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


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  • Kitchen, John
  • Monaco, Ralph


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.

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 21068.

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Date of creation: Oct 2003
Date of revision: Oct 2003
Publication status: Published in Business Economics 4.38(2003): pp. 10-19
Handle: RePEc:pra:mprapa:21068

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Keywords: real time; forecasting; GDP;

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  1. Dean Croushore & Tom Stark, 1999. "A real-time data set for macroeconomists," Working Papers 99-4, Federal Reserve Bank of Philadelphia.
  2. Karen E. Dynan & Douglas Elmendorf, 2001. "Do provisional estimates of output miss economic turning points?," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 2001-52, Board of Governors of the Federal Reserve System (U.S.).
  3. John C. Robertson & Ellis W. Tallman, 1998. "Data vintages and measuring forecast model performance," Economic Review, Federal Reserve Bank of Atlanta, Federal Reserve Bank of Atlanta, issue Q 4, pages 4-20.
  4. Evan F. Koenig & Sheila Dolmas & Jeremy Piger, 2000. "The use and abuse of "real-time" data in economic forecasting," Working Papers, Federal Reserve Bank of Dallas 0004, Federal Reserve Bank of Dallas.
  5. Robert Ingenito & Bharat Trehan, 1996. "Using monthly data to predict quarterly output," Economic Review, Federal Reserve Bank of San Francisco, Federal Reserve Bank of San Francisco, pages 3-11.
  6. Francis X. Diebold & Glenn D. Rudebusch, 1989. "Forecasting output with the composite leading index: an ex ante analysis," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 90, Board of Governors of the Federal Reserve System (U.S.).
  7. James H. Stock & Mark W.Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, American Economic Association, vol. 41(3), pages 788-829, September.
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