Asymptotically unbiased inference for a dynamic panel model with fixed effects when both n and T are large
By: Jinyong Hahn [and] Guido Kuersteiner
Contributors: Kuersteiner, Guido M.; Massachusetts Institute of Technology. Dept. of Economics
Series: Working paper series / Massachusetts Institute of Technology, Dept. of Economics -- working paper 01-17; Working paper (Massachusetts Institute of Technology. Dept. of Economics) -- no. 01-17.
Publisher: Massachusetts Institute of Technology, Dept. of Economics
Published: 2000
Place of publication: Cambridge, MA
Language: eng
Number of pages: 29
Description: 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.
Notes: Title from cover.

"December 2000."

Includes bibliographical references (p. 27-28).

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