Artificial neural networks versus multivariate statistics: An application from economics

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Abstract
An artificial neural network is a computer model that mimics the brain's ability to classify patterns or to make forecasts based on past experience. This paper explains the underlying theory of the widely used back-propagation algorithm and applies this procedure to a problem from the field of international economics, namely the identification of countries that are likely to seek a rescheduling of their international debt-service obligations. A comparison of the results with those obtained from three multivariate statistical procedures applied to the same data set suggests that neural networks are worthy of consideration by the applied economist.