Recent advances in the growth literature have proposed that difficult-to-quantify concepts such as social capital may play an important role in explaining the degree of persistent income disparity that is observed among countries. Other recently explored possibilities include institutional mechanisms which generate barriers to aggregate production. An important limitation for empirical work in this area stems from the fact that it is difficult to distinguish sources of heterogeneity when direct observations are not available. In this study, we show how developments in the analysis of nonstationary panels can aid in this endeavor. In contrast to traditional dynamic panel data analysis, this approach focuses explicitly on low-frequency behavior. Under relatively mild assumptions, the approach can be used to infer properties of aggregate production which are robust to the presence of large classes of unobserved features. In this framework we are able to estimate and test the distribution of production function parameters that would be required in order to generate conditional forecast convergence of per capita incomes even when some of the key factors required to explain growth are unobserved. The results indicate that in order to fully explain the observed persistence in the disparity of per capita incomes, the manner in which unobserved mechanisms influence production must go beyond merely accounting for differences in the trending behavior of aggregate productivity. Specifically, if such mechanisms are to be successful empirically, they must also be able to account for cross-country heterogeneity in steady-state capital shares. This adds to a growing literature that provides support for models with multiple production regimes.
