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

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  • María Clara Aristizábal Restrepo

    ()
    (Acciones, Bolsa y Renta, Medellín, Colombia)

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    Abstract

    The objective of the present work is to explore the non-linear relationship between money and inflation in Colombia through an artificial neural network using monthly information for the variation of the consumer price index and the monetary aggregate M3 since January 1982 through February 2005. Artificial neural networks turn up as an excellent alternative for monetary authorities to count on the best models to forecast inflation and guide their policy decisions. This article incorporates some innovations in money and inflation modeling that allow to generate more reliable forecasts given that the model approximates reality with greater accuracy

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    File URL: ftp://ftp.drivehq.com/cavasco/lecturas/numero65/n65a3.pdf
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    Bibliographic Info

    Article provided by Universidad de Antioquia, Departamento de Economía in its journal LECTURAS DE ECONOMÍA.

    Volume (Year): (2006)
    Issue (Month): 65 (Julio-Diciembre)
    Pages: 73-116

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    Handle: RePEc:lde:journl:y:2006:i:65:p:73-116

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    Web page: http://economia.udea.edu.co
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    Postal: Lecturas de Economía, Departamento de Economía, Calle 67, 53-108, Medellin 050010, Colombia.

    Related research

    Keywords: artificial neural network; non-linearity; hidden unit; activation function; rolling test; asymmetric lost function.;

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