Labor market peer firms: understanding firms’ labor market linkages through employees’ internet “also viewed” firms

Nan Li ()
Additional contact information
Nan Li: University of Toronto

Review of Accounting Studies, 2025, vol. 30, issue 1, No 11, 384-435

Abstract: Abstract This paper studies the grouping of firms based on their labor-market connections, a significant departure from the traditional approach of grouping based on product-market connections. It also proposes a measure of labor market peers by analyzing the “also viewed” companies on two major online labor market platforms, LinkedIn and Glassdoor. Using the labor market peer measure, I examine whether firms that hire employees with similar skills and that are presumably exposed to the same labor-related risks and shocks exhibit a strong comovement of stock returns and accounting-based performance variables. I find that labor market peers overlap but differ from traditional product-market-based industry groupings, have significant incremental power to explain stock return and accounting-based performance measure comovements, and outperform traditional industry groupings in explaining return and wage comovements when a base firm shares more labor skills with its peers. Overall, the study highlights that labor market peers capture fundamental linkages between firms that are challenging to identify using traditional industry measures.

Keywords: Peer firms; Labor market; Industry classification; Online search; LinkedIn; Glassdoor; Benchmarking (search for similar items in EconPapers)
JEL-codes: D83 G0 J01 M2 (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11142-024-09821-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:reaccs:v:30:y:2025:i:1:d:10.1007_s11142-024-09821-z

Ordering information: This journal article can be ordered from
http://www.springer.com/accounting/journal/11142

DOI: 10.1007/s11142-024-09821-z

Access Statistics for this article

Review of Accounting Studies is currently edited by Paul Fischer

More articles in Review of Accounting Studies from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().