Econometrica

Journal Of The Econometric Society

An International Society for the Advancement of Economic
Theory in its Relation to Statistics and Mathematics

Edited by: Guido W. Imbens • Print ISSN: 0012-9682 • Online ISSN: 1468-0262

Econometrica: Jul, 2004, Volume 72, Issue 4

Jackknife and Analytical Bias Reduction for Nonlinear Panel Models

https://doi.org/10.1111/j.1468-0262.2004.00533.x
p. 1295-1319

Jinyong Hahn, Whitney Newey

Fixed effects estimators of panel models can be severely biased because of the well‐known incidental parameters problem. We show that this bias can be reduced by using a panel jackknife or an analytical bias correction motivated by large . We give bias corrections for averages over the fixed effects, as well as model parameters. We find large bias reductions from using these approaches in examples. We consider asymptotics where grows with , as an approximation to the properties of the estimators in econometric applications. We show that if grows at the same rate as , the fixed effects estimator is asymptotically biased, so that asymptotic confidence intervals are incorrect, but that they are correct for the panel jackknife. We show growing faster than suffices for correctness of the analytic correction, a property we also conjecture for the jackknife.


Log In To View Full Content