Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects When Both N and T are Large

32 Pages Posted: 31 May 2001

See all articles by Jinyong Hahn

Jinyong Hahn

University of California, Los Angeles

Guido M. Kuersteiner

Boston University - Department of Economics

Date Written: December 2000

Abstract

We consider a dynamic panel AR(1) model with fixed effects when both "n" and "T" are large. Under the "T fixed n large" asymptotic approximation, the maximum likelihood estimator is known to be inconsistent due to the well-known incidental parameter problem. We consider an alternative asymptotic approximation where "n" and "T" grow at the same rate. It is shown that, although the MLE is asymptotically biased, a relatively simple fix to the MLE results in an asymptotically unbiased estimator. The bias corrected MLE is shown to be asymptotically efficient by a Hajek type convolution theorem.

Keywords: dynamic Panel, VAR, large n-large T asymptotics, bias correction, efficiency

JEL Classification: C13, C23, C33

Suggested Citation

Hahn, Jinyong and Kuersteiner, Guido, Asymptotically Unbiased Inference for a Dynamic Panel Model with Fixed Effects When Both N and T are Large (December 2000). Available at SSRN: https://ssrn.com/abstract=271728 or http://dx.doi.org/10.2139/ssrn.271728

Jinyong Hahn

University of California, Los Angeles ( email )

405 Hilgard Avenue
Box 951361
Los Angeles, CA 90095-1361
United States

Guido Kuersteiner (Contact Author)

Boston University - Department of Economics ( email )

270 Bay State Road
Boston, MA 02215
United States