Social Security and High-Frequency Labor Supply: Evidence from Uber Drivers

Timothy Beatty and Joakim A. Weill
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Joakim A. Weill: https://joakimweill.github.io/

No 2024-079, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

Abstract: We estimate the impact of anticipated transfers on labor supply using confidential driver-level data from Uber. Leveraging the staggered timing of Social Security retirement benefits within each month and a novel identification strategy, we find that the labor supply of older drivers declines by 2% on average in the week around benefit receipt—a precisely estimated but economically small effect. Individual-level analyses reveal that the average effect obscures heterogeneous micro-behavior: while the majority of drivers does not meaningfully adjust labor supply in response to social security benefits, a small group reduces labor supply by more than 40%. The results suggest that departures from standard models of labor supply are meaningful but only for a small number of individuals.

Keywords: Labor supply; Retirement; Social security; Gig economy (search for similar items in EconPapers)
JEL-codes: C10 H55 J14 J18 J22 J26 (search for similar items in EconPapers)
Pages: 62 p.
Date: 2024-09-20
New Economics Papers: this item is included in nep-age, nep-lma and nep-pbe
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2024-79

DOI: 10.17016/FEDS.2024.079

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