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La Inflación en Colombia: Una Aproximación desde las Redes Neuronales

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Listed:
  • Martha Misas Arango
  • Enrique López Enciso
  • Pablo Querubín Borrero

Abstract

Las redes neuronales (ANN) 1 son modelos computacionales diseñados para simular el funcionamiento del cerebro y, en particular, la forma como éste procesa información. En el contexto de análisis de series de tiempo, se clasifican como modelos no lineales entrenados para (i) realizar conexiones entre los valores pasados y presentes de una serie de tiempo y (ii) extraer estructuras y relaciones escondidas que gobiernan el sistema de información. El atractivo de este enfoque, inspirado en la neurología, es su habilidad para aprender, es decir, para identificar dependencias con base en una muestra finita, de manera que el conocimiento adquirido pueda ser generalizado a muestras no observadas (Herbrich et.al, 1999). Si bien, como señalan Kuan y White (1994), las redes neuronales y sus algoritmos de aprendizaje asociados están todavía lejos de ofrecer una descripción acertada de cómo funciona el cerebro, éstas se han constituido en un marco de modelación muy poderoso e interesante cuyo potencial ha sido comprobado en diversas aplicaciones en todas las ciencias2. Para Moshiri y Cameron (1998), los investigadores son atraídos hacia ese enfoque porque las redes neuronales no están sujetas a supuestos restrictivos como la linealidad, que suele ser necesaria para la aplicación de los modelos matemáticos tradicionales.

Suggested Citation

  • Martha Misas Arango & Enrique López Enciso & Pablo Querubín Borrero, 2002. "La Inflación en Colombia: Una Aproximación desde las Redes Neuronales," BORRADORES DE ECONOMIA 003029, BANCO DE LA REPÚBLICA.
  • Handle: RePEc:col:000094:003029
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    References listed on IDEAS

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    Cited by:

    1. Luis Fernando Melo & Rubén Albeiro Loaiza Maya, 2012. "Bayesian Forecast Combination for Inflation Using Rolling Windows: An Emerging Country Case," Borradores de Economia 705, Banco de la Republica de Colombia.
    2. Eliana González Molano & Luis Fernando Melo Velnadia & Anderson Grajales Olarte, 2007. "Pronósticos directos de la inflación colombiana," BORRADORES DE ECONOMIA 004247, BANCO DE LA REPÚBLICA.
    3. Martha A. Misas A. & Enrique López E. & Carlos A. Arango A. & uan Nicolás Hernández A., 2004. "No-linealidades en la demanda de efectivo en Colombia: las redes neuronales como herramienta de pronóstico," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República - ESPE, vol. 22(45), pages 10-57, June.
    4. Melo, Luis F. & Loaiza, Rubén A. & Villamizar-Villegas, Mauricio, 2016. "Bayesian combination for inflation forecasts: The effects of a prior based on central banks’ estimates," Economic Systems, Elsevier, vol. 40(3), pages 387-397.
    5. 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.
    6. Luis Fernando Melo Velandia & Martha Alicia Misas Arango, 2004. "Modelos Estructurales de Inflación en Colombia: Estimación a través de Mínimos Cuadrados Flexibles," BORRADORES DE ECONOMIA 003244, BANCO DE LA REPÚBLICA.
    7. Ignacio Lozano, 2009. "Budget Deficit, Money Growth and Inflation: Evidence from the Colombian case," Money Affairs, Centro de Estudios Monetarios Latinoamericanos, CEMLA, vol. 0(1), pages 65-95, January-J.
    8. Héctor Mauricio Nuñez Amortegui, 2005. "Una evaluación de los pronósticos de inflación en Colombia bajo el esquema de inflación objetivo," Revista de Economía del Rosario, Universidad del Rosario, December.
    9. Carlos A. Arango A. & Martha Misas A. & Juan Nicolás Hernández, 2004. "La Demanda de Especies Monetarias en Colombia: Estructura y Pronóstico," Borradores de Economia 309, Banco de la Republica de Colombia.
    10. Norberto Rodríguez N. & Patricia Siado C., 2003. "Un Pronóstico no Paramétrico de la Inflación Colombiana," Borradores de Economia 248, Banco de la Republica de Colombia.
    11. María Clara Aristizábal Restrepo, 2006. "Evaluación asimétrica de una red neuronal artificial:Aplicación al caso de la inflación en Colombia," Borradores de Economia 377, Banco de la Republica de Colombia.
    12. repec:bdr:ensayo:v::y:2004:i:45:p:10-57 is not listed on IDEAS

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    More about this item

    JEL classification:

    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • J30 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - General

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