Firm-Worker Matches: Experience or Inspection Goods?
Victoria Gregory,
Guido Menzio and
Giovanni M. Topa ()
No 2026-009, Working Papers from Federal Reserve Bank of St. Louis
Abstract:
We propose a novel empirical strategy to infer the extent to which firm-worker matches are inspection or experience goods. We argue that the informative content of the signals that firms and workers receive about the productivity of their match before entering an employment relationship can be inferred from the gaps between the separation rates of workers hired from unemployment, employment at low-tenure jobs, and employment at high-tenure jobs. We implement the strategy using German administrative data. We find that, before entering an employment relationship, a firm and a worker receive a signal that reduces the variance of their beliefs about the productivity of the match by 67%. The informative content of the signal varies according to the gender and the education of the worker, and it has increased over time. If matches were pure inspection goods, labor productivity would be 1:5% higher, and output 2% higher. If matches were pure experience goods, labor productivity would be 2% lower, and output 4% lower.
Keywords: labor markets; search frictions; information frictions; worker turnover (search for similar items in EconPapers)
JEL-codes: D83 E24 J63 J64 (search for similar items in EconPapers)
Pages: 39 pages
Date: 2026-05-14
References: Add references at CitEc
Citations:
Downloads: (external link)
https://doi.org/10.20955/wp.2026.009 Full text (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:fip:fedlwp:103248
Ordering information: This working paper can be ordered from
DOI: 10.20955/wp.2026.009
Access Statistics for this paper
More papers in Working Papers from Federal Reserve Bank of St. Louis Contact information at EDIRC.
Bibliographic data for series maintained by Scott St. Louis ().