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Swart R. Ghosh and Mr. Atish R. Ghosh
This paper examines the role of structural factors—governance and rule of law, corporate sector governance (creditor rights and shareholder rights), corporate financing structure—as well as macroeconomic variables in currency crises. Using a technique known as a binary recursive tree allows for interactions between the various explanatory variables. It is found that structural vulnerabilities play an important role in the occurrence of “deep” currency crises (those with a real GDP growth decline of at least 3 percentage points) and that there are complex interactions between these structural vulnerabilities and macroeconomic imbalances.
Mr. Atish R. Ghosh and Mr. Steven T Phillips
Although few would doubt that very high inflation is bad for growth, there is much less agreement about moderate inflation’s effects. Using panel regressions and a nonlinear specification, this paper finds a statistically and economically significant negative relationship between inflation and growth. This relationship holds at all but the lowest inflation rates and is robust across various samples and specifications. The method of binary recursive trees identifies inflation as one the most important statistical determinants of growth. Finally, while there are short-run growth costs of disinflation, these are only relevant for the most severe disinflations, or when the initial inflation rate is well within the single-digit range.
Mr. Robert P Flood

sectors—leading to a self-fulfilling run on the currency. In any panel dataset, it is likely that each of these various generations (or variants thereof) is represented. If these are simply lumped together, factors that are important in determining one type of crisis may not be identified because they do not help explain the other types of crises. As a methodological innovation of this paper, therefore, we go beyond standard probit analysis and use a decision-theoretic classification technique known as a binary recursive tree (BRT). This technique is particularly

Swart R. Ghosh and Mr. Atish R. Ghosh

imbalances in determining crises is often highly complex, highlighting the difficulties of undertaking effective surveillance and monitoring of countries’s potential vulnerability to crises. The remainder of this paper is organized as follows. Section 2 briefly outlines why structural vulnerabilities may be important in currency crises. Section 3 describes the methodology of binary recursive trees. Section 4 describes the data. Section 5 presents the empirical results. Section 6 concludes. II. C orporate G overnance and S tructural V ulnerabilities

Mr. Atish R. Ghosh and Mr. Steven T Phillips

methodological problems and examine the relationship between inflation, and disinflation, and output growth. We employ a large panel data set, covering IMF member countries over 1960-1996. Our primary analytical tool is a panel regression, in which our major contribution is to combine a nonlinear treatment of the inflation-growth relationship with an extensive examination of robustness. Complementing this analysis is our use of a nonlinear technique known as “binary recursive trees.” Throughout, the emphasis is on examining the still-controversial question of whether there is

Nouriel Roubini and Paolo Manasse
This paper contains an empirical investigation of the set of economic and political conditions that are associated with a likely occurrence of a sovereign debt crisis. We use a new statistical approach (Binary Recursive Tree) that allows us to derive a collection of "rules of thumb" that help identify the typical characteristics of defaulters. We find that not all crises are equal: they differ depending on whether the government faces insolvency, illiquidity, or various macroeconomic risks. We also characterize the set of fundamentals that can be associated with a relatively "risk free" zone. This classification is important for discussing appropriate policy options to prevent crises and improve response time and prediction.
Mr. Axel Schimmelpfennig, Nouriel Roubini, and Paolo Manasse
We develop an early-warning model of sovereign debt crises. A country is defined to be in a debt crisis if it is classified as being in default by Standard & Poor's, or if it has access to nonconcessional IMF financing in excess of 100 percent of quota. By means of logit and binary recursive tree analysis, we identify macroeconomic variables reflecting solvency and liquidity factors that predict a debt-crisis episode one year in advance. The logit model predicts 74 percent of all crises entries while sending few false alarms, and the recursive tree 89 percent while sending more false alarms.
Nouriel Roubini and Paolo Manasse

, debt equity swaps, and buy back for cash). We employ the Binary Recursive Tree methodology (BRT) for classification and prediction. 3 BRT is a computer-intensive data mining technique that selects explanatory variables, their critical values, and their interactions in order to identify “safe” from “crisis-prone” types. The main conclusions of our empirical analysis are as follows. First, out of 50 candidate variables, 10 predictor variables turn out to be sufficient for classification and prediction: total external debt/GDP ratio; short-term debt reserves ratio

Mr. Axel Schimmelpfennig, Nouriel Roubini, and Paolo Manasse

role of such imbalances in getting into a crisis versus getting out of a crisis? Are these effects asymmetric? Can we identify critical thresholds beyond which default risks rise considerably? Can we design an early warning systems (EWS) model of debt crises that can help predict early on the vulnerability to such a crisis? We use a panel dataset for 47 market access countries for the 1970–2002 period. We estimate and use logit models of debt crisis, a binary recursive tree technique and a combination of the two approaches. Based on our empirical analysis, we reach

Mr. Atish R. Ghosh, Mr. Jonathan David Ostry, and Miss Mahvash S Qureshi