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Determinants and dynamics of current account reversals: an empirical analysis

  • Liesenfeld, Roman
  • Moura, Guilherme V.
  • Richard, Jean-François

We use panel probit models with unobserved heterogeneity, state-dependence and serially correlated errors in order to analyze 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 (EIS). 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.

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Paper provided by Christian-Albrechts-University of Kiel, Department of Economics in its series Economics Working Papers with number 2009,04.

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Date of creation: 2009
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Handle: RePEc:zbw:cauewp:200904
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  1. Sebastian Edwards, 2004. "Thirty Years of Current Account Imbalances, Current Account Reversals and Sudden Stops," NBER Working Papers 10276, National Bureau of Economic Research, Inc.
  2. Guillermo A. Calvo & Alejandro Izquierdo & Luis-Fernando Mejia, 2004. "On the Empirics of Sudden Stops: The Relevance of Balance-Sheet Effects," NBER Working Papers 10520, National Bureau of Economic Research, Inc.
  3. Himarios, Daniel, 1989. "Do Devaluations Improve the Trade Balance? The Evidence Revisited," Economic Inquiry, Western Economic Association International, vol. 27(1), pages 143-68, January.
  4. Geweke, John F. & Keane, Michael P. & Runkle, David E., 1997. "Statistical inference in the multinomial multiperiod probit model," Journal of Econometrics, Elsevier, vol. 80(1), pages 125-165, September.
  5. Jeffrey A. Frankel & Andrew K. Rose, 1996. "Currency crashes in emerging markets: an empirical treatment," International Finance Discussion Papers 534, Board of Governors of the Federal Reserve System (U.S.).
  6. Geweke, John & Keane, Michael, 2001. "Computationally intensive methods for integration in econometrics," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 56, pages 3463-3568 Elsevier.
  7. Giancarol Corsetti & Paolo Pesenti & Nouriel Roubini & Cedric Tille, 1999. "Competitive devaluations: a welfare-based approach," Staff Reports 58, Federal Reserve Bank of New York.
  8. Sebastian Edwards, 2004. "Thirty Years of Current Account Imbalances, Current Account Reversals, and Sudden Stops," IMF Staff Papers, Palgrave Macmillan, vol. 51(s1), pages 1-49, June.
  9. Sebastian Edwards, 2004. "Financial Openness, Sudden Stops, and Current-Account Reversals," American Economic Review, American Economic Association, vol. 94(2), pages 59-64, May.
  10. Dean R. Hyslop, 1999. "State Dependence, Serial Correlation and Heterogeneity in Intertemporal Labor Force Participation of Married Women," Econometrica, Econometric Society, vol. 67(6), pages 1255-1294, November.
  11. Edwards, Sebastian & Rigobon, Roberto, 2002. "Currency crises and contagion: an introduction," Journal of Development Economics, Elsevier, vol. 69(2), pages 307-313, December.
  12. Elisabetta Falcetti & Merxe Tudela, 2006. "Modelling Currency Crises in Emerging Markets: A Dynamic Probit Model with Unobserved Heterogeneity and Autocorrelated Errors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(4), pages 445-471, 08.
  13. Jean-Francois Richard, 2007. "Efficient High-Dimensional Importance Sampling," Working Papers 321, University of Pittsburgh, Department of Economics, revised Jan 2007.
  14. Keane, Michael, 1993. "Simulation estimation for panel data models with limited dependent variables," MPRA Paper 53029, University Library of Munich, Germany.
  15. Dornbusch, Rudiger & Park, Yung Chul & Claessens, Stijn, 2000. "Contagion: Understanding How It Spreads," World Bank Research Observer, World Bank Group, vol. 15(2), pages 177-97, August.
  16. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
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