The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd


  • Steven N. Durlauf
  • Paul A. Johnson
Reference work entry


One of the most widely studied empirical questions in the new growth economics concerns the role of initial conditions in affecting long-run outcomes. The statistical formulation of this dependence is known as convergence. This article surveys empirical work on convergence, with emphasis on the relationships between conventional definitions of convergence, the main statistical frameworks of evaluating convergence, and various economic models.


Cass–Koopmans growth model Cobb–Douglas functions Cointegration Convergence Endogenous growth Galton’s fallacy Growth nonlinearities Identification Income distribution Literacy rates Neoclassical growth theory Production functions Solow growth model Statistics and economics Technical change Time series analysis Regression tree 

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  1. Acemoglu, D., S. Johnson, and J. Robinson. 2001. The Colonial origins of comparative development: An empirical investigation. American Economic Review 91: 1369–1401.CrossRefGoogle Scholar
  2. Acemoglu, D., S. Johnson, and J. Robinson. 2002. Reversal of fortune: Geography and institutions in the making of the modern world income distribution. Quarterly Journal of Economics 117: 1231–1294.CrossRefGoogle Scholar
  3. Anderson, G. 2004. Making inferences about the polarization, welfare, and poverty of nations: A study of 101 countries 1970–1995. Journal of Applied Econometrics 19: 530–550.CrossRefGoogle Scholar
  4. Azariadis, C., and A. Drazen. 1990. Threshold externalities in economic development. Quarterly Journal of Economics 105: 501–526.CrossRefGoogle Scholar
  5. Barro, R. 1991. Economic growth in a cross-section of countries. Quarterly Journal of Economics 106: 407–443.CrossRefGoogle Scholar
  6. Barro, R., and X. Sala-i-Martin. 1992. Convergence. Journal of Political Economy 100: 223–251.CrossRefGoogle Scholar
  7. Bernard, A., and S. Durlauf. 1995. Convergence in international output. Journal of Applied Econometrics 10(2): 97–108.CrossRefGoogle Scholar
  8. Bernard, A., and S. Durlauf. 1996. Interpreting tests of the convergence hypothesis. Journal of Econometrics 71(1–2): 161–173.CrossRefGoogle Scholar
  9. Bloom, D., D. Canning, and J. Sevilla. 2003. Geography and poverty traps. Journal of Economic Growth 8: 355–378.CrossRefGoogle Scholar
  10. Canova, F. 2004. Testing for convergence clubs in income per capita: A predictive density approach. International Economic Review 45: 49–77.CrossRefGoogle Scholar
  11. Cannon, E., and N. Duck. 2000. Galton’s fallacy and economic convergence. Oxford Economic Papers 53: 415–419.CrossRefGoogle Scholar
  12. Caselli, F., G. Esquivel, and F. Lefort. 1996. Reopening the convergence debate: A new look at cross country growth empirics. Journal of Economic Growth 1: 363–389.CrossRefGoogle Scholar
  13. Doppelhofer, G., R. Miller, and X. Sala-i-Martin. 2004. Determinants of long-term growth: A Bayesian averaging of classical estimates (BACE) approach. American Economic Review 94: 813–835.CrossRefGoogle Scholar
  14. Durlauf, S., and P. Johnson. 1995. Multiple regimes and cross-country growth behaviour. Journal of Applied Econometrics 10: 365–384.CrossRefGoogle Scholar
  15. Durlauf, S., P. Johnson, and J. Temple. 2005. Growth econometrics. In Handbook of economic growth, ed. P. Aghion and S. Durlauf. Amsterdam: North-Holland.Google Scholar
  16. Durlauf, S., and D. Quah. 1999. The new empirics of economic growth. In Handbook of macroeconomics, ed. J. Taylor and M. Woodford. Amsterdam: North-Holland.Google Scholar
  17. Evans, P. 1996. Using cross-country variances to evaluate growth theories. Journal of Economic Dynamics and Control 20: 1027–1049.CrossRefGoogle Scholar
  18. Fernandez, C., E. Ley, and M. Steel. 2001. Model uncertainty in cross-country growth regressions. Journal of Applied Econometrics 16: 563–576.CrossRefGoogle Scholar
  19. Friedman, M. 1992. Do old fallacies ever die? Journal of Economic Literature 30: 2129–2132.Google Scholar
  20. Graham, B., and J. Temple. 2006. Rich nations, poor nations: How much can multiple equilibria explain? Journal of Economic Growth 11: 5–41.CrossRefGoogle Scholar
  21. Hobijn, B., and P. Franses. 2000. Asymptotically perfect and relative convergence of productivity. Journal of Applied Econometrics 15: 59–81.CrossRefGoogle Scholar
  22. Islam, N. 1995. Growth empirics: A panel data approach. Quarterly Journal of Economics 110: 1127–1170.CrossRefGoogle Scholar
  23. Lee, K., M. Pesaran, and R. Smith. 1997. Growth and convergence in multi country empirical stochastic Solow model. Journal of Applied Econometrics 12: 357–392.CrossRefGoogle Scholar
  24. Maasoumi, E., J. Racine, and T. Stengos. 2007. Growth and convergence: A profile of distribution dynamics and mobility. Jounal of Econometrics 136(2): 483–508.CrossRefGoogle Scholar
  25. Mankiw, N., D. Romer, and D. Weil. 1992. A contribution to the empirics of economic growth. Quarterly Journal of Economics 107: 407–437.CrossRefGoogle Scholar
  26. Papageorgiou, C., and W. Masanjala. 2004. The Solow model with CES technology: Nonlinearities with parameter heterogeneity. Journal of Applied Econometrics 19: 171–201.CrossRefGoogle Scholar
  27. Quah, D. 1993a. Galton’s fallacy and tests of the convergence hypothesis. Scandinavian Journal of Economics 95: 427–443.CrossRefGoogle Scholar
  28. Quah, D. 1993b. Empirical cross-section dynamics in economic growth. European Economic Review 37: 426–434.CrossRefGoogle Scholar
  29. Quah, D. 1996. Convergence empirics across economies with (some) capital mobility. Journal of Economic Growth 1: 95–124.CrossRefGoogle Scholar

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© Macmillan Publishers Ltd. 2018

Authors and Affiliations

  • Steven N. Durlauf
    • 1
  • Paul A. Johnson
    • 1
  1. 1.