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A Pair-wise Approach to Testing for Output and Growth Convergence

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  • Pesaran, M.H.

Abstract

This paper proposes a pair-wise approach to testing for output convergence that considers all N(N-1)/2 possible pairs of log per capita output gaps across N economies. A general probabilistic definition of output convergence is also proposed. The approach is compatible with individual output series having unit roots, does not involve the choice of a reference country in computation of output gaps, and can be applied when N is large relative to T. The test is applied to output series in the Penn World Tables (1950-2000), and to Maddison's historical series (1870-2000). Overall, the results do not support output convergence and suggest that the findings of convergence clubs in the literature might be spurious. However, significant evidence of growth convergence is found. Non-convergence of log per capita outputs combined with growth convergence suggests that there are important country-specific factors that render output gaps highly persistent.

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Bibliographic Info

Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 0453.

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Length: 66
Date of creation: Oct 2004
Date of revision:
Handle: RePEc:cam:camdae:0453

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Keywords: Economic Growth; Panel Data Models; Common Technological Shocks; Convergence;

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  1. Fabio Canova, 2004. "Testing for Convergence Clubs in Income Per Capita: A Predictive Density Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(1), pages 49-77, 02.
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  8. Galor, Oded, 1996. "Convergence? Inferences from Theoretical Models," Economic Journal, Royal Economic Society, vol. 106(437), pages 1056-69, July.
  9. Xavier Sala-i-Martin, 2002. "The Disturbing "Rise" of Global Income Inequality," NBER Working Papers 8904, National Bureau of Economic Research, Inc.
  10. Bianchi, Marco, 1997. "Testing for Convergence: Evidence from Non-parametric Multimodality Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(4), pages 393-409, July-Aug..
  11. L. Vanessa Smith & Stephen Leybourne & Tae-Hwan Kim & Paul Newbold, 2004. "More powerful panel data unit root tests with an application to mean reversion in real exchange rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(2), pages 147-170.
  12. Islam, Nazrul, 1995. "Growth Empirics: A Panel Data Approach," The Quarterly Journal of Economics, MIT Press, vol. 110(4), pages 1127-70, November.
  13. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-36, July.
  14. Bernard, Andrew B & Durlauf, Steven N, 1995. "Convergence in International Output," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 97-108, April-Jun.
  15. Nazrul Islam, 2003. "What have We Learnt from the Convergence Debate?," Journal of Economic Surveys, Wiley Blackwell, vol. 17(3), pages 309-362, 07.
  16. Durlauf, S.M. & Johnson, P.A., 1995. "Multiple Regimes and Cross-Country Growth Behavior," Working papers 9419r, Wisconsin Madison - Social Systems.
  17. Binder, Michael & Pesaran, M Hashem, 1999. " Stochastic Growth Models and Their Econometric Implications," Journal of Economic Growth, Springer, vol. 4(2), pages 139-83, June.
  18. Binder, M. & Pesaran, M.H., 1996. "Stochastic Growth," Cambridge Working Papers in Economics 9615, Faculty of Economics, University of Cambridge.
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