Predicting Individual Effects in Fixed Effects Panel Probit Models

Johannes Kunz, Kevin Staub and Rainer Winkelmann

No 2021-05, SoDa Laboratories Working Paper Series from Monash University, SoDa Laboratories

Abstract: Many applied settings in empirical economics require estimation of a large number of individual effects, like teacher effects or location effects; in health economics, prominent examples include patient effects, doctor effects, or hospital effects. Increasingly, these effects are the object of interest of the estimation, and predicted effects are often used for further descriptive and regression analyses. To avoid imposing distributional assumptions on these effects, they are typically estimated via fixed effects methods. In short panels, the conventional maximum likelihood estimator for fixed effects binary response models provides poor estimates of these individual effects since the finite sample bias is typically substantial. We present a bias-reduced fixed effects estimator that provides better estimates of the individual effects in these models by removing the first-order asymptotic bias. An additional, practical advantage of the estimator is that it provides finite predictions for all individual effects in the sample, including those for which the corresponding dependent variable has identical outcomes in all time periods over time (either all zeros or ones); for these, the maximum likelihood prediction is infinite. We illustrate the approach in simulation experiments and in an application to health care utilization. Stata estimation command is available at [Github:brfeglm](https://github.com/JohannesSKunz/brfeglm)

Keywords: Incidental parameter bias; Perfect prediction; Fixed effects; Panel data; Bias reduction (search for similar items in EconPapers)
JEL-codes: C23 C25 I11 I18 (search for similar items in EconPapers)
Date: 2021-05
New Economics Papers: this item is included in nep-dcm, nep-ecm and nep-hea
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Citations: View citations in EconPapers (7)

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Journal Article: Predicting individual effects in fixed effects panel probit models (2021)
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