TY - JOUR
AU - Jochmans, Koen
AB - 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.
TI - Split-panel Jackknife Estimation of Fixed-effect Models
JF - The Review of Economic Studies
DO - 10.1093/restud/rdv007
DA - 2015-07-12
UR - https://www.deepdyve.com/lp/oxford-university-press/split-panel-jackknife-estimation-of-fixed-effect-models-uwQMfju5cP
SP - 991
EP - 1030
VL - 82
IS - 3
DP - DeepDyve
ER -