Arbeitspapier

Do Workers Discriminate against Their Out-group Employers? Evidence from the Gig Economy

We study possible worker-to-employer discrimination manifested via social preferences in an online labor market. Specifically, we ask, do workers exhibit positive social preferences for an out-race employer relative to an otherwise-identical, own-race one? We run a well-powered, model-based experiment wherein we recruit 6,000 workers from Amazon's M-Turk platform for a real-effort task and randomly (and unobtrusively) reveal to them the racial identity of their non-fictitious employer. Strikingly, we find strong evidence of race-based altruism – white workers, even when they do not benefit personally, work relatively harder to generate more income for black employers. Self-declared white Republicans and Independents exhibit significantly more altruism relative to Democrats. Notably, the altruism does not seem to be driven by race-specific beliefs about the income status of the employers. Our results suggest the possibility that pro-social behavior of whites toward blacks, atypical in traditional labor markets, may emerge in the gig economy where associative (dis)taste is naturally muted due to limited social contact.

Sprache
Englisch

Erschienen in
Series: IZA Discussion Papers ; No. 13012

Klassifikation
Wirtschaft
Labor Discrimination
Micro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making‡
Field Experiments
Thema
discrimination
worker-to-employer
social preferences
taste-based discrimination
Gig Economy
mechanical turk
Structural Behavioral Economics

Ereignis
Geistige Schöpfung
(wer)
Asad, Sher Afghan
Banerjee, Ritwik
Bhattacharya, Joydeep
Ereignis
Veröffentlichung
(wer)
Institute of Labor Economics (IZA)
(wo)
Bonn
(wann)
2020

Handle
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Asad, Sher Afghan
  • Banerjee, Ritwik
  • Bhattacharya, Joydeep
  • Institute of Labor Economics (IZA)

Entstanden

  • 2020

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