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Evaluación asimétrica de una red neuronal artificial:Aplicación al caso de la inflación en Colombia

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  • María Clara Aristizábal Restrepo

Abstract

El objetivo de este trabajo es explorar la relación no lineal entre el dinero y la inflación en Colombia a través de una red neuronal artificial (RNA), utilizando información mensual de la variación del IPC y del agregado monetario M3, desde enero de 1982 hasta febrero de 2005. La Constitución de 1991 le otorgo al Banco de la República la responsabilidad de velar por la estabilidad de precios. Este hecho, sumado al rezago con el que las políticas monetarias afectan a su variable objetivo, en este caso la inflación, hace indispensable para las autoridades monetarias, contar con los mejores modelos para pronosticarla y guiar sus decisiones de política. Las RNA aparecen como una excelente alternativa para lograr este propósito, dado el comportamiento intrínsecamente no lineal exhibido por la relación entre estas variables. El presente trabajo incorpora algunas innovaciones en la modelación de dinero e inflación, que permiten generar pronósticos más confiables, debido a que el modelo se aproxima con mayor exactitud a la realidad. Tales innovaciones se refieren a una selección mas sofisticada de los rezagos significativos que deben ser incorporados en el modelo, una construcción de pronósticos que actualiza su base de datos y una función de costos asimétricos para su evaluación.

Suggested Citation

  • 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.
  • Handle: RePEc:bdr:borrec:377
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    References listed on IDEAS

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    Keywords

    Red Neuronal Artificial; No linealidad; Unidad Escondida; Función de Activación; Rolling de Pronósticos; Función de Perdida Asimétrica.;

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