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Incorporating Judgments and Dealing with Data Uncertainty in Forecasting at the Czech National Bank

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  • Jan Bruha
  • Tibor Hledik
  • Tomas Holub
  • Jiri Polansky
  • Jaromir Tonner

Abstract

This paper focuses on the forecasting process at the Czech National Bank with an emphasis on incorporating expert judgments into forecasts and addressing data uncertainty. At the beginning, the core model and the forecasting process are described and it is presented how data and the underlying uncertainty are handled. The core of the paper contains five case studies, which reflect policy issues addressed during forecasting rounds since 2008. Each case study first describes a particular forecasting problem, then the way how the issue was addressed, and finally the effect of incorporating off-model information into the forecast is briefly summarized. The case studies demonstrate that a careful incorporation of expert information into a structural framework may be useful for generating economically intuitive forecasts even during very turbulent times, and we show that such judgements may have important monetary policy implications.

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Bibliographic Info

Paper provided by Czech National Bank, Research Department in its series Research and Policy Notes with number 2013/02.

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Date of creation: Oct 2013
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Handle: RePEc:cnb:rpnrpn:2013/02

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Keywords: DSGE models; forecasting; Kalman filter; monetary policy.;

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  1. Adda, Jérôme & Cooper, Russell W., 1997. "Balladurette and jupette: a discrete analysis of scrapping subsidies," CEPREMAP Working Papers (Couverture Orange) 9711, CEPREMAP.
  2. V.V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2008. "New Keynesian Models: Not Yet Useful for Policy Analysis," NBER Working Papers 14313, National Bureau of Economic Research, Inc.
  3. Roberto Perotti, 2008. "In Search of the Transmission Mechanism of Fiscal Policy," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 169-226 National Bureau of Economic Research, Inc.
  4. Kevin Clinton & Marianne Johnson & Jaromir Benes & Douglas Laxton & Troy Matheson, 2010. "Structural Models in Real Time," IMF Working Papers 10/56, International Monetary Fund.
  5. McCarthy, Patrick S, 1996. "Market Price and Income Elasticities of New Vehicles Demand," The Review of Economics and Statistics, MIT Press, vol. 78(3), pages 543-47, August.
  6. Camilo E Tovar, 2008. "DSGE models and central banks," BIS Working Papers 258, Bank for International Settlements.
  7. Daniel F. Waggoner & Tao Zha, 1998. "Conditional forecasts in dynamic multivariate models," Working Paper 98-22, Federal Reserve Bank of Atlanta.
  8. Jaromir Tonner & Jiri Polansky & Osvald Vašíèek, 2011. "Parameter Drifting in a DSGE Model Estimated on Czech Data," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(5), pages 510-524, November.
  9. Jaromír Beneš & Andrew Binning & Kirdan Lees, 2008. "Incorporating judgement with DSGE models," Reserve Bank of New Zealand Discussion Paper Series DP2008/10, Reserve Bank of New Zealand.
  10. Richard H. Clarida & Diane Coyle, 1984. "Conditional Projection by Means of Kalman Filtering," Cowles Foundation Discussion Papers 702, Cowles Foundation for Research in Economics, Yale University.
  11. Jerome Adda & Russell Cooper, 2000. "The Dynamics of Car Sales: A Discrete Choice Approach," NBER Working Papers 7785, National Bureau of Economic Research, Inc.
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