Resource title

Parametric and Semiparametric Estimation in Models with Misclassified Categorical Dependent Variables

Resource image

image for OpenScout resource :: Parametric and Semiparametric Estimation in Models with Misclassified Categorical Dependent Variables

Resource description

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.

Resource author

Christian Dustmann, Arthur van Soest

Resource publisher

Resource publish date

Resource language

eng

Resource content type

text/html

Resource resource URL

http://hdl.handle.net/10419/21064

Resource license

Adapt according to the presented license agreement and reference the original author.