Omitted Variables and Misspecified Disturbances in the Logit Model
AbstractIn binary discrete regression models like logit or probit the omis-sion of a relevant regressor (even if it is orthogonal) depresses the re-maining b coefficients towards zero. For the probit model, Wooldridge(2002) has shown that this bias does not carry over to the effect ofthe regressor on the outcome. We find by simulations that this alsoholds for logit models, even when the omitted variable leads to severemisspecification of the disturbance. More simulations show that es-timates of these effects by logit analysis are also impervious to puremisspecification of the disturbance.
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Bibliographic InfoPaper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 05-084/4.
Date of creation: 15 Sep 2005
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logit model; omitted variables; misspecification;
Find related papers by JEL classification:
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-09-29 (All new papers)
- NEP-DCM-2005-09-29 (Discrete Choice Models)
- NEP-ECM-2005-09-29 (Econometrics)
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