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- W3123483313 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." @default.
- W3123483313 created "2021-02-01" @default.
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- W3123483313 date "1996-01-01" @default.
- W3123483313 modified "2023-09-26" @default.
- W3123483313 title "Money Demand in Uruguay an artificial neural network approach" @default.
- W3123483313 hasPublicationYear "1996" @default.
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