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Predicting Financial Debt Crises: A Case Study of India

By Matthew Sperber

The following paper develops a qualitative and quantitative model for predicting financial debt crises. The qualitative model breaks down the balance sheet of emerging market countries to identify weaknesses in the country’s assets and liabilities. The values of the items on a country’s balances sheet are then compared to the pre-crisis conditions of the East Asian and South American crises that occurred in the late 1990’s and early 2000’s. The quantitative model consists of a logistic function that uses economic variables to determine the probability that a country will face a financial crisis the following year. The logistic function is developed using a comprehensive set of data which consists of forty different variables from forty-three countries over the past ten years. The logistic model developed in the paper is further analyzed to identify the economic variables that have the greatest impact on a country having a financial crisis. The marginal effect each of the variables is identified by increasing each of the variables by one standard deviation while keeping the other variables constant. The variables with the greatest marginal effect have the largest impact on a financial crisis and policy reform is recommended based on keeping these variables at sustainable levels. The paper concludes with a case study that applies the models to India. Using the balance sheet analysis and the logistic model, India’s strengths and weaknesses are identified. The paper concludes that India is not in danger of a financial debt crisis but there are still many areas where the economy can improve.

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Advisor: Kent Kimbrough


Undergraduate Program Assistant
Jennifer Becker

Director of the Honors Program
Michelle P. Connolly