Split-Panel Jackknife Estimation of Fixed-Effect Models

Geert Dhaene (1) , Koen Jochmans (2)

1 KU Leuven - Catholic University of Leuven = Katholieke Universiteit Leuven
2 ECON - Département d'économie (Sciences Po)

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.

Mots clés: bias reduction; dependent data; incidental-parameter problem; jackknife; nonlinear model

Domaines: Economies et finances

Geert Dhaene, Koen Jochmans. Split-Panel Jackknife Estimation of Fixed-Effect Models. 2014. ⟨hal-01070553⟩