Tauchmann H (2019)
Publication Language: English
Publication Type: Other publication type
Publication year: 2019
Series: FAU Discussion Papers in Economics
Journal Issue: 09/2019
This paper shows that popular linear fixed-effects panel-data estimators (first-differences, within-transformation) are biased and inconsistent when applied in a discrete-time hazard setting, that is, one with the outcome variable being a binary dummy indicating an absorbing state, even if the data generating process is fully consistent with the linear discrete-time hazard model. Besides conventional survival bias, these estimators suffer from another source of – potentially severe – bias that originates from the data transformation itself and is present even in the absence of any unobserved heterogeneity. We suggest an alternative, computationally very simple, adjusted first-differences estimator that cures the data-transformation driven bias of the classical estimators. The theoretical line of argument is supported by evidence from Monte Carlo simulations and is illustrated by an empirical application.
APA:
Tauchmann, H. (2019). Fixed-Effects estimation of the Linear Discrete-Time Hazard Model: an Adjusted First-Differences Estimator.
MLA:
Tauchmann, Harald. Fixed-Effects estimation of the Linear Discrete-Time Hazard Model: an Adjusted First-Differences Estimator. 2019.
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