Do Superstar Employers Depress Labor Shares? Evidence from Counties in the United States

Do Superstar Employers Depress Labor Shares? Evidence from Counties in the United States | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Do Superstar Employers Depress Labor Shares? Evidence from Counties in the United States Christopher D. Blake This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7273134/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper investigates the relationship between the presence of ''superstar" employers--establishments with exceptionally large employment relative to sectoral peers--and labor shares at the county level across the United States. Motivated by a growing literature on the declining labor share and the rise of dominant firms, the analysis develops a novel methodology that constructs synthetic employment distributions using County Business Patterns data to identify statistical outliers within county-sector-year combinations. Fixed effects panel regressions are employed across three spatial scales (Georgia, the Southeastern region, and the nation) to assess whether either the existence or the prevalence of superstar employers is associated with changes in labor’s share of income. The findings are strikingly consistent: little evidence emerges that superstar employers reduce labor shares at the county-sector level. Where significant effects are detected, they are typically positive, particularly in service sectors. Robustness checks confirm these results across alternative definitions and specifications. These findings challenge prevailing assumptions that attracting or retaining large employers necessarily leads to declining worker income shares at the regional scale. Policy implications and considerations for the measurement of labor market concentration in local contexts are discussed. The approach demonstrates the utility of combining public establishment-size data with outlier detection to study monopsony and labor market power in settings where detailed firm-level data are unavailable. Overall, the results suggest that concerns about the effect of large-scale employers affecting the local distribution of income are unfounded. JEL Classification: J31 , R11 , R50 Superstar Employers Monopsony Labor Shares Statistical Outliers Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7273134","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":503155485,"identity":"0e84836c-6510-4bf9-b5c4-fb15a726f274","order_by":0,"name":"Christopher D. 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