^*Marcos Chamon is an economist with the IMF Research Department; Paolo Manasse is a professor of economics at the University of Bologna; and Alessandro Prati is an advisor with the IMF Research Department. This paper would not have been possible without the contributions of the IMF staff's working group on vulnerability indicators, IMF desk economists, and several IMF teams in charge of financial, corporate, and commodity price data. These groups also contributed to the selection of crisis episodes and to the construction of the vulnerability indicators used in this paper. We thank Jonathan Ostry, Carmen Reinhart, Marianne Schulze-Ghattas, Antonio Spilimbergo, and participants at the 2006 IMF Annual Research Conference for comments of this paper. Marcos Souto and Murad Omoev provided excellent research assistance.

Abstract

This paper uses binary classification trees (BCTs) to predict capital account crises. BCTs successively compare candidate variables and thresholds to split the data into two subsamples, allowing for a large number of indicators to be considered and complex interactions to emerge in a way that standard regressions cannot easily replicate. We identify a robust leading indicator role for three variables (international reserves, current account balance, and short-term external debt) as well as a reserve cover measure that combines them. External indebtedness and domestic GDP growth forecasts are also important predictors of vulnerability. Out of sample, we were able to capture some of the main emerging market crises with relatively few false alarms but the overall out-of-sample performance of our forecasts was mixed. Global cyclical variables help explain vulnerability to crises but they are difficult to predict and, therefore, are of limited use for forecasting purposes.