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| Type | Working Paper |
| Scope | Discipline-based scholarship |
| Title | Predicting fixed effects in panel probit models |
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| Institution | University of York, Department of Economics and Related Studies |
| Series Name | HEDG Working Paper series |
| Number | 18/23 |
| ISSN | 1751-1976 |
| Number of Pages | 31 |
| Date | 2018 |
| Abstract Text | We present a method to estimate and predict fixed effects in a panel probit model when N is large and T is small, and when there is a high proportion of individual units without variation in the binary response. Our approach builds on a bias-reduction method originally developed by Kosmidis and Firth (2009) for cross-section data. In contrast to other estimators, our approach ensures that predicted fixed effects are finite in all cases. Results from a simulation study document favorable properties in terms of bias and mean squared error. The estimator is applied to predict period-specific fixed effects for the extensive margin of health care utilization (any visit to a doctor during the previous three months), using German data for 2000-2014. We find a negative correlation between fixed effects and observed characteristics. Although there is some within-individual variation in fixed effects over sub-periods, the between-variation is four times as large. |
| Official URL | https://www.york.ac.uk/economics/hedg/wps/wp2018/ |
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| Keywords | Perfect prediction, bias reduction, modified score function |
| Additional Information | Auch publiziert als Monash University Discussion Paper 10/19 |