The issue of convergence of per-capita incomes across economic areas is an old one. Are income differences across countries and regions disappearing as time goes by? Do poor regions stay poor? In Discussion Paper No. 1265, Research Fellows Fabio Canova and Albert Marcet study the issue of income convergence across countries and regions with a Bayesian model which allows them to use information in an efficient and flexible way. The paper argues that the very slow convergence rates to a common level of per-capita income found, for example, by Barro and Sala-i-Martin, is due to a `fixed effect bias' that their cross-sectional analysis introduces in the results. The approach permits the estimation of different convergence rates to different steady states for each cross-sectional unit. When this diversity is allowed, the authors find that convergence of each unit to (its own) steady-state income level is much faster than previously estimated, but that cross-sectional differences persist: inequalities will only be reduced over time by a small amount. The cross-country distribution of the steady state is largely explained by the cross-sectional distribution of initial conditions.

Average estimates of the convergence rate are much higher than those found in the literature; approximately 11% for countries and 23% for regions, with each unit converging to its own steady state. Second, the hypothesis that the steady state is the same for all cross-sectional units is rejected by the data, both for regions and countries. Third, the initial income conditions are, by far, the most important determinant of the cross-sectional dispersion of steady states. Poorer regions and countries stay poor and, over time, differences are reduced by only a small amount.

The Poor Stay Poor:
Non-Convergence Across Countries and Regions
Fabio Canova and Albert Marcet

Discussion Paper No. 1265, November 1995 (IM)