Modeling the CNB's Monetary Policy Interest Rate by Artificial Neural Networks
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.
Volume (Year): 2011 (2011)
Issue (Month): 6 ()
|Contact details of provider:|| Postal: |
Phone: (02) 24 09 51 11
Fax: (02) 24 22 06 57
Web page: http://www.vse.cz/
More information through EDIRC
|Order Information:|| Postal: Redakce Politické ekonomie, Vysoká škola ekonomická, nám. W. Churchilla 4, 130 67 Praha 3|
Web: http://www.vse.cz/polek/ Email:
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Lucas, Robert Jr., 1972. "Expectations and the neutrality of money," Journal of Economic Theory, Elsevier, vol. 4(2), pages 103-124, April.
- Jaromir Benes & Tibor Hledik & Michael Kumhof & David Vavra, 2005. "An Economy in Transition and DSGE: What the Czech National Bankâ€™s New Projection Model Needs," Working Papers 2005/12, Czech National Bank, Research Department.
- 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.
- 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.
- N. G. Mankiw., 2009.
"The Macroeconomist as Scientist and Engineer,"
N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 5.
- N. Gregory Mankiw, 2006. "The Macroeconomist as Scientist and Engineer," Harvard Institute of Economic Research Working Papers 2121, Harvard - Institute of Economic Research.
- N. Gregory Mankiw, 2006. "The Macroeconomist as Scientist and Engineer," NBER Working Papers 12349, National Bureau of Economic Research, Inc.
- Blanchard, Olivier Jean & Kiyotaki, Nobuhiro, 1987. "Monopolistic Competition and the Effects of Aggregate Demand," American Economic Review, American Economic Association, vol. 77(4), pages 647-66, September.
- Kydland, Finn E & Prescott, Edward C, 1982.
"Time to Build and Aggregate Fluctuations,"
Econometric Society, vol. 50(6), pages 1345-70, November.
- Finn E. Kydland & Edward C. Prescott, 1982. "Executable program for "Time to Build and Aggregate Fluctuations"," QM&RBC Codes 4, Quantitative Macroeconomics & Real Business Cycles.
- Finn E. Kydland & Edward C. Prescott, 1982. "Web interface for "Time to Build and Aggregate Fluctuations"," QM&RBC Codes 4a, Quantitative Macroeconomics & Real Business Cycles.
- Narayana R. Kocherlakota, 2010. "Modern macroeconomic models as tools for economic policy," The Region, Federal Reserve Bank of Minneapolis, issue May, pages 5-21.
- Krivy, Ivan & Tvrdik, Josef & Krpec, Radek, 2000. "Stochastic algorithms in nonlinear regression," Computational Statistics & Data Analysis, Elsevier, vol. 33(3), pages 277-290, May.
When requesting a correction, please mention this item's handle: RePEc:prg:jnlpol:v:2011:y:2011:i:6:id:823:p:810-829. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Vaclav Subrta)
If references are entirely missing, you can add them using this form.