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Self-Organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis

By Óscar Clavería González, Enric Monte Moreno and Salvador Torra Porras


By means of Self-Organizing Maps we cluster fourteen European countries according to the most suitable way to model their agents’ expectations. Using the financial crisis of 2008 as a benchmark, we distinguish between those countries that show a progressive anticipation of the crisis and those where sudden changes in expectations occur. By mapping the trajectory of economic experts’ expectations prior to the recession we find that when there are brisk changes in expectations before impending shocks, Artificial Neural Networks are more suitable than time series models for modelling expectations. Conversely, in countries where expectations show a smooth transition towards recession, ARIMA models show the best forecasting performance. This result demonstrates the usefulness of clustering techniques for selecting the most appropriate method to model and forecast expectations according to their behaviour

Topics: Previsió econòmica, Desenvolupament econòmic, Xarxes neuronals (Informàtica), Anàlisi funcional no lineal, Economic forecasting, Economic development, Neural networks (Computer science), Nonlinear functional analysis
Publisher: Universitat de Barcelona. Institut de Recerca en Economia Aplicada Regional i Pública
Year: 2015
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