宏观审慎评估体系(MPA)是我国在“双支柱”框架下的重要探索和创新,旨在规范商业银行的经营行为,降低其风险承担。MPA于2016年首次提出,于2017年升级。本文利用2009—2018年中国47家商业银行的资产负债表数据,推算银行广义信贷规模,通过设计双重差分模型,探究MPA对银行广义信贷和信用风险的影响。研究结果表明:第一,MPA的实施显著抑制银行广义信贷的过快扩张,并且显著降低银行信用风险。第二,MPA对银行广义信贷的影响存在结构差异。面临考核压力的银行倾向于先压缩非狭义类型信贷规模,但对狭义信贷和表外理财的抑制作用并不显著,这将推动银行资产配置结构的转变。第三,以上结论在基于资本充足率的分组与基于广义信贷增速的分组中保持一致,表明实施MPA的政策效果是稳健的。
Abstract
As an essential exploration and innovation under the two-pillar framework, the macroprudential assessment system (MPA) aims to supervise the business behavior of commercial banks and reduce their risk-taking. MPA was first proposed in 2016 and further upgraded in 2017. However, its policy effect evaluation has yet to be involved in the current research.
This paper focuses on two profound changes in MPA, using the balance sheet data of 47 commercial banks in China from 2009 to 2018. Firstly, this paper calculates the broad credit scale of banks. Secondly, this paper groups banks according to the regulatory pressure faced by banks and empirically explores the impact of MPA on banks' broad credit and credit risk by designing a difference in difference (DID) model.
The results show that: firstly, the implementation of MPA significantly inhibits the banks' broad credit expansion and significantly reduces the banks' credit risk-taking behaviors. Secondly, there are structural differences in the impact of MPA on banks' broad credit. Banks tend to reduce the scale of non-narrow credit first. However, the inhibitory effect on the growth of narrow loans and off-balance sheet financing is insignificant, promoting the transformation of banks' asset allocation structure. Thirdly, the grouping results based on the capital adequacy ratio are consistent with those based on broad credit growth, and the policy effect is stable.
关键词
宏观审慎评估体系 /
双重差分模型 /
银行广义信贷 /
信用风险
{{custom_keyword}} /
Key words
MPA /
DID Model /
Bank Broad Credit /
Credit Risk
{{custom_keyword}} /
中图分类号:
F830
{{custom_clc.code}}
({{custom_clc.text}})
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 方意. 宏观审慎政策有效性研究[J]. 世界经济,2016(8):25-49
[2] 郭品,沈悦. 互联网金融、存款竞争与银行风险承担[J]. 金融研究,2019(8):58-76
[3] 兰晓梅,杨胜刚,杨申燕. 货币政策与宏观审慎政策协调对影子银行的影响[J]. 国际金融研究,2020(9):23-33
[4] 李文泓,林凯旋. 关于用广义信贷/GDP分析我国银行业系统性风险的研究[J]. 金融监管研究,2013(6):13-30
[5] 马勇. “双支柱”调控框架的理论与经验基础[J]. 金融研究,2019(12):18-37
[6] 彭俞超,何山. 资管新规、影子银行与经济高质量发展[J]. 世界经济,2020,43(1):47-69
[7] 宋科,李振,赵宣凯. 宏观审慎政策、经济周期与银行风险承担[J]. 经济理论与经济管理,2019(1):43-58
[8] 苏帆,于寄语,熊劼. 更高资本充足率要求能够有效防范金融风险吗?——基于双重差分法的再检验[J]. 国际金融研究,2019(9):76-86
[9] 许坤,苏扬. 逆周期资本监管、监管压力与银行信贷研究[J]. 统计研究,2016,33(3):97-105
[10] 于博,吴菡虹. 银行业竞争、同业杠杆率攀升与商业银行信用风险[J]. 财经研究,2020,46(2):36-51
[11] 中国人民银行总行调查统计司课题组. 广义信贷研究[J]. 上海金融,2019(4):1-16
[12] 朱太辉,黄海晶. 中国金融周期:指标、方法和实证[J]. 金融研究,2018(12):55-71
[13] Bruno V,Shim I,Shin H S.Comparative Assessment of Macroprudential Policies[J]. Journal of Financial Stability,2017,28:183-202
[14] Cerutti E,Claessens S,Laeven L.The Use and Effectiveness of Macroprudential Policies:New Evidence[J]. Journal of Financial Stability,2017,28,203-224
[15] Cerutti E,Dagher J,Dell'Ariccia G. Housing Finance and Real-Estate Booms:A Cross-Country Perspective[J]. Journal of Housing Economics,2017,38:1-13
[16] Cizel J,Frost J,Houben A,Wierts P.Effective Macroprudential Policy:Cross-Sector Substitution from Price and Quantity Measures[J]. Journal of Money,Credit and Banking,2019,51(5):1209-1235
[17] Claessens S,Ghosh S R,Mihet R.Macro-Prudential Policies to Mitigate Financial System Vulnerabilities[J]. Journal of International Money and Finance,2013,39:153-185
[18] Cozzi G,Darracq Paries M,Karadi P,Körner J,Kok C,Mazelis F,Nikolov K,Rancoita E,Van Der Ghote A,Weber J. Macroprudential Policy Measures:Macroeconomic Impact and Interaction with Monetary Policy[R]. ECB Working Paper,2020
[19] De Nicolò G,Dell'Ariccia G,Laeven L,Valencia F. Monetary Policy and Bank Risk Taking[R]. IMF Working Paper,2010
[20] Dell'Ariccia G,Igan D,Laeven L,Tong H,Bakker B,Vandenbussche J. Policies for Macrofinancial Stability:How to Deal with Credit Booms[R]. IMF Staff Discussion Note,2012
[21] Dinger V,Von Hagen J.Does Interbank Borrowing Reduce Bank Risk?[J]. Journal of Money,Credit and Banking,2009,41(2-3):491-506
[22] Liao S,Sojli E,Tham W.Managing Systemic Risk in the Netherlands[J]. International Review of Economics and Finance,2015,40,231-245
[23] Lim C H,Costa A,Columba F,Kongsamut P,Otani A,Saiyid M,Wezel T,Wu X.Macroprudential Policy:What Instruments and How to Use Them?Lessons from Country Experiences[R]. IMF Working Paper,2011
[24] Meuleman E,Vander Vennet R.Macroprudential Policy and Bank Systemic Risk[J]. Journal of Financial Stability,2020,47:100724
[25] Vandenbussche J,Vogel U,Detragiache E.Macroprudential Policies and Housing Prices:A New Database and Empirical Evidence for Central,Eastern and Southeastern Europe[J]. Journal of Money,Credit and Banking,2015,47(S1):343-377
{{custom_fnGroup.title_cn}}
脚注
{{custom_fn.content}}
基金
*本文获国家自然科学基金项目“金融文本大数据与银行业系统性风险:指标构建、应用与评估整合”(72173144)、国家自然科学基金项目“金融周期视角下的中国银行业系统性风险防范与化解研究”(71973162)资助
{{custom_fund}}