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Assessing the historical role of credit: Business cycles, financial crises and the legacy of Charles S. Peirce

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  • Jordà, Òscar

Abstract

This paper provides a historical overview of financial crises and their origins. The objective is to discuss a few of the modern statistical methods that can be used to evaluate predictors of these rare events. The problem involves the prediction of binary events, and therefore fits modern statistical learning, signal processing theory, and classification methods. The discussion also emphasizes the need for statistics and computational techniques to be supplemented with economics. The success of a forecast in this environment hinges on the economic consequences of the actions taken as a result of the forecast, rather than on typical statistical metrics of prediction accuracy.

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  • Jordà, Òscar, 2014. "Assessing the historical role of credit: Business cycles, financial crises and the legacy of Charles S. Peirce," International Journal of Forecasting, Elsevier, vol. 30(3), pages 729-740.
    • Handle: RePEc:eee:intfor:v:30:y:2014:i:3:p:729-740
    DOI: 10.1016/j.ijforecast.2014.02.003
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    1. Moritz Schularick & Alan M. Taylor, 2012. "Credit Booms Gone Bust: Monetary Policy, Leverage Cycles, and Financial Crises, 1870-2008," American Economic Review, American Economic Association, vol. 102(2), pages 1029-1061, April.
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    Cited by:

    1. Harri Ponka, 2017. "The Role of Credit in Predicting US Recessions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(5), pages 469-482, August.

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