Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/238191 
Year of Publication: 
2021
Series/Report no.: 
FAU Discussion Papers in Economics No. 03/2021
Version Description: 
May 2021
Publisher: 
Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute for Economics, Nürnberg
Abstract: 
This paper demonstrates that popular linear fixed-effects panel-data estimators are biased and inconsistent when applied in a discrete-time hazard setting - that is, one in which the outcome variable is a binary dummy indicating an absorbing state, even if the data-generating process is fully consistent with the linear discrete-time hazard model. In addition to conventional survival bias, these estimators suffer from another source of - frequently severe - bias that originates from the data transformation itself and, unlike survival bias, is present even in the absence of any unobserved heterogeneity. We suggest an alternative estimation strategy, which is instrumental variables estimation using first-differences of the exogenous variables as instruments for their levels. Monte Carlo simulations and an empirical application substantiate our theoretical results.
Subjects: 
linear probability model
individual fixed effects
discrete-time hazard
absorbing state
survival bias
instrumental variables estimation
JEL: 
C23
C25
C41
Document Type: 
Working Paper

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