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Modeling the CNB's Monetary Policy Interest Rate by Artificial Neural Networks

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  • Jaromír Kukal
  • Tran Van Quang
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    Abstract

    Knowledgeability about interest rates set by a central bank is very important for all participants in an economy. In this paper we have used publicly available data to model how Czech National Bank manipulates its 2W repo rate when conducts its monetary policy. For this purpose, eight indicators are chosen. They are the Consumer Price Index (CPI), GDP growth rate (HDP), the monthly exchange rate EURCZK (KURZ), the monthly growth rate of monetary aggregate M2 (M2), the monthly unemployment rate (NEZAM), the monetary policy interest rate of the European Central Bank (EBC), the two-week Prague Interbank Interest rate PRIBOR14 and Economic Sentiment Indicator (IES). First, they are used as explanatory variables and then as the input signals to two different artificial neural network types with different architecture: the multilayer perceptron (MLP) and radial basis function (RBF) nets with different number of hidden neurons to model 2W repo rate of CNB. As a result, we fi nd that while the RBF network fails to provide stable results superior to the one of the linear model, the MLP network always can deliver better results than the one of the linear model. The best results are achieved with a network with only two hidden neurons. Further, these results are relatively stable with minimum time needed to complete the calculation. The MLP network therefore seems to be a promising tool for modeling the 2W repo rate of CNB.

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    Bibliographic Info

    Article provided by University of Economics, Prague in its journal Politická ekonomie.

    Volume (Year): 2011 (2011)
    Issue (Month): 6 ()
    Pages: 810-829

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    Handle: RePEc:prg:jnlpol:v:2011:y:2011:i:6:id:823:p:810-829

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    Related research

    Keywords: RBF; multilayer perceptron; linear model; CNB; Artificial neural network; 2W repo rate;

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    References

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    1. Lucas, Robert Jr., 1972. "Expectations and the neutrality of money," Journal of Economic Theory, Elsevier, vol. 4(2), pages 103-124, April.
    2. N. Gregory Mankiw, 2006. "The Macroeconomist as Scientist and Engineer," Journal of Economic Perspectives, American Economic Association, vol. 20(4), pages 29-46, Fall.
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    7. Jaromir Benes & Tibor Hledik & Michael Kumhof & David Vavra, 2005. "An Economy in Transition and DSGE: What the Czech National Bank’s New Projection Model Needs," Working Papers 2005/12, Czech National Bank, Research Department.
    8. Michal Andrle & Tibor Hledik & Ondra Kamenik & Jan Vlcek, 2009. "Implementing the New Structural Model of the Czech National Bank," Working Papers 2009/2, Czech National Bank, Research Department.
    9. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
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