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

Daniel Cooper, Giovanni Olivei and Hannah Rhodenhiser

No 25-4, Working Papers from Federal Reserve Bank of Boston

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.

Keywords: macroeconomic forecasting; small information set; forecast accuracy (search for similar items in EconPapers)
JEL-codes: E27 E37 (search for similar items in EconPapers)
Pages: 41
Date: 2025-06-01
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedbwp:101183

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DOI: 10.29412/res.wp.2025.04

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