Determinants and costs of current account reversals under heterogeneity and serial correlation

Recent empirical evidence suggests that reversing current account balances imply costly adjustment processes leading to reduced economic growth. Using large panel data sets to analyze determinants and costs of reversals asks for controls of heterogeneity among countries. This paper contributes a Bayesian analysis, which allows a parsimonious yet flexible handling of country specific heterogeneity via random coeffcients. Furthermore, the analysis allows for serially correlated errors in order to capture persistence within the employed macroeconomic data. Bayesian specification tests provide evidence in favor of models incorporating heterogeneity and serial correlation. The results suggest that consideration of serial correlation and heterogeneity is necessary to assess correctly the determinants and costs of reversals. Results are checked for robustness against the underlying reversal definition.