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Evaluación de pronóstico de una red neuronal sobre el PIB en Colombia

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  • José Mauricio Salazar Sáenz

Abstract

Las redes neuronales artificiales han mostrado ser modelos robustos para dar cuenta del comportamiento de diferentes variables. En el presente trabajo se emplean para modelar la relación no lineal del crecimiento del PIB. Tres modelos son considerados: dos autoregresivos (especificación lineal y no lineal) y una red neuronal que usa la tasa de interés. Evaluando el desempeño de los modelos dentro y fuera de muestra, los pronósticos realizados por las redes neuronales artificiales superan ampliamente a los modelos lineales, siendo esta evidencia de relaciones asimétricas en el comportamiento del PIB en Colombia.

Suggested Citation

  • José Mauricio Salazar Sáenz, 2009. "Evaluación de pronóstico de una red neuronal sobre el PIB en Colombia," Borradores de Economia 575, Banco de la Republica de Colombia.
    • Handle: RePEc:bdr:borrec:575
    DOI: 10.32468/be.575
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    1. Fabiani, S. & Druant, M. & Hernando, I. & Kwapil, C. & Landau, B. & Claire Loupias & Martins, F. & Math , T. & Sabbatini, R. & Stahl, H. & Stockman, A., 2005. "The Pricing Behaviour of Firms in the Euro Area: New Survey Evidence," Working papers 135, Banque de France.
    2. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    3. Martha Misas Arango & Enrique L�pez Enciso & Pablo Querub�n Borrero, 2002. "La Inflaci�n en Colombia: Una Aproximaci�n desde las Redes Neuronales," Borradores de Economia 3029, Banco de la Republica.
    4. Martha Misas A. & Enrique L�pez E. & Carlos A. Arango A. & Juan Nicol�s Hern�ndez A., 2003. "La Demanda de Efectivo en Colombia: Una Caja Nagra a la Luz de las Redes Neuronales," Borradores de Economia 2963, Banco de la Republica.
    5. Greg Tkacz & Sarah Hu, 1999. "Forecasting GDP Growth Using Artificial Neural Networks," Staff Working Papers 99-3, Bank of Canada.
    6. Sims, Christopher A, 1980. "Comparison of Interwar and Postwar Business Cycles: Monetarism Reconsidered," American Economic Review, American Economic Association, vol. 70(2), pages 250-257, May.
    7. Carmen M. Reinhart. & Vicent R. Reinhart, 1991. "Fluctuaciones del producto y choques monetarios: evidencia colombiana," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 10(20), pages 53-85.
    8. Munir A. Jalil. B & Martha Misas, 2006. "Evaluaci�n de pron�sticos del tipo de cambio utilizando," Borradores de Economia 2636, Banco de la Republica.
    9. Carmen M. Reinhart. & Vicent R. Reinhart, 1991. "Fluctuaciones del producto y choques monetarios: evidencia colombiana," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 10(20), pages 53-85, December.
    10. Silvia Fabiani & Martine Druant & Ignacio Hernando & Claudia Kwapil & Bettina Landau & Claire Loupias & Fernando Martins & Thomas Mathä & Roberto Sabbatini & Harald Stahl & Ad Stokman, 2006. "What Firms' Surveys Tell Us about Price-Setting Behavior in the Euro Area," International Journal of Central Banking, International Journal of Central Banking, vol. 2(3), September.
    11. Norman R. Swanson & Halbert White, 1997. "A Model Selection Approach To Real-Time Macroeconomic Forecasting Using Linear Models And Artificial Neural Networks," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 540-550, November.
    12. Yoshihito Saito & Yoko Takeda, 2000. "Predicting the US Real GDP Growth Using Yield Spreads of Corporate Bonds," Bank of Japan Working Paper Series International Department,, Bank of Japan.
    13. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    14. Araújo, E. & Gama, C. A. F., 2004. "Replicando características de ciclos econômicos: um estudo comparativo entre Redes Neurais Artificiais e modelos ARIMA," Insper Working Papers wpe_45, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    15. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164.
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    Keywords

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    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
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production

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