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Using large panel data sets for analysis of determinants and costs of reversals asks for controls of latent heterogeneity among countries. This article performs a Bayesian analysis, which allows for a parsimonious yet flexible handling of country specific heterogeneity via random coefficients and serially correlated errors. Consideration of persistence within the employed macroeconomic data is important to gauge the impact of explaining variables suggested by theory correctly. Bayesian specification tests provide evidence in favour of models incorporating heterogeneity and serial correlation. The results suggest that costs of reversals are overestimated, when country specific heterogeneity is neglected and stress the importance of external variables in explaining current account reversals. Results are checked for robustness against the underlying reversal definition.

Determinants and Costs of Current Account Reversals Under Heterogeneity and Serial Correlation