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Mixture Models, Convergence Clubs, And Polarization

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

Abstract

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.

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Bibliographic Info

Article provided by International Association for Research in Income and Wealth in its journal Review of Income and Wealth.

Volume (Year): 56 (2010)
Issue (Month): 1 (03)
Pages: 102-122

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Handle: RePEc:bla:revinw:v:56:y:2010:i:1:p:102-122

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Cited by:
  1. Gianfranco Di Vaio & Kerstin Enflo, 2010. "Did Globalization Drive Convergence? Identifying Cross-Country Growth Regimes in the Long Run," Working Paper Series 30_10, The Rimini Centre for Economic Analysis.
  2. Garance Genicot & Debraj Ray, 2014. "Aspirations and Inequality," NBER Working Papers 19976, National Bureau of Economic Research, Inc.
  3. Battisti, Michele & Parmeter, Christopher F., 2012. "GDP clustering: A reappraisal," Economics Letters, Elsevier, vol. 117(3), pages 837-840.
  4. Clementi, F. & Schettino, F., 2013. "Income polarization in Brazil, 2001-2011: A distributional analysis using PNAD data," 2013 Second Congress, June 6-7, 2013, Parma, Italy 149891, Italian Association of Agricultural and Applied Economics (AIEAA).
  5. 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.
  6. 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.
  7. Michele Battisti & Michael S. Delgado & Christopher F. Parmeter, 2013. "Evolution of the Global Distribution of Carbon Dioxide: A Finite Mixture Analysis," Working Papers 2013-10, University of Miami, Department of Economics.

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