Jackknife and analytical bias reduction for nonlinear panel models

Jinyong Hahn and Whitney K. Newey

No 17/03, CeMMAP working papers from Institute for Fiscal Studies

Abstract: 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 T. 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 T grows with n, as an approximation to the properties of the estimators in econometric applications. We show that if T grows at the same rate as n 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 T growing faster than n1/3 suffices for correctness of the analytic correction, a property we also conjecture for the jackknife.

Date: 2003-10-01
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.cemmap.ac.uk/wp-content/uploads/2020/08/CWP1703.pdf (application/pdf)

Related works:
Journal Article: Jackknife and Analytical Bias Reduction for Nonlinear Panel Models (2004)
Working Paper: Jackknife and analytical bias reduction for nonlinear panel models (2003)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:azt:cemmap:17/03

DOI: 10.1920/wp.cem.2003.1703

Access Statistics for this paper

More papers in CeMMAP working papers from Institute for Fiscal Studies Contact information at EDIRC.
Bibliographic data for series maintained by Dermot Watson ().