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A simple way to estimate current-quarter GNP

Author

Listed:
  • Terry J. Fitzgerald
  • Preston J. Miller

Abstract

This paper describes a method developed to predict the advance (first) estimate of inflation-adjusted gross national product (real GNP) using hours-worked data. Besides generating fairly accurate forecasts of advance GNP, the method has two implications. First, the Commerce Department seems to weigh the hours-worked data most heavily in its early estimates of real GNP but less and less so in its revised estimates. Second, analysts attempting to predict current-quarter outcomes in real time need to consider the availability and reliability of data at the time the forecasts are made.

Suggested Citation

  • Terry J. Fitzgerald & Preston J. Miller, 1989. "A simple way to estimate current-quarter GNP," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 13(Fall), pages 27-31.
    • Handle: RePEc:fip:fedmqr:y:1989:i:fall:p:27-31:n:v.13no.4
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    Citations

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    Cited by:

    1. Peter A. Zadrozny, 1990. "Estimating A Multivariate Arma Model with Mixed-Frequency Data: An Application to Forecasting U.S. GNP at Monthly Intervals," Working Papers 90-5, Center for Economic Studies, U.S. Census Bureau.
    2. Jonas E. Arias & Minchul Shin, 2020. "Tracking U.S. Real GDP Growth During the Pandemic," Economic Insights, Federal Reserve Bank of Philadelphia, vol. 5(3), pages 9-14, September.
    3. 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.
    4. Tom Stark, 2000. "Does current-quarter information improve quarterly forecasts for the U.S. economy?," Working Papers 00-2, Federal Reserve Bank of Philadelphia.
    5. Klaus Wohlrabe, 2009. "Makroökonomische Prognosen mit gemischten Frequenzen," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(21), pages 22-33, November.

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