Parametric and Semiparametric Estimation in Models with Misclassified Categorical Dependent Variables

We consider both a parametric and a semiparametric method to account for classification errors on the dependent variable in an ordered response model. The methods are applied to the analysis of self-reported speaking fluency of male immigrants in Germany. We find that a parametric model which explicitly allows for misclassification performs better than a standard ordered probit model and than a model with random thresholds. We find some substantial differences in parameter estimates and predictions of the different models

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Year of publication:	[2021]
Authors:	Dustmann, Christian ; Soest, Arthur van
Publisher:	[S.l.] : SSRN
Subject:	Schätztheorie \| Estimation theory \| Qualitative Methode \| Qualitative method \| Deutschland \| Germany \| Statistischer Fehler \| Statistical error \| Migranten \| Migrants \| Sprache \| Language

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