Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies

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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
Other authors:	Universitat de Barcelona
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.
Subject(s):	-Algorismes -Algorismes genètics -Indicadors econòmics -Enquestes -Anàlisi de regressió -Algorithms -Genetic algorithms -Economic indicators -Surveys -Regression analysis
Rights:	(c) Taylor and Francis, 2016 info:eu-repo/semantics/embargoedAccess
Document type:	Article Article - Accepted version
Published by:	Taylor and Francis
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