Economic forecasting with evolved confidence indicators
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- @Article{CLAVERIA:2020:EM,
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author = "Oscar Claveria and Enric Monte and Salvador Torra",
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title = "Economic forecasting with evolved confidence
indicators",
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journal = "Economic Modelling",
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year = "2020",
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ISSN = "0264-9993",
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DOI = "doi:10.1016/j.econmod.2020.09.015",
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URL = "http://www.sciencedirect.com/science/article/pii/S0264999320311998",
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keywords = "genetic algorithms, genetic programming, forecasting,
economic growth, qualitative survey data, business and
consumer expectations, symbolic regression,
evolutionary algorithms",
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abstract = "We present a machine-learning method for sentiment
indicators construction that allows an automated
variable selection procedure. By means of genetic
programming, we generate country-specific business and
consumer confidence indicators for thirteen European
economies. The algorithm finds non-linear combinations
of qualitative survey expectations that yield estimates
of the expected rate of economic growth. Firms'
production expectations and consumers' expectations to
spend on home improvements are the most frequently
selected variables - both lagged and contemporaneous.
To assess the performance of the proposed approach, we
have designed an out-of-sample iterative predictive
experiment. We found that forecasts generated with the
evolved indicators outperform those obtained with time
series models. These results show the potential of the
methodology as a predictive tool. Furthermore, the
proposed indicators are easy to implement and help to
monitor the evolution of the economy, both from demand
and supply sides.",
- }
Genetic Programming entries for
Oscar Claveria Gonzalez
Enric Monte Moreno
Salvador Torra
Citations