Estimation in Binary Choice Models with Measurement Errors

Arbeitspapier

In this paper we develop a simple maximum likelihood estimator for probit models where the regressors have measurement error. We first assume precise information about the reliability ratios (or, equivalently, the proxy correlations) of the regressors. We then show how reasonable bounds for the parameter estimates can be obtained when only imprecise information is available. The analysis is also extended to situations where the measurement error has non-zero mean and is correlated with the true values of the regressors. An extensive simulation study shows that the estimator works very well, even in quite small samples. Finally the method is applied to data explaining sick leave in Sweden.

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• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Working Paper ; No. 2003:4

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities ; Single Equation Models; Single Variables: Other
• Subject: Measurement error ; errors-in-variables ; probit ; binary choice ; bounds

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Edgerton, David ; Jochumzen, Peter
• Event: Veröffentlichung
• (who): Lund University, School of Economics and Management, Department of Economics
• (where): Lund
• (when): 2003

Further information

• Handle: http://hdl.handle.net/10419/259870