Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/33318 
Kompletter Metadatensatz
DublinCore-FeldWertSprache
dc.contributor.authorRegan, Tracy L.en
dc.contributor.authorOaxaca, Ronald L.en
dc.date.accessioned2006-05-23-
dc.date.accessioned2010-07-07T09:10:14Z-
dc.date.available2010-07-07T09:10:14Z-
dc.date.issued2006-
dc.identifier.urihttp://hdl.handle.net/10419/33318-
dc.description.abstractWe address the bias from using potential vs. actual experience in earnings models. Statistical tests reject the classical errors-in-variable framework. The nature of the measurement error is best viewed as a model misspecification problem. We correct for this by modeling actual experience as a stochastic regressor and predicting experience using the NLSY79 and the PSID. Predicted experience measures are applied to the IPUMS. Our results suggest that potential experience biases the effects of schooling and the rates of return to labor market experience. Using such a measure in earnings models underestimates the explained portion of the male-female wage gap.en
dc.language.isoengen
dc.publisher|aInstitute for the Study of Labor (IZA) |cBonnen
dc.relation.ispartofseries|aIZA Discussion Papers |x1920en
dc.subject.jelC81en
dc.subject.jelJ24en
dc.subject.jelJ31en
dc.subject.ddc330en
dc.subject.keywordexperienceen
dc.subject.keywordspecification erroren
dc.subject.keyworddecompositionen
dc.subject.keywordgenderen
dc.subject.stwLohndifferenzierungen
dc.subject.stwGeschlechten
dc.subject.stwDekompositionsverfahrenen
dc.subject.stwModell-Spezifikationen
dc.subject.stwBerufserfahrungen
dc.subject.stwSchätzungen
dc.subject.stwUSAen
dc.titleWork experience as a source of specification error in earnings models: implications for gender wage decompositions-
dc.type|aWorking Paperen
dc.identifier.ppn506211657en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

Datei(en):
Datei
Größe
331.88 kB





Publikationen in EconStor sind urheberrechtlich geschützt.