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Structural Models in Real Time

Author

Listed:
  • Kevin Clinton
  • Marianne Johnson
  • Mr. Jaromir Benes
  • Mr. Douglas Laxton
  • Mr. Troy D Matheson

Abstract

This paper outlines a simple approach for incorporating extraneous predictions into structural models. The method allows the forecaster to combine predictions derived from any source in a way that is consistent with the underlying structure of the model. The method is flexible enough that predictions can be up-weighted or down-weighted on a case-by-case basis. We illustrate the approach using a small quarterly structural and real-time data for the United States.

Suggested Citation

  • Kevin Clinton & Marianne Johnson & Mr. Jaromir Benes & Mr. Douglas Laxton & Mr. Troy D Matheson, 2010. "Structural Models in Real Time," IMF Working Papers 2010/056, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2010/056
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    References listed on IDEAS

    as
    1. Ricardo Mestre & Peter McAdam, 2011. "Is forecasting with large models informative? Assessing the role of judgement in macroeconomic forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(3), pages 303-324, April.
    2. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
    3. Eric Leeper, 2003. "An "Inflation Reports" Report," NBER Working Papers 10089, National Bureau of Economic Research, Inc.
    4. Michel Juillard & Ondrej Kamenik & Michael Kumhof & Douglas Laxton, 2006. "Measures of Potential Output from an Estimated DSGE Model of the United States," Working Papers 2006/11, Czech National Bank.
    5. Tiff Macklem, 2002. "Information and Analysis for Monetary Policy: Coming to a Decision," Bank of Canada Review, Bank of Canada, vol. 2002(Summer), pages 11-18.
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    Cited by:

    1. Rania A. Al-Mashat & Mr. Aleš Bulíř & N. Nergiz Dinçer & Tibor Hlédik & Mr. Tomás Holub & Asya Kostanyan & Mr. Douglas Laxton & Armen Nurbekyan & Mr. Rafael A Portillo & Hou Wang, 2018. "An Index for Transparency for Inflation-Targeting Central Banks: Application to the Czech National Bank," IMF Working Papers 2018/210, International Monetary Fund.
    2. Jan Brùha, 2011. "An Empirical Small Labor Market Model for the Czech Economy," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(5), pages 434-449, November.
    3. Piotr Białowolski & Tomasz Kuszewski & Bartosz Witkowski, 2014. "Bayesian averaging of classical estimates in forecasting macroeconomic indicators with application of business survey data," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(1), pages 53-68, February.
    4. Ali Alichi & Mr. Jaromir Benes & Mr. Joshua Felman & Irene Feng & Charles Freedman & Mr. Douglas Laxton & Mr. Evan C Tanner & David Vávra & Hou Wang, 2015. "Frontiers of Monetary Policymaking: Adding the Exchange Rate as a Tool to Combat Deflationary Risks in the Czech Republic," IMF Working Papers 2015/074, International Monetary Fund.
    5. Jan Bruha & Tibor Hledik & Tomas Holub & Jiri Polansky & Jaromir Tonner, 2013. "Incorporating Judgments and Dealing with Data Uncertainty in Forecasting at the Czech National Bank," Research and Policy Notes 2013/02, Czech National Bank.

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