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oai:recercat.cat:2445/970022025-12-05T05:48:41Zcom_2072_1057col_2072_478808col_2072_478917

Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies Clavería González, Óscar Monte Moreno, Enric Torra Porras, Salvador Algorismes Algorismes genètics Indicadors econòmics Enquestes Anàlisi de regressió Algorithms Genetic algorithms Economic indicators Surveys Regression analysis 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. 2016-04-06T08:17:15Z 2017-10-01T22:01:26Z 2016-03 2016-04-06T08:17:21Z info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion 0012-8775 https://hdl.handle.net/2445/97002 658787 eng Versió postprint del document publicat a: http://dx.doi.org/10.1080/00128775.2015.1136564 Eastern European Economics, 2016, vol. 54, num. 2, p. 171-189 http://dx.doi.org/10.1080/00128775.2015.1136564 (c) Taylor and Francis, 2016 info:eu-repo/semantics/openAccess 19 p. application/pdf Taylor and Francis Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)