We study the issue of income convergence across countries and regions with a Bayesian estimator which allows us to use information in an efficient and flexible way. We argue that the very slow convergence rates to a common level of per-capita income found, e.g., by Barro and Xavier Sala-i-Martin, is due to a 'fixed effect bias' that their cross-sectional analysis introduces in the results. Our approach permits the estimation of different convergence rates to different steady states for each cross sectional unit. When this diversity is allowed, we 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 by a small amount by the passage of time. The cross country distribution of the steady state is largely explained by the cross country distribution of initial conditions.
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Paper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number
137.
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