Testing Convergence in Income Distribution
The generalized method of moments (GMM) estimator is often used to test for convergence in income distribution in a dynamic panel set-up. We argue that though consistent, the GMM estimator utilizes the sample observations inefficiently. We propose a simple ordinary least squares (OLS) estimator with more efficient use of sample information. Our Monte Carlo study shows that the GMM estimator can be very imprecise and severely biased in finite samples. In contrast, the OLS estimator overcomes these shortcomings. Copyright (c) Blackwell Publishing Ltd and the Department of Economics, University of Oxford, 2008.
Year of publication: |
2009
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Authors: | Bao, Yong ; Dhongde, Shatakshee |
Published in: |
Oxford Bulletin of Economics and Statistics. - Department of Economics, ISSN 0305-9049. - Vol. 71.2009, 2, p. 295-302
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Publisher: |
Department of Economics |
Saved in:
freely available
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