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Forecasting U.S. Economic Activity with a Small Information Set

Author

Listed:
  • Daniel H. Cooper
  • Giovanni P. Olivei
  • Hannah Rhodenhiser

Abstract

We provide a parsimonious setup for forecasting U.S. GDP growth and the unemployment rate based on a few fundamental drivers. This setup yields forecasts that are reasonably accurate compared with private-sector and Federal Reserve forecasts over the 1984–2019 and post COVID-19 pandemic periods. This result is achieved by jointly estimating the processes for GDP growth and the unemployment rate, with the constraint that GDP and unemployment follow Okun’s law in first differences. This setup can be easily extended to replace the variables in the information set with factors that might better capture the underlying fundamentals.

Suggested Citation

  • Daniel H. Cooper & Giovanni P. Olivei & Hannah Rhodenhiser, 2025. "Forecasting U.S. Economic Activity with a Small Information Set," Working Papers 25-4, Federal Reserve Bank of Boston.
    • Handle: RePEc:fip:fedbwp:101183
    DOI: 10.29412/res.wp.2025.04
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    More about this item

    Keywords

    macroeconomic forecasting; small information set; forecast accuracy;
    All these keywords.

    JEL classification:

    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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