Study of Discrete Choice Models and Adaptive Neuro-Fuzzy Inference System in the Prediction of Economic Crisis Periods in USA

Giovanis, Eleftherios

Study of Discrete Choice Models and Adaptive Neuro-Fuzzy Inference System in the Prediction of Economic Crisis Periods in USA

MPRA Paper from University Library of Munich, Germany

Abstract: In this study two approaches are applied for the prediction of the economic recession or expansion periods in USA. The first approach includes Logit and Probit models and the second is an Adaptive Neuro-Fuzzy Inference System (ANFIS) with Gaussian and Generalized Bell membership functions. The in-sample period 1950-2006 is examined and the forecasting performance of the two approaches is evaluated during the out-of sample period 2007-2010. The estimation results show that the ANFIS model outperforms the Logit and Probit model. This indicates that neuro-fuzzy model provides a better and more reliable signal on whether or not a financial crisis will take place.

Keywords: Discrete choice models; Neuro-Fuzzy; Fuzzy rules; Membership functions; Financial crisis; US economy (search for similar items in EconPapers)
JEL-codes: C25 C45 C53 C63 G01 (search for similar items in EconPapers)
Date: 2012-03
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Citations: View citations in EconPapers (2)

Published in Economic Analysis & Policy 1.42(2012): pp. 79-95

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Journal Article: Study of Discrete Choice Models and Adaptive Neuro-Fuzzy Inference System in the Prediction of Economic Crisis Periods in USA (2012)
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