Split-Panel Jackknife Estimation of Fixed-Effect Models - Archive ouverte HAL Access content directly
Preprints, Working Papers, ... Year :

Split-Panel Jackknife Estimation of Fixed-Effect Models

(1) , (2)
1
2

Abstract

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.
Fichier principal
Vignette du fichier
2014-03.pdf (662.42 Ko) Télécharger le fichier
Origin : Explicit agreement for this submission
Loading...

Dates and versions

hal-01070553 , version 1 (01-10-2014)

Licence

Attribution - NoDerivatives - CC BY 4.0

Identifiers

Cite

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

Share

Gmail Facebook Twitter LinkedIn More