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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- @Article{Claveria:2016:EEE,
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author = "Oscar Claveria and Enric Monte and Salvador Torra",
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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",
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journal = "Eastern European Economics",
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year = "2016",
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volume = "54",
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number = "2",
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pages = "171--189",
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keywords = "genetic algorithms, genetic programming, Economic
Climate Indicators, evolutionary algorithms,
forecasting, symbolic regression, survey-based
expectations, tendency surveys",
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ISSN = "0012-8775",
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URL = "https://doi.org/10.1080/00128775.2015.1136564",
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size = "19 pages",
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abstract = "Tendency surveys are the main source of agents
expectations. This study has a twofold aim. First, it
proposes a new method to quantify survey-based
expectations by means of symbolic regression (SR) via
genetic programming. Second, it combines the main
SR-generated indicators to estimate the evolution of
GDP, obtaining the best results for the Czech Republic
and Hungary. Finally, it assesses the impact of the
2008 financial crisis, finding that the capacity of
agents expectations to anticipate economic growth in
most Central and Eastern European economies improved
after the crisis.",
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notes = "Institute of Applied Economics Research (AQR-IREA),
University of Barcelona, Barcelona, Spain",
- }
Genetic Programming entries for
Oscar Claveria Gonzalez
Enric Monte Moreno
Salvador Torra
Citations