Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/238191 
Erscheinungsjahr: 
2021
Schriftenreihe/Nr.: 
FAU Discussion Papers in Economics No. 03/2021
Versionsangabe: 
May 2021
Verlag: 
Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute for Economics, Nürnberg
Zusammenfassung: 
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.
Schlagwörter: 
linear probability model
individual fixed effects
discrete-time hazard
absorbing state
survival bias
instrumental variables estimation
JEL: 
C23
C25
C41
Dokumentart: 
Working Paper

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