Stephen G. Hall, George S. Tavlas, Lorenzo Trapani, Yongli Wang
{"title":"On the Detection of Structural Breaks: The Case of the Covid Shock","authors":"Stephen G. Hall, George S. Tavlas, Lorenzo Trapani, Yongli Wang","doi":"10.1002/for.3238","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Both the Federal Reserve (Fed) and the European Central Bank (ECB) have been criticized for not having perceived that the outbreak of Covid at the beginning of 2020 would lead to a structural change in inflation in the early 2020s. Both central banks viewed the initial inflation surge in 2021 as temporary and delayed monetary tightening until 2022. We argue that the existing literature on structural breaks could not have been useful to policymakers because it identifies the breaks in an arbitrary way. The tests used to identify breaks do not incorporate prior knowledge that a break may have occurred so that the tests have very little power to detect a break that occurs at the end of the sample. We show that, in the event of a major shock, such as Covid, using knowledge that a break may have occurred and testing for a break in a recursive way as new data become available could have alerted policymakers to the break in inflation. We conduct Monte Carlo simulations suggesting that our method would have identified that a break had occurred in inflation by the end of 2020, well before policymakers had perceived the break.</p>\n </div>","PeriodicalId":47835,"journal":{"name":"Journal of Forecasting","volume":"44 3","pages":"1042-1070"},"PeriodicalIF":3.4000,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Forecasting","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/for.3238","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
On the Detection of Structural Breaks: The Case of the Covid Shock
Both the Federal Reserve (Fed) and the European Central Bank (ECB) have been criticized for not having perceived that the outbreak of Covid at the beginning of 2020 would lead to a structural change in inflation in the early 2020s. Both central banks viewed the initial inflation surge in 2021 as temporary and delayed monetary tightening until 2022. We argue that the existing literature on structural breaks could not have been useful to policymakers because it identifies the breaks in an arbitrary way. The tests used to identify breaks do not incorporate prior knowledge that a break may have occurred so that the tests have very little power to detect a break that occurs at the end of the sample. We show that, in the event of a major shock, such as Covid, using knowledge that a break may have occurred and testing for a break in a recursive way as new data become available could have alerted policymakers to the break in inflation. We conduct Monte Carlo simulations suggesting that our method would have identified that a break had occurred in inflation by the end of 2020, well before policymakers had perceived the break.
期刊介绍:
The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.