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La Inflación En Colombia: Una Aproximación Desde Las Redes Neuronales




Este documento presenta un modelo de estimación de la inflación en Colombia con base en la utilización de un modelo de la red neuronal artificial (ANN). La prueba de no-linealidad de la relación entre el dinero y la inflación, al igual que diferentes argumentos teóricos mencionados en el trabajo, muestra la importancia de modelar la inflación con técnicas no lineales como las redes neuronales.

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Volume (Year): 20 (2002)
Issue (Month): 41-42 (June)
Pages: 143-214

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Handle: RePEc:col:000107:005350
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  1. Donald P. Morgan, 1993. "Asymmetric effects of monetary policy," Economic Review, Federal Reserve Bank of Kansas City, issue Q II, pages 21-33.
  2. Nicoletti-Altimari, Sergio, 2001. "Does money lead inflation in the euro area?," Working Paper Series 0063, European Central Bank.
  3. Lars E. O. Svensson, 1999. "Monetary policy issues for the Eurosystem," Proceedings, Federal Reserve Bank of San Francisco.
  4. Enrique López E. & Martha Misas A., 1999. "Un Examen Empirico De La Curva De Phillips En Colombia," BORRADORES DE ECONOMIA 003676, BANCO DE LA REPÚBLICA.
  5. Ball, Laurence & Mankiw, N Gregory, 1994. "Asymmetric Price Adjustment and Economic Fluctuations," Economic Journal, Royal Economic Society, vol. 104(423), pages 247-61, March.
  6. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, November.
  7. Martha Misas & Enrique López & Luis Fernando Melo, . "La Inflación desde una Perspectiva Monetaria: Un Modelo P* para Colombia," Borradores de Economia 133, Banco de la Republica de Colombia.
  8. Gerlach, Stefan & Svensson, Lars E. O., 2003. "Money and inflation in the euro area: A case for monetary indicators?," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1649-1672, November.
  9. A. M. Gazely & J. M. Binner, 2000. "The application of neural networks to the Divisia index debate: evidence from three countries," Applied Economics, Taylor & Francis Journals, vol. 32(12), pages 1607-1615.
  10. Tkacz, Greg & Hu, Sarah, 1999. "Forecasting GDP Growth Using Artificial Neural Networks," Staff Working Papers 99-3, Bank of Canada.
  11. Raimundo Soto, . "Nonlinearities in the Demand for money: A Neural Network Approach," ILADES-Georgetown University Working Papers inv107, Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines.
  12. Luis Eduardo Arango & Andrés González, 1998. "Some Evidence Of Smooth Transition Nonlinearity In Colombian Inflation," BORRADORES DE ECONOMIA 003515, BANCO DE LA REPÚBLICA.
  13. S. Baranzoni & P. Bianchi & L. Lambertini, 2000. "Multiproduct Firms, Product Differentiation, and Market Structure," Working Papers 368, Dipartimento Scienze Economiche, Universita' di Bologna.
  14. Nikola Gradojevic & Jing Yang, 2000. "The Application of Artificial Neural Networks to Exchange Rate Forecasting: The Role of Market Microstructure Variables," Staff Working Papers 00-23, Bank of Canada.
  15. Jean-François Fillion & André Léonard, 1997. "La courbe de Phillips au Canada : un examen de quelques hypothèses," Staff Working Papers 97-3, Bank of Canada.
  16. James Peery Cover, 1992. "Asymmetric Effects of Positive and Negative Money-Supply Shocks," The Quarterly Journal of Economics, Oxford University Press, vol. 107(4), pages 1261-1282.
  17. Lütkepohl, Helmut & Teräsvirta, Timo & Wolters, Jürgen, 1995. "Investigating Stability and Linearity of a German M1 Money Demand Function," SSE/EFI Working Paper Series in Economics and Finance 64, Stockholm School of Economics.
  18. Jeffrey J. Hallman & Richard D. Porter & David H. Small, 1989. "M2 per unit of potential GNP as an anchor for the price level," Staff Studies 157, Board of Governors of the Federal Reserve System (U.S.).
  19. Tkacz, Greg, 2000. "Non-Parametric and Neural Network Models of Inflation Changes," Staff Working Papers 00-7, Bank of Canada.
  20. Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-75, July.
  21. Chung-Ming Kuan, 2006. "Artificial Neural Networks," IEAS Working Paper : academic research 06-A010, Institute of Economics, Academia Sinica, Taipei, Taiwan.
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