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2016-03

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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/97002

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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http://dx.doi.org/10.1080/00128775.2015.1136564

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.

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Algorismes, Algorismes genètics, Indicadors econòmics, Enquestes, Anàlisi de regressió

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Algorithms, Genetic algorithms, Economic indicators, Surveys, Regression analysis

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Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)

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CLAVERÍA GONZÁLEZ, Óscar, MONTE MORENO, Enric and TORRA PORRAS, Salvador. Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies. Eastern European Economics. 2016. Vol. 54, num. 2, pags. 171-189. ISSN 0012-8775. [consulted: 12 of June of 2026]. Available at: https://hdl.handle.net/2445/97002

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