Split-panel Jackknife Estimation of Fixed-effect Models

• Autores: Geert Dhaene, Koen Jochmans
• Localización: Review of economic studies, ISSN 0034-6527, Vol. 82, Nº 3, 2015, págs. 991-1030
• Idioma: inglés
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• Resumen

  • 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 article presents a jackknife method to reduce this bias and to obtain confidence intervals that are correctly centred under rectangular-array asymptotics. The method is explicitly designed to handle dynamics in the data, and yields estimators that are straightforward to implement and can be readily applied to a range of models and estimands. We provide distribution theory for estimators of model parameters 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 relating to female labour-force participation is also provided.