Predicting Fixed Effects in Panel Probit Models

Monash Business School, No 10/19

34 Pages Posted: 12 Dec 2019

See all articles by Johannes Kunz

Johannes Kunz

Monash University - Centre for Health Economics; University of Zurich - Department of Economics

Kevin E. Staub

University of Melbourne - Department of Economics; IZA Institute of Labor Economics

Rainer Winkelmann

University of Zurich - Department of Economics

Date Written: October 29, 2019

Abstract

Many applied settings in empirical economics require estimation of a large number of fixed effects, like teacher effects or location effects. In the context of binary response variables, previous studies have been limited to the linear probability model, citing perfect prediction and incidental parameter biases as reasons. We explain why these problems arise and present an appropriate solution for the probit model. In contrast to other estimators, it ensures that predicted fixed effects exist for all units. We illustrate the approach in simulation experiments and an application to health care utilization.

Keywords: Perfect Prediction, Incidental Parameter Bias, Fixed Effects, Panel Data, Binary Response

Suggested Citation

Kunz, Johannes S and Staub, Kevin E. and Winkelmann, Rainer, Predicting Fixed Effects in Panel Probit Models (October 29, 2019). Monash Business School, No 10/19, Available at SSRN: https://ssrn.com/abstract=3477025 or http://dx.doi.org/10.2139/ssrn.3477025

Johannes S Kunz (Contact Author)

Monash University - Centre for Health Economics ( email )

Building 75, 15 Innovation Walk
Monash University
Clayton, Victoria 3800
Australia

University of Zurich - Department of Economics ( email )

Zürich
Switzerland

Kevin E. Staub

University of Melbourne - Department of Economics ( email )

Melbourne, Victoria 3010
Australia

IZA Institute of Labor Economics ( email )

P.O. Box 7240
Bonn, D-53072
Germany

Rainer Winkelmann

University of Zurich - Department of Economics ( email )

Zürich
Switzerland

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