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Split-Panel Jackknife Estimation of Fixed-Effect Models



Type:   Working paper
Titre:   Split-Panel Jackknife Estimation of Fixed-Effect Models
Auteur(s):   Dhaene, Geert - KU Leuven (Auteur)
Jochmans, Koen (1982-...) - Département d'économie (Auteur)
Date de publication:   2014-03
Collection:   Sciences Po Economics Discussion Papers  :  2014-03
Mots-clés:   [fr] bias reduction, dependent data, incidental-parameter problem, jackknife, nonlinear model
Résumé:   [en] Maximum-likelihood estimation of nonlinear models with fixed effects is subject to the incidental-parameter problem. This typically implies that point estimates suffer from large bias and confidence intervals have poor coverage. This paper presents a jackknife method to reduce this bias and to obtain confidence intervals that are correctly centered under rectangular-array asymptotics. The method is explicitly designed to handle dynamics in the data and yields estimators that are straightforward to implement and that can be readily applied to a range of models and estimands. We provide distribution theory for estimators of index coefficients and average effects, present validity tests for the jackknife, and consider extensions to higher-order bias correction and to two-step estimation problems. An empirical illustration on female labor-force participation is also provided.


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Version de l'éditeur 2014-03.pdf 0,65 MB