New Economics Papers
on Neuroeconomics
Issue of 2007‒02‒24
two papers chosen by
Daniela Raeva

  1. Consumers Sentiment and Cognitive Macroeconometrics Paradoxes and Explanations By Maurizio Bovi
  2. Predicting Sovereign Debt Crises Using Artificial Neural Networks: A Comparative Approach By Marco Fioramanti

  1. By: Maurizio Bovi (ISAE - Institute for Studies and Economic Analyses)
    Abstract: Using data from the Business Surveys Unit of the European Commission as a long-running-continental-scale experiment, this paper examines how, and how accurately, people assess economic systems. Data show both commonsense (e.g. people know the past better than the future) and puzzling results (e.g. there is a systematic bias in forecasts). The former support the reliability of the surveys, the latter are in sharp contrast with the standard maintained hypothesis of a world populated by calculating and unemotional maximizers. The dualism of behavior may be fruitfully explored via cognitive psychology, according to which both logic and emotions systematically drive people’s choices.
    Keywords: Beliefs, survey research, consumer sentiment, cognitive economics.
    JEL: C42 C82 D12 D84
    Date: 2006–04
  2. By: Marco Fioramanti (ISAE - Institute for Studies and Economic Analyses; University of Pescara, Faculty of Economics)
    Abstract: Recent episodes of financial crises have revived the interest in developing models that are able to timely signal their occurrence. The literature has developed both parametric and non parametric models to predict these crises, the so called Early Warning Systems. Using data related to sovereign debt crises occurred in developing countries from 1980 to 2004, this paper shows that a further progress can be done applying a less developed non-parametric method, i.e. Artificial Neural Networks (ANN). Thanks to the high flexibility of neural networks and to the Universal Approximation Theorem an ANN based early warning system can, under certain conditions, outperform more consolidated methods.
    Keywords: Early Warning System; Financial Crisis; Sovereign Debt Crises; Artificial Neural Network.
    JEL: F34 F37 C45 C14
    Date: 2006–10

This issue is ©2007 by Daniela Raeva. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
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NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.