Growth and Convergence in a Multi-County empirical Stochastic Solow Model
AbstractThe paper considers international per capita output and its growth using a panel of data for 102 countries between 1960-1989. It sets out an explicitly stochastic Solow growth model and shows that this has quite different properties from the standard approach where the output equation is obtained by adding an error term to the linearized solution of a deterministic Solow model. It examines the econometric properties of estimates of beta convergence as traditionally defined in the literature and shows that all these estimates are subject to substantial biases. Empirical estimates clearly reflect the nature and the magnitude of these biases as predicted by econometric theory. Steady state growth rates differ significantly across countries and once this heterogeneity is allowed for, the estimates of beta are substantially higher than the consensus in the literature. But they are very imprecisely estimated and difficult to interpret. The paper also discusses the economic implications of these results for sigma convergence.
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Bibliographic InfoPaper provided by Department of Economics, University of Leicester in its series Discussion Papers in Economics with number 96/14.
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Postal: Department of Economics University of Leicester, University Road. Leicester. LE1 7RH. UK
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Other versions of this item:
- Kevin Lee & M. Hashem Pesaran & Ron Smith, 1996. "Growth and Convergence in a Multi-Country Empirical Stochastic Solow Model," Working Papers 9637, Economic Research Forum, revised Dec 1996.
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