Mixture Models, Convergence Clubs, And Polarization

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.