Viral V. Acharya, Richard Berner, Robert Engle, Hyeyoon Jung, Johannes Stroebel, Xuran Zeng, Yihao Zhao
{"title":"Climate Stress Testing","authors":"Viral V. Acharya, Richard Berner, Robert Engle, Hyeyoon Jung, Johannes Stroebel, Xuran Zeng, Yihao Zhao","doi":"10.1146/annurev-financial-110921-101555","DOIUrl":null,"url":null,"abstract":"We explore the design of climate stress tests to assess and manage macroprudential risks from climate change in the financial sector. We review the climate stress scenarios currently employed by regulators, highlighting the need to ( a) consider many transition risks as dynamic policy choices, ( b) better understand and incorporate feedback loops between climate change and the economy, and ( c) further explore compound risk scenarios in which climate risks co-occur with other risks. We discuss how the process of mapping climate stress scenarios into financial firm outcomes can incorporate existing evidence on the effects of various climate-related risks on credit and market outcomes. We argue that more research is required to ( a) identify channels through which plausible scenarios can lead to meaningful short-run impact on credit risks given typical bank loan maturities, ( b) incorporate bank-lending responses to climate risks, ( c) assess the adequacy of climate risk pricing in financial markets, and ( d) better understand how market participants form climate risk expectations and how that affects financial stability. Finally, we discuss the advantages and disadvantages of using market-based climate stress tests that can be conducted with publicly available data to complement existing stress-testing frameworks. Expected final online publication date for the Annual Review of Financial Economics, Volume 15 is November 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.","PeriodicalId":47162,"journal":{"name":"Annual Review of Financial Economics","volume":null,"pages":null},"PeriodicalIF":5.0000,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review of Financial Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1146/annurev-financial-110921-101555","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
We explore the design of climate stress tests to assess and manage macroprudential risks from climate change in the financial sector. We review the climate stress scenarios currently employed by regulators, highlighting the need to ( a) consider many transition risks as dynamic policy choices, ( b) better understand and incorporate feedback loops between climate change and the economy, and ( c) further explore compound risk scenarios in which climate risks co-occur with other risks. We discuss how the process of mapping climate stress scenarios into financial firm outcomes can incorporate existing evidence on the effects of various climate-related risks on credit and market outcomes. We argue that more research is required to ( a) identify channels through which plausible scenarios can lead to meaningful short-run impact on credit risks given typical bank loan maturities, ( b) incorporate bank-lending responses to climate risks, ( c) assess the adequacy of climate risk pricing in financial markets, and ( d) better understand how market participants form climate risk expectations and how that affects financial stability. Finally, we discuss the advantages and disadvantages of using market-based climate stress tests that can be conducted with publicly available data to complement existing stress-testing frameworks. Expected final online publication date for the Annual Review of Financial Economics, Volume 15 is November 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.