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

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...

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Detalles Bibliográficos
Autores: Clavería González, Óscar, Monte Moreno, Enric, Torra Porras, Salvador
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2016
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/97002
Acceso en línea:https://hdl.handle.net/2445/97002
Access Level:acceso abierto
Palabra clave:Algorismes
Algorismes genètics
Indicadors econòmics
Enquestes
Anàlisi de regressió
Algorithms
Genetic algorithms
Economic indicators
Surveys
Regression analysis
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spelling Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European EconomiesClavería González, ÓscarMonte Moreno, EnricTorra Porras, SalvadorAlgorismesAlgorismes genèticsIndicadors econòmicsEnquestesAnàlisi de regressióAlgorithmsGenetic algorithmsEconomic indicatorsSurveysRegression analysisTendency 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.Taylor and Francis2016info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://hdl.handle.net/2445/97002Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésVersió postprint del document publicat a: http://dx.doi.org/10.1080/00128775.2015.1136564Eastern European Economics, 2016, vol. 54, num. 2, p. 171-189http://dx.doi.org/10.1080/00128775.2015.1136564(c) Taylor and Francis, 2016info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/970022026-05-27T06:46:51Z
dc.title.none.fl_str_mv Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies
title Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies
spellingShingle 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
Algorismes
Algorismes genètics
Indicadors econòmics
Enquestes
Anàlisi de regressió
Algorithms
Genetic algorithms
Economic indicators
Surveys
Regression analysis
title_short Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies
title_full Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies
title_fullStr Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies
title_full_unstemmed Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies
title_sort Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies
dc.creator.none.fl_str_mv Clavería González, Óscar
Monte Moreno, Enric
Torra Porras, Salvador
author Clavería González, Óscar
author_facet Clavería González, Óscar
Monte Moreno, Enric
Torra Porras, Salvador
author_role author
author2 Monte Moreno, Enric
Torra Porras, Salvador
author2_role author
author
dc.subject.none.fl_str_mv Algorismes
Algorismes genètics
Indicadors econòmics
Enquestes
Anàlisi de regressió
Algorithms
Genetic algorithms
Economic indicators
Surveys
Regression analysis
topic Algorismes
Algorismes genètics
Indicadors econòmics
Enquestes
Anàlisi de regressió
Algorithms
Genetic algorithms
Economic indicators
Surveys
Regression analysis
description 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.
publishDate 2016
dc.date.none.fl_str_mv 2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/97002
url https://hdl.handle.net/2445/97002
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv 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
dc.rights.none.fl_str_mv (c) Taylor and Francis, 2016
info:eu-repo/semantics/openAccess
rights_invalid_str_mv (c) Taylor and Francis, 2016
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Taylor and Francis
publisher.none.fl_str_mv Taylor and Francis
dc.source.none.fl_str_mv Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300724

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