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ASYMPTOTICALLY UNBIASED ESTIMATION OF AUTOCOVARIANCES AND AUTOCORRELATIONS WITH LONG PANEL DATA

Published online by Cambridge University Press:  17 February 2010

Ryo Okui
Ryo Okui*
Affiliation:
Kyoto University
*
*Address correspondence to Ryo Oku, Institute of Economic Research, Kyoto University, Yoshida-Honmachi, Sakyo, Kyoto, Kyoto, Japan; e-mail: okui@kier.kyoto-u.ac.jp.
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Abstract

An important reason for analyzing panel data is to observe the dynamic nature of an economic variable separately from its time-invariant unobserved heterogeneity. This paper examines how to estimate the autocovariances of a variable separately from its time-invariant unobserved heterogeneity. When both cross-sectional and time series sample sizes tend to infinity, we show that the within-group autocovariances are consistent, although they are severely biased when the time series length is short. The biases have the leading term that converges to the long-run variance of the individual dynamics. This paper develops methods to estimate the long-run variance in panel data settings and to alleviate the biases of the within-group autocovariances based on the proposed long-run variance estimators. Monte Carlo simulations reveal that the procedures developed in this paper effectively reduce the biases of the estimators for small samples.

Type
ARTICLES
Information
Econometric Theory , Volume 26 , Issue 5 , October 2010 , pp. 1263 - 1304
Copyright
Copyright © Cambridge University Press 2010

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