Due to model uncertainty, there is no consensus about which are the most salient determinants of economic growth. To address model uncertainty, Bayesian Model Averaging approaches have recently been used in cross-country cross-sectional analyses. This paper extends these approaches to panel data...

In this paper I estimate empirical growth models simultaneaously considering endogenous regressors and model uncertainty. In order to apply Bayesian methods such as Bayesian Model Averaging (BMA) to dynamic panel data models with predetermined or endogenous variables and fixed effects, I propose...

Fragility of regression analysis to arbitrary assumptions and decisions about choice of control variables is an important concern for applied econometricians (e.g. Leamer (1983)). Sensitivity analysis in the form of model averaging represents an (agnostic) approach that formally addresses this...