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金融研究  2021, Vol. 498 Issue (12): 38-56    
  绿色金融专辑 本期目录 | 过刊浏览 | 高级检索 |
环境灾害冲击对银行违约率的影响效应研究:理论与实证分析
王遥, 王文蔚
中央财经大学绿色金融国际研究院/财经研究院,北京 100081;
中央财经大学金融学院,北京 102206
The Impact of Environmental Disasters on the Bank Default Rate: Theoretical and Empirical Analysis
WANG Yao, WANG Wenwei
International Institute of Green Finance & Institute for Finance and Economics, Central University of Finance and Economics;
School of Finance, Central University of Finance and Economics
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摘要 本文通过模型模拟和基于中国数据的实证检验,分析了环境灾害损失冲击对于银行违约率的影响。本文模型模拟的结果显示,环境灾害冲击会显著提升银行体系的违约率水平,同时伴随着企业融资溢价水平的提升以及整个经济活动的萎缩;实证研究发现:环境灾害损失冲击会导致银行违约率水平显著提升。且与理论分析一致,本文实证发现宏观经济不确定性水平、企业的资本折损以及全要素生产率的下降在环境灾害影响银行违约率的过程中发挥了显著的传导作用。进一步研究发现,环境灾害冲击及其导致的银行违约率上升还会降低银行的风险偏好水平,降低放贷规模和主动风险承担,并反作用于实体企业,提升企业的融资约束和成本。本文的研究结论丰富了基于中国视角的环境物理风险研究,刻画了环境灾害损失对于银行风险的影响及其后续效应,为政策部门防范气候环境风险提供了借鉴。
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王遥
王文蔚
关键词:  环境灾害  物理风险  银行违约率  金融风险    
Summary:  China has experienced frequent environmental disasters with huge negative impacts on economic and social development. The real economy and financial sector are becoming more closely aligned, and the impact of environmental disasters on the real economy will inevitably be transmitted to the financial system and institutions, affecting financial stability, generating financial risks, and generally amplifying the negative impact of environmental disasters. From the perspective of physical risk, this paper discusses the actual impact of environmental disasters on banks' default risk through dynamic stochastic general equilibrium model simulations and empirical tests using data from China's banking institutions from 2008 to 2018.
This article's main contributions are as follows: First, it is one of the first theoretical and empirical studies on China's environmental risks. Second, in terms of research methods, this article simultaneously introduces disaster shock factors and the financial friction mechanism, highlighting the amplification effect of the financial accelerator mechanism on the impact of disaster shocks. Further, this article examines the impact of disaster shocks on relevant economic and financial indicators, including bank default rates. In terms of empirical research, this article uses the entropy method to construct environmental disaster loss indicators on multiple dimensions, providing empirical evidence from China of environmental risks. Third, the theoretical and empirical tests not only support the existence of environmental risks but also further analyze and explore a series of derivative consequences of environmental disasters on banks' default rates, including the impact on corporate financing constraints and banks' willingness to lend. This enriches the research perspectives on topics such as financing constraints and bank liquidity creation.
The simulation results of the theoretical model show that environmental disasters significantly increase the default rate of bank credit contracts. This leads to higher risk premiums and reduces the scale of credit issuance, undermining enterprises and increasing their financing costs. Eventually, the tightening of financing constraints significantly negatively affects investment and output, reducing enterprises' leverage. Consistent with these results, the empirical tests show that environmental disasters significantly increase banks' default rates, and these findings pass a series of robustness tests. The mechanism test shows that the decline in total factor productivity, asset impairment loss and the increase in macroeconomic uncertainty are all significant transmission channels in this process. Further analysis shows that the environmental disaster effect of increasing the default rate significantly reduces the risk appetite of banks, reducing the scale of lending and risk-taking. This then restricts enterprises through tighter financing constraints and higher financing premiums, negatively affecting their operations.
The main conclusions of this paper have the following policy implications: First, the systems and mechanisms to deal with environmental disasters should be improved and more attention given to the negative impacts of environmental disasters on the financial system. Next, awareness should be strengthened, and financial factors fully incorporated into the system. Second, government departments should consider the stability of the financial system when formulating disaster relief policies. Specifically, they should explore establishing disaster financial stability funds to prevent financial system runs and liquidity crises caused by extreme events. The supervision of financial institutions should include a standing disaster reserve, improving the construction of disaster recovery centers, adopting relevant incentives to guide financial institutions to reduce investment and credit for brown stranded assets, and encouraging financial institutions to engage in green finance. Third, the financial sector must fully consider climate and environmental risks and conduct environmental stress tests on a regular basis. Before launching a credit business, banks and other financial departments should thoroughly assess the climate and environmental risks of the business and region and fully consider environmental disaster risks in credit pricing. After a disaster occurs, the financial sector should also actively assist disaster-stricken enterprises through extensions and other benign interactions.
Keywords:  Environmental Disaster    Physical Risk    Bank Default Rate    Financial Risk
JEL分类号:  E32   G21   Q54  
基金资助: * 本文感谢国家社会科学基金重点项目(18AZD013)资助。感谢匿名审稿人的宝贵意见,文责自负。
通讯作者:  王文蔚,博士研究生,中央财经大学金融学院,E-mail:1062091215@qq.com.   
作者简介:  王遥,经济学博士,研究员,中央财经大学绿色金融国际研究院、财经研究院,E-mail:yaowang2013@163.com.
引用本文:    
王遥, 王文蔚. 环境灾害冲击对银行违约率的影响效应研究:理论与实证分析[J]. 金融研究, 2021, 498(12): 38-56.
WANG Yao, WANG Wenwei. The Impact of Environmental Disasters on the Bank Default Rate: Theoretical and Empirical Analysis. Journal of Financial Research, 2021, 498(12): 38-56.
链接本文:  
http://www.jryj.org.cn/CN/  或          http://www.jryj.org.cn/CN/Y2021/V498/I12/38
[1]卞志村和杨源源,2016,《结构性财政调控与新常态下财政工具选择》,《经济研究》第51期,第66~80页。
[2]陈国进、晁江锋、武晓利和赵向琴,2014,《罕见灾难风险和中国宏观经济波动》,《经济研究》第8期,第54~66页。
[3]陈雨露,2020,《当前全球中央银行研究的若干重点问题》,《金融研究》第2期,第1~14页。
[4]丁志帆和孔存玉,2021,《灾难风险冲击与结构性财政政策的收入分配效应研究》,《财贸经济》第1期,第1~15页。
[5]方意和陈敏,2019,《经济波动、银行风险承担与中国金融周期》,《世界经济》第2期,第3~25页。
[6]葛新宇、庄嘉莉和刘岩,2021,《贸易政策不确定性如何影响商业银行风险——对企业经营渠道的检验》,《中国工业经济》第8期,第133~151页。
[7]古志辉和张睿,2021,《台风灾害与股价崩盘风险》,《中国管理科学》第8期,第1~14页。
[8]顾海峰和于家珺,2019,《中国经济政策不确定性与银行风险承担》,《世界经济》第11期,第148~171页。
[9]李小荣和牛美龄,2020,《突发公共事件与金融关系研究进展》,《经济学动态》第7期,第129~144页。
[10]彭俞超、韩珣和李建军,2018,《经济政策不确定性与企业金融化》,《中国工业经济》第1期,第137~155页。
[11]苏冬蔚和连莉莉,2018,《绿色信贷是否影响重污染企业的投融资行为?》,《金融研究》第12期,第123~137页。
[12]陶静和胡雪萍,2019,《环境规制对中国经济增长质量的影响研究》,《中国人口·资源与环境》第6期,第85~96页。
[13]王国静和田国强,2014,《金融冲击和中国经济波动》,《经济研究》第3期,第20~34页。
[14]闫绪娴、范玲和樊媛媛,2019, 《中国省域生态—灾害—社会系统耦合协调时空分布及演化》,《宏观经济研究》第8期,第115~127页。
[15]余杰和黄孝武,2020,《中国宏观经济不确定性的经济效应》,《中央财经大学学报》第12期,第78~94页。
[16]张琳、廉永辉和辛兵海,2015,《宏观经济不确定性、银行异质性和信贷供给》,《当代经济科学》第4期,第60~71+126页。
[17]张晓晶、刘学良和王佳,2019,《债务高企、风险集聚与体制变革——对发展型政府的反思与超越》,《经济研究》第6期,第4~21页。
[18]赵向琴、袁靖和陈国进,2017,《灾难冲击与我国最优财政货币政策选择》,《经济研究》第4期,第34~47页。
[19]中国人民银行, 2021,《中国金融稳定报告2020》,中国金融出版社。
[20]朱军,2015,《中国宏观DSGE模型中的税收模式选择及其实证研究》,《数量经济技术经济研究》第1期,第67~81页。
[21]Baker, S., and N.Bloom.2011.“Does Uncertainty Drive Business Cycles? Using Disasters as Natural Experiments”, NBER Working Paper, No.19475.
[22]Bansal, R., M.Croce, and W.Kiao.2019.“Uncertainty-induced Reallocations and Growth”, NBER Working Paper, No.26248.
[23]Barro, R.J.2006.“Rare Disasters and Asset Markets in the Twentieth Century”, Quarterly Journal of Economics, 121(3):823~866.
[24]Bernanke, B.S., M.Gertler, and S.Gilchrist.1999.“The Financial Accelerator in a Quantitative Business Cycle Framework”, Handbook of Macroeconomics, 1(21):1341~1393.
[25]Bolton, P., M.Despres, L.A.Silva, F.Samama, and R.Svartzman.2020.The Green Swan: Central Banking and Financial Stability in the Age of Climate Change, Published by Bank for International Settlements.
[26]Christiano, L.J., R.Motto, and M.Rostagno.2014.“Risk Shocks”, American Economic Review, 104(1):27~65.
[27]Dell, M., B.F.Jones, and B.A.Olken.2014.“ What Do We Learn from the Weather? The New Climate Economy Literature”, Journal of Economic Literature, 52(3): 740~798.
[28]Fernandez, V.J.2010.“Fiscal Policy in a Model with Financial Frictions”, American Economic Review, 100(5): 35~40.
[29]Gabaix, X.2008.“Variable Rare Disasters: A Tractable Theory of Ten Puzzles in Macro-finance”, American Economic Review, 98(2):64~67.
[30]Gallic, E., and G.Vermandel.2020.“Weather Shocks”, European Economic Review,124(3): 973~990.
[31]Gourio, F.2012.“Disaster Risk and Business Cycles”, American Economic Review, 102(6): 2734~2766.
[32]Gourio, F., M.Siemer, and A.Verdelhan.2013.“International Risk Cycles”, Journal of International Economics, 89(2): 471~484.
[33]Huang, B., M.T.Punzi, and Y.Wu.2021.“Do Banks Price Environmental Transition Risks? Evidence From a Quasi-natural Experiment in China”, Journal of Corporate Finance, 69, 101983.
[34]Keen, B.D., and M.R.Pakko.2011.“Monetary Policy and Natural Disasters in a DSGE Model”, Southern Economic Journal, 77(4): 973~990.
[35]Klomp, J.2014.“Financial Fragility and Natural Disasters: An Empirical Analysis”, Journal of Financial Stability, 13: 180~192.
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