This paper provides a broad replication of Calderón et al. (2015). We address some complex and relevant issues, namely functional form, non-stationary variables and cross-sectional dependence. In particular, by adopting the CCE framework, we consider both parametric-static and dynamic-and non-parametric specications, thus allowing for dierent degrees of exibility. Contrary to Calderón et al. (2015), we nd a lack of signicance of the infrastructure index, with an estimated elasticity very close to zero for all estimates. Moreover, by employing the data-driven model selection procedure proposed by Gioldasis et al. (2021), it is found that non-parametric specications provide the best predictive performance and that CCE models always overperform with respect to traditional panel data methods that employ cross-sectional demeaning to account for cross-sectional dependence.