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Title: Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies
Author: Clavería González, Óscar
Monte Moreno, Enric
Torra Porras, Salvador
Keywords: Algorismes
Algorismes genètics
Indicadors econòmics
Anàlisi de regressió
Genetic algorithms
Economic indicators
Regression analysis
Issue Date: Mar-2016
Publisher: Taylor and Francis
Abstract: Tendency surveys are the main source of agents' expectations. The main aim of this study is twofold. First, we propose a new method to quantify survey-based expectations by means of symbolic regression (SR) via genetic programming. Second, we combine the main SR-generated indicators to estimate the evolution of GDP, obtaining the best results for the Czech Republic and Hungary. Finally, we assess the impact of the 2008 financial crisis, finding an improvement in the capacity of agents' expectations in most Central and Eastern European economies to anticipate economic growth after the crisis.
Note: Versió postprint del document publicat a:
It is part of: Eastern European Economics, 2016, vol. 54, num. 2, p. 171-189
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ISSN: 0012-8775
Appears in Collections:Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)

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