Parametric and Semiparametric Estimation in Models with Misclassified Categorical Dependent Variables
AbstractWe 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 some substantial differences in parameter estimates between parametric and semiparametric models, and between predictions of true and reported fluency. We compare the predictions of the three models, and perform a graphical test of the parametric models against semiparametric alternatives.
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Bibliographic InfoPaper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 1999-51.
Date of creation: 1999
Date of revision:
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immigrants; speaking fluency; measurement error;
Other versions of this item:
- Dustmann, Christian & van Soest, Arthur, 2000. "Parametric and Semiparametric Estimation in Models with Misclassified Categorical Dependent Variables," IZA Discussion Papers 218, Institute for the Study of Labor (IZA).
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, and Immigrants; Non-labor Discrimination
This paper has been announced in the following NEP Reports:
- NEP-ALL-1999-07-28 (All new papers)
- NEP-DCM-1999-09-02 (Discrete Choice Models)
- NEP-ECM-1999-07-28 (Econometrics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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