Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/112127
Title: Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming
Author: Clavería González, Óscar
Monte Moreno, Enric
Torra Porras, Salvador
Keywords: Indicadors econòmics
Enquestes
Anàlisi de regressió
Algorismes
Economic indicators
Surveys
Regression analysis
Algorithms
Issue Date: 2017
Publisher: Universitat de Barcelona. Institut de Recerca en Economia Aplicada Regional i Pública
Abstract: In this study we use agents’ expectations about the state of the economy to generate indicators of economic activity in twenty-six European countries grouped in five regions (Western, Eastern, and Southern Europe, and Baltic and Scandinavian countries). We apply a data-driven procedure based on evolutionary computation to transform survey variables in economic growth rates. In a first step, we design five independent experiments to derive the optimal combination of expectations that best replicates the evolution of economic growth in each region by means of genetic programming, limiting the integration schemes to the main mathematical operations. We then rank survey variables according to their performance in tracking economic activity, finding that agents’ “perception about the overall economy compared to last year” is the survey variable with the highest predictive power. In a second step, we assess the out-of-sample forecast accuracy of the evolved indicators. Although we obtain different results across regions, Austria, Slovakia, Portugal, Lithuania and Sweden are the economies of each region that show the best forecast results. We also find evidence that the forecasting performance of the survey-based indicators improves during periods of higher growth.
Note: Reproducció del document publicat a: http://www.ub.edu/irea/working_papers/2017/201711.pdf
It is part of: IREA – Working Papers, 2017, IR17/11
AQR – Working Papers, 2017, AQR17/06
URI: http://hdl.handle.net/2445/112127
ISSN: 2014-1254
Appears in Collections:Documents de treball (Institut de Recerca en Economia Aplicada Regional i Pública (IREA))
AQR (Grup d’Anàlisi Quantitativa Regional) – Working Papers

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