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Further convergence accounting

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  • F. J. G. Gisbert

Abstract

This article extends the convergence accounting framework established by Serrano and proposes a simple way to statistically test for the significance of different factors of production affecting labour productivity convergence. The result comes from expressing the log of labour productivity as a sum of different factors in a Cobb-Douglas production function. The end result is that a similar accounting exercise to that in Serrano can be done using the different factors driving convergence. Its application to OECD countries over the period 1965-1990 illustrates the approach and shows that, in agreement with most of the literature, total factor productivity is the factor that has contributed most to labour convergence and that physical investment in non-residential capital is the second most important one. Human capital accumulation, on the other hand, has had little effect throughout the period, but has taken on an increasing importance in recent years. However, from the point of view of the convergence of each factor considered individually, all factors have converged, human capital having done so the most quickly.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics Letters.

Volume (Year): 10 (2003)
Issue (Month): 9 ()
Pages: 553-556

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Handle: RePEc:taf:apeclt:v:10:y:2003:i:9:p:553-556

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  1. Barro, Robert J & Lee, Jong Wha, 1996. "International Measures of Schooling Years and Schooling Quality," American Economic Review, American Economic Association, vol. 86(2), pages 218-23, May.
  2. Barro, Robert J & Lee, Jong-Wha, 2001. "International Data on Educational Attainment: Updates and Implications," Oxford Economic Papers, Oxford University Press, vol. 53(3), pages 541-63, July.
  3. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119, September.
  4. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  5. Angel de la Fuente & Rafael Domenech, 2001. "Schooling Data, Technological Diffusion, and the Neoclassical Model," American Economic Review, American Economic Association, vol. 91(2), pages 323-327, May.
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