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Money Demand in Uruguay an artificial neural network approach

Author

Listed:
  • Elizabeth Bucacos

    (Banco Central del Uruguay)

Abstract

This paper examines money demand with error-correction models (ECM) and artificial neural network (ANN) methods in order to approximate more accurately the "true" underlying non-linear functional forms for the long-run equilibrium demand for money, and to estimate the learning and adjustment processes for money stocks in the short run. Non-linear techniques like Artificial Neural Networks are more appropriate to deal with those nonlinearities because, among other reasons, ANN can process information in multiple layers, each neuron has a nonlinear response to inputs, and they work in parallel. Unlike previous studies, in this paper inflation and exchange-rate uncertainty are explicitly incorporated in the short-run demand for money.

Suggested Citation

  • Elizabeth Bucacos, 1996. "Money Demand in Uruguay an artificial neural network approach," Documentos de trabajo 1996003, Banco Central del Uruguay.
    • Handle: RePEc:bku:doctra:1996003
    as

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    File URL: https://www.bcu.gub.uy/Estadisticas-e-Indicadores/Documentos%20de%20Trabajo/3.1996.pdf
    File Function: First version, 1996
    Download Restriction: no
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