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Mixture Models, Convergence Clubs, And Polarization


  • Maria Grazia Pittau
  • Roberto Zelli
  • Paul A. Johnson


We argue that modeling the cross-country distribution of per capita income as a mixture distribution provides a natural framework for the detection of convergence clubs. The framework yields tests for the number of component distributions that are likely to be more informative than "bump hunting" tests and includes a method of assessing the cross-component immobility necessary to imply a correspondence between components and convergence clubs. Applying this approach to Penn World Data for the period 1960 to 2000 we find evidence of three component densities. We find little cross-component mobility and so interpret the multiple mixture components as representing convergence clubs. We document a pronounced tendency for the strength of the bonds between countries and clubs to increase and show that the well-known "hollowing out" of the middle of the distribution is largely attributable to the increased concentration of the rich countries around their component means. Copyright 2009 The Authors. Journal compilation International Association for Research in Income and Wealth 2009.

Suggested Citation

  • Maria Grazia Pittau & Roberto Zelli & Paul A. Johnson, 2010. "Mixture Models, Convergence Clubs, And Polarization," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 56(1), pages 102-122, March.
  • Handle: RePEc:bla:revinw:v:56:y:2010:i:1:p:102-122

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    References listed on IDEAS

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    1. Md. Rabiul Islam & James B. Ang & Jakob B. Madsen, 2014. "Quality-Adjusted Human Capital And Productivity Growth," Economic Inquiry, Western Economic Association International, vol. 52(2), pages 757-777, April.
    2. Battisti, Michele & Parmeter, Christopher F., 2012. "GDP clustering: A reappraisal," Economics Letters, Elsevier, vol. 117(3), pages 837-840.
    3. Fabio Clementi & Francesco Schettino, 2013. "Income polarization in Brazil, 2001-2011: A distributional analysis using PNAD data," Economics Bulletin, AccessEcon, vol. 33(3), pages 1796-1815.
    4. Gordon Anderson & Alessio Farcomeni & Grazia Pittau & Roberto Zelli, 2014. "A new approach to measuring and studying the characteristics of class membership: The progress of poverty, inequality and polarization of income classes in urban China," Working Papers tecipa-521, University of Toronto, Department of Economics.
    5. Di Vaio, Gianfranco & Enflo, Kerstin, 2011. "Did globalization drive convergence? Identifying cross-country growth regimes in the long run," European Economic Review, Elsevier, vol. 55(6), pages 832-844, August.
    6. Krause, Melanie, 2015. "The Millennium Peak in Club Convergence - What the Critical Bandwidth Can Say About Distributional Changes in the Wealth of Nations," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113053, Verein für Socialpolitik / German Economic Association.
    7. Garance Genicot & Debraj Ray, 2014. "Aspirations and Inequality," NBER Working Papers 19976, National Bureau of Economic Research, Inc.
    8. Barseghyan, Levon & DiCecio, Riccardo, 2011. "Cross-country income convergence revisited," Economics Letters, Elsevier, vol. 113(3), pages 244-247.
    9. Jitka Bartošová & Nicholas T. Longford, 2014. "A Study of Income Stability in the Czech Republic by Finite Mixtures," Prague Economic Papers, University of Economics, Prague, vol. 2014(3), pages 330-348.
    10. Battisti, Michele & Delgado, Michael S. & Parmeter, Christopher F., 2015. "Evolution of the global distribution of carbon dioxide: A finite mixture analysis," Resource and Energy Economics, Elsevier, vol. 42(C), pages 31-52.
    11. Amini, Shahram & Battisti, Michele & Parmeter, Christopher F., 2017. "Decomposing changes in the conditional variance of GDP over time," Economic Modelling, Elsevier, vol. 61(C), pages 376-387.
    12. Gordon Anderson & Maria Grazia Pittau & Roberto Zelli, 2016. "Assessing the convergence and mobility of nations without artificially specified class boundaries," Journal of Economic Growth, Springer, vol. 21(3), pages 283-304, September.
    13. Oleg Badunenko & Daniel Henderson & R. Russell, 2013. "Polarization of the worldwide distribution of productivity," Journal of Productivity Analysis, Springer, vol. 40(2), pages 153-171, October.
    14. Gordon Anderson & Maria Pittau & Roberto Zelli, 2014. "Poverty status probability: a new approach to measuring poverty and the progress of the poor," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(4), pages 469-488, December.
    15. Fishman, Ezra & Kimhi, Ayal, 2013. "Is the Israeli Labor Market Segmented? Revisiting the Mixture Regression Model," Discussion Papers 164512, Hebrew University of Jerusalem, Department of Agricultural Economics and Management.
    16. Anderson, Gordon & Farcomeni, Alessio & Pittau, Maria Grazia & Zelli, Roberto, 2016. "A new approach to measuring and studying the characteristics of class membership: Examining poverty, inequality and polarization in urban China," Journal of Econometrics, Elsevier, vol. 191(2), pages 348-359.
    17. Mauro Mussini & Biancamaria Zavanella, 2015. "Measuring bipolarization in labour productivity in Italy: a new index and its decomposition by sectors and regional factors," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2015(3), pages 29-55.
    18. Răileanu-Szeles, Monica & Albu, Lucian, 2015. "Nonlinearities and divergences in the process of European financial integration," Economic Modelling, Elsevier, vol. 46(C), pages 416-425.

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