Pesaran and Smith (1995) show that, under slope heterogeneity, GMM (and simple Least Square Dummy Variable) dynamic fixed effect estimates of the speed of convergence are usually affected by a downward heterogeneity bias. Accordingly, Arnold et al (2011) rather looked at an error correction (ECM) version of equation A3.8, using Pooled Mean Group (PMG) estimators which allow the speed of convergence to the steady state differ across countries. This is a realistic approach, as both exogenous (i.e. Solow) and endogenous (i.e. Uzawa-Lucas) growth models imply that the speed of convergence to the steady state differs across countries because of cross-country heterogeneity in population growth, technical change and progressiveness of the income tax. Moreover, the approach permits to discriminate between growth theories by glancing at the estimated parameters. In fact, for plausible values of the parameters, the Solow model implies a much slower speed of convergence to the steady state than that implied by the Lucas model (the paper concludes that the estimated speed of convergence is compatible with endogenous growth theories). As mentioned, this empirical approach could not be taken in the case of present analysis due to the lack of time series variation in inequality data.