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Predicting fixed effects in panel probit models

Johannes Kunz (), Kevin Staub () and Rainer Winkelmann ()

No 10-19, Monash Economics Working Papers from Monash University, Department of Economics

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, pre-vious 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 pre- dicted 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; Bias reduction (search for similar items in EconPapers)
Pages: 34 pages
Date: 2019-06
New Economics Papers: this item is included in nep-dcm
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Working Paper: Predicting fixed effects in panel probit models (2018) Downloads
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