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Identification with Models and Exogenous Data Variation

dc.contributor.authorKahn, R. Jay
dc.contributor.authorWhited, Toni M.
dc.date.accessioned2016-07-14T12:31:31Z
dc.date.available2016-07-14T12:31:31Z
dc.date.issued2016-07
dc.identifier1323en_US
dc.identifier.citationForthcoming, Foundations and Trends in Accountingen_US
dc.identifier.urihttps://hdl.handle.net/2027.42/122724
dc.description.abstractWe distinguish between identification and establishing causality. Identification means forming a unique mapping from features of data to quantities that are of interest to economists. Establishing causality is synonymous with finding sources of exogenous variation. These two issues are often confused. However, exogenous variation is only sometimes necessary and never sufficient to identify economically interesting parameters. Instead, even for causal questions identification must rest on an underlying economic model. We illustrate these points by examining identification in two recent papers: one causal study relying on an entirely verbal model and one non-causal study relying on a formal mathematical model.en_US
dc.subjectIdentificationen_US
dc.subjectCausalityen_US
dc.subjectNatural Experimentsen_US
dc.subjectStructural Estimationen_US
dc.subject.classificationFinanceen_US
dc.titleIdentification with Models and Exogenous Data Variationen_US
dc.typeWorking Paperen_US
dc.subject.hlbsecondlevelFinanceen_US
dc.subject.hlbtoplevelBusiness
dc.contributor.affiliationumRoss School of Businessen_US
dc.contributor.affiliationumcampusAnn Arbor
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/122724/1/1323_Whited.pdf
dc.owningcollnameBusiness, Stephen M. Ross School of - Working Papers Series


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