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Real-Time Forecasting in Practice: The U.S. Treasury Staff's Real-Time GDP Forecast System

Author

Listed:
  • Kitchen, John
  • Monaco, Ralph

Abstract

This paper outlines a method for making effective use of monthly indicators to develop a current-quarter GDP forecast. Estimates and projections of real GDP growth are usually used to describe how the economy is doing. But estimates of GDP are only available quarterly, and the first GDP estimate for a quarter is released late in the month following the end of the quarter. The lack of a timely, comprehensive economic picture may mean that policymakers and business planners may be as much as four months behind in recognizing a significant slowdown or acceleration in the economy. This problem is especially important around business cycle peaks or troughs, where there may be some evidence that the economy is changing direction. There are many less-comprehensive, but higher-frequency data series about the economy, however. The chief difficulty with using the multiple indicators is that different indicators can give different signals, and there is no agreed-upon way for aggregating the statistics to give a single-valued answer. In this paper, we describe the approach we have adopted at the Treasury Department to use a broad variety of high-frequency incoming data to construct “realtime” estimates of quarterly real GDP growth. We draw on the recent work by Stock and Watson and others and describe the indicators, the techniques, and the recent performance of the system.

Suggested Citation

  • Kitchen, John & Monaco, Ralph, 2003. "Real-Time Forecasting in Practice: The U.S. Treasury Staff's Real-Time GDP Forecast System," MPRA Paper 21068, University Library of Munich, Germany, revised Oct 2003.
  • Handle: RePEc:pra:mprapa:21068
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    File URL: https://mpra.ub.uni-muenchen.de/21068/2/MPRA_paper_21068.pdf
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    References listed on IDEAS

    as
    1. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2003. "The Use and Abuse of Real-Time Data in Economic Forecasting," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 618-628, August.
    2. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    3. Robert Ingenito & Bharat Trehan, 1996. "Using monthly data to predict quarterly output," Economic Review, Federal Reserve Bank of San Francisco, pages 3-11.
    4. Karen E. Dynan & Douglas W. Elmendorf, 2001. "Do provisional estimates of output miss economic turning points?," Finance and Economics Discussion Series 2001-52, Board of Governors of the Federal Reserve System (U.S.).
    5. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    6. John C. Robertson & Ellis W. Tallman, 1998. "Data vintages and measuring forecast model performance," Economic Review, Federal Reserve Bank of Atlanta, issue Q 4, pages 4-20.
    7. Francis X. Diebold & Glenn D. Rudebusch, 1989. "Forecasting output with the composite leading index: an ex ante analysis," Finance and Economics Discussion Series 90, Board of Governors of the Federal Reserve System (U.S.).
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    real time; forecasting; GDP;

    JEL classification:

    • E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics

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