To Pool or Not to Pool: Revisited

To Pool or Not to Pool: Revisited 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Oxford Bulletin of Economics & Statistics Wiley

To Pool or Not to Pool: Revisited

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Publisher
Wiley
Copyright
Copyright © 2018 The Department of Economics, University of Oxford and John Wiley & Sons Ltd
ISSN
0305-9049
eISSN
1468-0084
D.O.I.
10.1111/obes.12220
Publisher site
See Article on Publisher Site

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.

Journal

Oxford Bulletin of Economics & StatisticsWiley

Published: Jan 1, 2018

References

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