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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. 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.
    2. 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.
    3. 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.
    4. Eric Leeper, 2003. "An "Inflation Reports" Report," NBER Working Papers 10089, National Bureau of Economic Research, Inc.
    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. Ales Bulir & 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. 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.
    4. 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.
    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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