Determinants and Dynamics of Current Account Reversals: An Empirical Analysis

32 Pages Posted: 21 Jun 2010

See all articles by Roman Liesenfeld

Roman Liesenfeld

University of Cologne, Department of Economics

Guilherme V. Moura

Universidade Federal de Santa Catarina (UFSC) - Department of Economics

Jean-François Richard

affiliation not provided to SSRN

Abstract

We use panel probit models with unobserved heterogeneity, state dependence and serially correlated errors in order to analyse the determinants and the dynamics of current account reversals for a panel of developing and emerging countries. The likelihood-based inference of these models requires high-dimensional integration for which we use efficient importance sampling. Our results suggest that current account balance, terms of trades, foreign reserves and concessional debt are important determinants of current account reversal. Furthermore, we find strong evidence for serial dependence in the occurrence of reversals. While the likelihood criterion suggest that state dependence and serially correlated errors are essentially observationally equivalent, measures of predictive performance provide support for the hypothesis that the serial dependence is mainly due to serially correlated country-specific shocks related to local political or macroeconomic events.

Suggested Citation

Liesenfeld, Roman and Moura, Guilherme Valle and Richard, Jean-François, Determinants and Dynamics of Current Account Reversals: An Empirical Analysis. Oxford Bulletin of Economics and Statistics, Vol. 72, No. 4, pp. 486-517, August 2010. Available at SSRN: https://ssrn.com/abstract=1626526 or http://dx.doi.org/10.1111/j.1468-0084.2010.00588.x

Roman Liesenfeld (Contact Author)

University of Cologne, Department of Economics ( email )

Albertus-Magnus-Platz
D-50931 Köln
Germany

Guilherme Valle Moura

Universidade Federal de Santa Catarina (UFSC) - Department of Economics ( email )

PO Box 476
Florianopolis, SC 88010-970
Brazil

Jean-François Richard

affiliation not provided to SSRN

No Address Available

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