天宇: 《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》2018年第6期,第81-97页。23 Cutler M., Poterba M. & Summers H., “Speculative dynamics and the role of feedback traders,” American Economic Review, Vol. 80, No. 2 (1990), pp. 63-68.24 He Y. & Xia F., “Heterogeneous traders, house prices and healthy urban housing market: a DSGE model based on behavioral economics,” https://doi.org/10.1016/j.habitatint.2019.102085, 2021-08-31.25 Abel A. B., “Asset prices under habit formation and catching up with the Joneses,” American Economic Review, Vol. 80, No. 2 (1990), pp. 38-42.26 Gerali A., Neri S. & Sessa L. et al., “Credit and banking in a DSGE model of the Euro area,” Journal of Money, Credit and Banking, Vol. 42, No. 1 (2010), pp. 107-141.27 苏嘉胜、王曦: 《宏观审慎管理的有效性及其与货币政策的协调》,《财贸经济》2019年第9期,第65-83页。28 王曦、王茜、陈中飞: 《货币政策预期与通货膨胀管理——基于消息冲击的DSGE分析》,《经济研究》2016年第2期,第16-29页。29 杨小海、刘红忠、王弟海: 《中国应加速推进资本账户开放吗?——基于DSGE的政策模拟研究》,《经济研究》2017年第8期,第49-64页。30 李力、温来成、唐遥等: 《货币政策与宏观审慎政策双支柱调控下的地方政府债务风险治理》,《经济研究》2020年第11期,第36-49页。31 Iacoviello M. & Neri S., “Housing market spillovers: evidence from an estimated DSGE model,” American Economic Journal: Macroeconomics, Vol. 2, No. 2 (2010), pp. 125-164.32 Fernández-Villaverde J. & Uribe M., “Optimal fiscal and monetary policy in a medium-scale macroeconomic model,” NBER Macroeconomics Annual, Vol. 20 (2005), pp. 427-444.33 康立、龚六堂: 《金融摩擦、银行净资产与国际经济危机传导——基于多部门DSGE模型分析》,《经济研究》2014年第5期,第147-159页。34 Smets F. & Wouters R., “Shocks and frictions in US business cycles: a Bayesian DSGE approach,” American Economic Review, Vol. 3, No. 3 (2007), pp. 586-606.35 Rubio M. & Carrasco-Gallego A., “Macroprudential and monetary policies: implications for financial stability and welfare,” Journal of Banking & Finance, Vol. 49 (2014), pp. 326-336.36 罗娜、程方楠: 《房价波动的宏观审慎政策与货币政策协调效应分析——基于新凯恩斯主义的DSGE模型》,《国际金融研究》2017年第1期,第39-48页。37 岑磊、谷慎: 《宏观审慎政策效应及其与货币政策的配合》,《财政研究》2016年第4期,第26-38页。38 庄子罐、贾红静、刘鼎铭: 《货币政策的宏观经济效应研究:预期与未预期冲击视角》,《中国工业经济》2018年第7期,第80-97页。39 马理、范伟: 《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》2021年第3期,第5-23页。40 王曦、汪玲、彭玉磊等: 《中国货币政策规则的比较分析——基于DSGE模型的三规则视角》,《经济研究》2017年第9期,第24-38页。41 Iacoviello M., “Household debt and income inequality, 1963-2003,” Journal of Money, Credit and Banking, Vol. 40, No. 5 (2008), pp. 929-965.