Convergence: A Story of Quantiles and Spillovers

Abstract

In this paper, we revisit the analysis of cross-country convergence by combining spatial econometrics and panel quantile regressions to estimate conditional -convergence models. Moreover, we use both exogenous and endogenous weight matrices. Our results show that indeed the effects of initial per capita income, investment rate, population growth and human capital on growth rates vary considerably across the estimated quantiles. Convergence is not a generalized phenomenon across the conditional growth distribution. Moreover, while using exogenous spatial weight matrices does not substantially alter the findings found in a-spatial models, it appears that endogenous weights dramatically affect the estimates of the convergence process.