E. dehaan, James R. Moon, Jonathan E. Shipman, Quinn T. Swanquist, Robert L. Whited
{"title":"Control Variables in Interactive Models","authors":"E. dehaan, James R. Moon, Jonathan E. Shipman, Quinn T. Swanquist, Robert L. Whited","doi":"10.2308/jfr-2021-023","DOIUrl":null,"url":null,"abstract":"\n Accounting studies often examine whether the relation between X and Y varies with a moderating variable, M, by including an interactive term, X × M, in a regression. We provide plain-English guidance on why, how, and when to use control variables, Z, in interaction tests. A simulation and simple descriptions demonstrate how interacted controls affect coefficient estimates and interpretations. In particular, we demonstrate how controlling for Z without an accompanying interaction of X × Z and/or M × Z generally does not eliminate the confounding effect of Z on X × M. We conclude with guidance for future research.\n Data Availability: Stata code to produce the simulations in this paper is available, as linked in the text.\n JEL Classifications: M40; M41; C01; C18.","PeriodicalId":42044,"journal":{"name":"Journal of Financial Reporting","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Financial Reporting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2308/jfr-2021-023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 1
Abstract
Accounting studies often examine whether the relation between X and Y varies with a moderating variable, M, by including an interactive term, X × M, in a regression. We provide plain-English guidance on why, how, and when to use control variables, Z, in interaction tests. A simulation and simple descriptions demonstrate how interacted controls affect coefficient estimates and interpretations. In particular, we demonstrate how controlling for Z without an accompanying interaction of X × Z and/or M × Z generally does not eliminate the confounding effect of Z on X × M. We conclude with guidance for future research.
Data Availability: Stata code to produce the simulations in this paper is available, as linked in the text.
JEL Classifications: M40; M41; C01; C18.