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To Pool or Not to Pool: Revisited

22 Pages Posted: 16 Jun 2015  

M. Hashem Pesaran

USC Dornsife Institute for New Economic Thinking; University of Southern California; Trinity College, Cambridge

Qiankun Zhou

University of Southern California

Multiple version iconThere are 2 versions of this paper

Date Written: June 15, 2015

Abstract

This paper provides a new comparative analysis of pooled least squares and fixed effects estimators of the slope coefficients in the case of panel data models when the time dimension (T) is fixed while the cross section dimension (N) is allowed to increase without bounds. The individual effects are allowed to be correlated with the regressors, and the comparison is carried out in terms of an exponent coefficient, δ, which measures the degree of pervasiveness of the fixed effects in the panel. It is shown that the pooled estimator remains consistent so long as δ < 1, and is asymptotically normally distributed if δ < 1/2, for a fixed T and as N → 1. It is further shown that when δ < 1/2, the pooled estimator is more efficient than the fixed effects estimator. Monte Carlo evidence provided supports the main theoretical findings and gives some indications of gains to be made from pooling when δ < 1/2. The problem of how to estimate δ in short T panels is not considered in this paper.

Keywords: Short panel, Fixed effects estimator, Pooled estimator, Efficiency

JEL Classification: C01, C23, C33

Suggested Citation

Pesaran, M. Hashem and Zhou, Qiankun, To Pool or Not to Pool: Revisited (June 15, 2015). USC-INET Research Paper No. 15-16. Available at SSRN: https://ssrn.com/abstract=2618773 or http://dx.doi.org/10.2139/ssrn.2618773

M. Hashem Pesaran (Contact Author)

USC Dornsife Institute for New Economic Thinking ( email )

3620 S. Vermont Avenue, KAP 364F
Los Angeles, CA 90089-0253
United States

University of Southern California ( email )

Los Angeles, CA 90089
United States

Trinity College, Cambridge ( email )

United Kingdom

Qiankun Zhou

University of Southern California ( email )

Los Angeles, CA 90089
United States

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