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Study of discrete choice models and fuzzy rule based systems in the prediction of economic crisis periods in USA

Eleftherios Giovanis: Bologna University


This paper studies the economic recessions and the financial crisis in US economy, as these crisis periods affect not only USA but the rest of the world. The wrong government policies and the regulations in bond market among others lead to the longest and deepest financial crisis since the Great depression of 1929. In this paper we examine three models in order to predict the economic recession or expansion periods in USA. The first one is the Logit model, the second is the Probit model and the last one is a fuzzy rule based system binary regression with sigmoid membership function. We examine the in-sample period 1913-2005 and we test the models in the outof sample period 2006-2009. The estimation results indicate that the fuzzy regression outperforms the Logit and Probit models, especially in the out-of sample period. This indicates that fuzzy regressions provide a better and more reliable signal on whether or not a financial crisis will take place. Furthermore, based on the estimated values for the period 1913-2009 we estimate the forecasts to investigate if the economic recession will be continued or not during 2010. The conclusion is that Logit model presents a signal that the economic recession will be continued during the whole period 2010, while based on Probit and fuzzy regressions the economic recovery might begin in the second half of 2010.

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