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

46 Pages Posted: 31 May 2007

See all articles by Roman Liesenfeld

Roman Liesenfeld

University of Cologne, Department of Economics

Guilherme valle Moura

University of Kiel - Faculty of Economics and Social Sciences

Jean-Francois Richard

University of Pittsburgh - Department of Economics

Date Written: May 18, 2007

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). It allows the ML estimation of panel probit models with various dynamic specifications for the error components. 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.

Keywords: Panel data, Dynamic discrete choice, Importance sampling, Monte Carlo integration, State dependence, Spillover effects

JEL Classification: C15, C23, C25, F32

Suggested Citation

Liesenfeld, Roman and Moura, Guilherme valle and Richard, Jean-Francois, Dynamic Panel Probit Models for Current Account Reversals and Their Efficient Estimation (May 18, 2007). Available at SSRN: https://ssrn.com/abstract=988770 or http://dx.doi.org/10.2139/ssrn.988770

Roman Liesenfeld (Contact Author)

University of Cologne, Department of Economics ( email )

Albertus-Magnus-Platz
D-50931 Köln
Germany

Guilherme valle Moura

University of Kiel - Faculty of Economics and Social Sciences ( email )

Westring 425
D-24118 Kiel, 24161
Germany

Jean-Francois Richard

University of Pittsburgh - Department of Economics ( email )

4901 Wesley Posvar Hall
230 South Bouquet Street
Pittsburgh, PA 15260
United States
412-648-1750 (Phone)

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
141
Abstract Views
921
rank
226,643
PlumX Metrics