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No-linealidades en la demanda de efectivo en Colombia: las redes neuronales como herramienta de pronóstico

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  • Martha A. Misas A.
  • Enrique López E.
  • Carlos A. Arango A.
  • uan Nicolás Hernández A.

Abstract

Forecasting the demand for cash in Colombia has become a true challenge in the recent past. The last decade witnessed strong changes in the variables that determine the demand for money: Inflation and, hence, interest rates, fall substantially, technological progress was strong in the Colombian Payment System and distorting Tobin-like taxes to financial transactions were imposed. These changes are of special relevance when the demand for money is a non-linear function of its determinants. In this paper we exploit the flexibility of artificial neural networks (ANN) to explore the existence of nonlinearity in the demand for cash. The results show that the ANN models outperform those of linear nature in terms of forecast errors. Furthermore, significant evidence is found of non-linearity in the dynamics of the demand for cash.

Suggested Citation

  • 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, vol. 22(45), pages 10-57, June.
    • Handle: RePEc:col:000107:003277
    DOI: 10.32468/Espe.4501
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    Cited by:

    1. Carlos A. Arango A., 2004. "La Demanda De Especies Monetarias En Colombia: Estructura Y Pronóstico," Borradores de Economia 2964, Banco de la Republica.

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    Keywords

    DEMAND FOR MONEY;

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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