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.
|Date of creation:||Nov 2000|
|Date of revision:|
|Publication status:||published in: Journal of Business and Economic Statistics, 2004, 22 (3), 312-321|
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