Juan Carlos Parra-Alvarez, Olaf Posch, Andreas Schrimpf
{"title":"Peso problems in the estimation of the C‐CAPM","authors":"Juan Carlos Parra-Alvarez, Olaf Posch, Andreas Schrimpf","doi":"10.3982/qe1478","DOIUrl":null,"url":null,"abstract":"This paper shows that the consumption‐based capital asset pricing model (C‐CAPM) with low‐probability disaster risk rationalizes pricing errors. We find that implausible estimates of risk aversion and time preference are not puzzling if market participants expect a future catastrophic change in fundamentals, which just happens not to occur in the sample (a “peso problem”). A bias in structural parameter estimates emerges as a result of pricing errors in quiet times. While the bias essentially removes the pricing error in the simple models when risk‐free rates are constant, time‐variation may also generate large and persistent estimated pricing errors in simulated data. We also show analytically how the problem of biased estimates can be avoided in empirical research by resolving the misspecification in moment conditions.","PeriodicalId":46811,"journal":{"name":"Quantitative Economics","volume":"1 1","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantitative Economics","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.3982/qe1478","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 1
Abstract
This paper shows that the consumption‐based capital asset pricing model (C‐CAPM) with low‐probability disaster risk rationalizes pricing errors. We find that implausible estimates of risk aversion and time preference are not puzzling if market participants expect a future catastrophic change in fundamentals, which just happens not to occur in the sample (a “peso problem”). A bias in structural parameter estimates emerges as a result of pricing errors in quiet times. While the bias essentially removes the pricing error in the simple models when risk‐free rates are constant, time‐variation may also generate large and persistent estimated pricing errors in simulated data. We also show analytically how the problem of biased estimates can be avoided in empirical research by resolving the misspecification in moment conditions.