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Dynamic Panel Probit Models for Current Account Reversals and their Efficient Estimation

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Author Info
Liesenfeld, Roman
Moura, Guilherme V.
Richard, Jean-François
Abstract

We use panel probit models with unobserved heterogeneity 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 evaluation of these models requires high-dimensional integration for which we use a generic procedure known as Efficient Importance Sampling (EIS). Our empirical results suggest that current account balance, terms of trades, foreign reserves and concessional debt are important determinants of the probability of current-account reversal. Furthermore we find under all specifications evidence for serially correlated error components and weak evidence for state dependence.

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Paper provided by Christian-Albrechts-University of Kiel, Department of Economics in its series Economics working papers with number 2007,11.

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Date of creation: 2007
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Handle: RePEc:zbw:cauewp:5584

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Web page: http://www.wiso.uni-kiel.de/econ/

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Related research
Keywords: Panel data Dynamic discrete choice Current account reversals Importance Sampling Monte Carlo integration State dependence

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Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data
C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models
F32 - International Economics - - International Finance - - - Current Account Adjustment; Short-term Capital Movements

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  6. Maria Milesi-Ferretti, Gian & Razin, Assaf, 1998. "Sharp reductions in current account deficits An empirical analysis," European Economic Review, Elsevier, vol. 42(3-5), pages 897-908, May. [Downloadable!] (restricted)
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  7. Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January. [Downloadable!] (restricted)
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  10. Wei Zhang & Lung-fei Lee, 2004. "Simulation estimation of dynamic discrete choice panel models with accelerated importance samplers," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 120-142, 06. [Downloadable!] (restricted)
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  13. Dornbusch, Rudiger & Park, Yung Chul & Claessens, Stijn, 2000. "Contagion: Understanding How It Spreads," World Bank Research Observer, Oxford University Press, vol. 15(2), pages 177-97, August.
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