Growth Empirics in Panel Data under Model Uncertainty and Weak Exogeneity

This paper considers cross-country growth regressions in panel data simultaneously considering model uncertainty and reverse causality concerns. For this purpose, I combine Bayesian Model Averaging with a suitable likelihood function for dynamic panel models with weakly exogenous regressors and fixed effects. In contrast to the previous consensus in the literature, empirical results indicate that the estimated convergence rate is indistinguishable from zero. Moreover, I argue that no variable can be labeled as a robust determinant of long-run economic growth according to the robustness-checking method considered in the paper.