Mixture Models and Convergence Clubs

29 Pages Posted: 21 Jan 2008 Last revised: 11 Feb 2008

See all articles by M. Grazia Pittau

M. Grazia Pittau

University of Rome I

Roberto Zelli

University of Rome I

Paul A. Johnson

Vassar College

Date Written: January 19, 2008


In this paper we argue that modelling 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 have more power than bump hunting tests and includes a natural method of assessing the cross-component immobility necessary to imply a correspondence between components and convergence clubs. Applying the mixture approach to cross-country per capita income data for the period 1960 to 2000 we find evidence of three component densities in each of the nine years that we examine. 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. We 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. This increased concentration as well as that of the poor countries around their component mean produces a rise in polarization in the distribution over the sample period.

Keywords: Convergence Clubs, Economic Growth, Mixture Models, Polarization

JEL Classification: D31, C14

Suggested Citation

Pittau, Maria Grazia and Zelli, Roberto and Johnson, Paul Arden, Mixture Models and Convergence Clubs (January 19, 2008). Available at SSRN: https://ssrn.com/abstract=1085546 or http://dx.doi.org/10.2139/ssrn.1085546

Maria Grazia Pittau

University of Rome I ( email )

Piazzale Aldo Moro 5
Rome, 00185

Roberto Zelli

University of Rome I ( email )

Piazzale Aldo Moro, 5
Rome, 00185

Paul Arden Johnson (Contact Author)

Vassar College ( email )

124 Raymond Avenue
Poughkeepsie, NY 12604
United States

Register to save articles to
your library


Paper statistics

Abstract Views
PlumX Metrics