The Chicago Fed Labor Market Indicators: Bridging the Gap with Alternative Labor Data

Scott Brave, Ben Henken, Ezra Karger and Aryan Safi
Additional contact information
Ben Henken: https://www.chicagofed.org/people/h/henken-ben
Ezra Karger: https://www.chicagofed.org/people/k/karger-ezra
Aryan Safi: https://www.chicagofed.org/people/s/safi-aryan

No WP 2026-09, Working Paper Series from Federal Reserve Bank of Chicago

Abstract: We present the Chicago Fed Labor Market Indicators (LMI): a twice-monthly release that includes the job-finding rate, the job-separation rate, and a forecast for the U.S. Bureau of Labor Statistics (BLS) unemployment rate. To overcome limitations in data availability, the LMI uses partial least squares to combine CPS-based finding and separation rates with higher-frequency alternative and traditional labor market data series—such as unemployment insurance claims, Google Trends searches, online job postings, and survey-based indicators. Our resulting flow-consistent unemployment rate (FCR) correlates strongly with the BLS unemployment rate, and can be used to characterize the current “low-hire, low-fire” nature of the U.S. labor market. We use a Bayesian linear regression centered on a no-change prior to translate changes in our FCR into a real-time forecast for the next BLS unemployment rate reading. In backtesting spanning 2018–2026, our unemployment rate forecast improves on both a random-walk benchmark and the Bloomberg consensus forecast, with the largest accuracy gains during the Covid-19 pandemic when the unemployment rate rose rapidly in a way that was well-captured by high-frequency labor market data.

Keywords: unemployment; Job separation; job finding; nowcast; big data; Alternative data (search for similar items in EconPapers)
JEL-codes: C01 C53 E24 E37 J64 (search for similar items in EconPapers)
Pages: 40
Date: 2026-04
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DOI: 10.21033/wp-2026-09

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