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...
| Autores: | , , |
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| 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 |
| Sumario: | 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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