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Estimación adelantada del crecimiento regional mediante redes neuronales LSTM

Author

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  • de Lucio, Juan

    (Universidad de Alcalá)

Abstract

El trabajo propone incorporar técnicas de Inteligencia Artificial a las herramientas disponibles para el análisis de coyuntura regional. Se comparan las estimaciones realizadas con Redes Neuronales (en concreto, mediante la utilización de redes con larga memoria de corto plazo, LSTM por sus siglas en inglés) con los instrumentos más habituales en el análisis de coyuntura (series temporales, indicadores sintéticos y factores dinámicos). Los resultados muestran que los avances en redes neuronales pueden ser incorporados al análisis de coyuntura mejorando las estimaciones. Son herramientas complementarias, con mayor flexibilidad para captar la diversidad de situaciones en la economía real y con una capacidad de estimación superior (menor error cuadrático medio). El documento propone la utilización de este tipo de técnicas para solucionar una diversidad de problemas en economía regional. This paper studies the incorporation of Artificial Intelligence techniques to the set of tools available for the analysis of the regional situation. The estimates using long-short-term memory, LSTM, neural networks are compared with the most common instruments in the analysis of conjuncture (time series, synthetic indicators and dynamic factors). Results show that advances in neural networks can be incorporated into the tools used in regional economic analysis reducing the estimation error. They are complementary tools, with greater flexibility to capture the diversity of situations in the real economy and with a higher estimation capacity (lower mean square error). The document suggests the use of these types of techniques to solve a variety of problems in regional research.

Suggested Citation

  • de Lucio, Juan, 2021. "Estimación adelantada del crecimiento regional mediante redes neuronales LSTM," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 49, pages 45-64.
    • Handle: RePEc:ris:invreg:0452
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    References listed on IDEAS

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    More about this item

    Keywords

    regional analysis; neural networks; artificial intelligence; LSTM;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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