To Pool or Not to Pool: Revisited

33 Pages Posted: 26 Feb 2018

See all articles by M. Hashem Pesaran

M. Hashem Pesaran

University of Southern California - Department of Economics; University of Cambridge - Trinity College (Cambridge)

Qiankun Zhou

Louisiana State University, Baton Rouge - Department of Economics

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Date Written: April 2018

Abstract

This paper provides a new comparative analysis of pooled least squares and fixed effects (FE) 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 FE in the panel. The use of δ allows us to distinguish between poolability of small N dimensional panels with large T from large N dimensional panels with small T. 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→∞. It is further shown that when δ<1/2, the pooled estimator is more efficient than the FE estimator. We also propose a Hausman type diagnostic test of δ<1/2 as a simple test of poolability, and propose a pretest estimator that could be used in practice. Monte Carlo evidence supports the main theoretical findings and gives some indications of gains to be made from pooling when δ<1/2.

Suggested Citation

Pesaran, M. Hashem and Zhou, Qiankun, To Pool or Not to Pool: Revisited (April 2018). Oxford Bulletin of Economics and Statistics, Vol. 80, Issue 2, pp. 185-217, 2018, Available at SSRN: https://ssrn.com/abstract=3129528 or http://dx.doi.org/10.1111/obes.12220

M. Hashem Pesaran (Contact Author)

University of Southern California - Department of Economics

3620 South Vermont Ave. Kaprielian (KAP) Hall 300
Los Angeles, CA 90089
United States

University of Cambridge - Trinity College (Cambridge) ( email )

United Kingdom

Qiankun Zhou

Louisiana State University, Baton Rouge - Department of Economics ( email )

Department of economics
Baton Rouge, LA 70803-6308
United States

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