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,

• author = "Oscar Claveria and Enric Monte and Salvador Torra",
• title = "Quantification of Survey Expectations by Means of Symbolic Regression via Genetic Programming to Estimate Economic Growth in Central and Eastern European Economies",
• journal = "Eastern European Economics",
• year = "2016",
• volume = "54",
• number = "2",
• pages = "171--189",
• keywords = "genetic algorithms, genetic programming, Economic Climate Indicators, evolutionary algorithms, forecasting, symbolic regression, survey-based expectations, tendency surveys",
• ISSN = "0012-8775",
• URL = "https://doi.org/10.1080/00128775.2015.1136564",
• size = "19 pages",
• 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.",
• 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

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