Home bias in hiring: Evidence from an online labor market

Chen Liang, Yili Hong, Bin Gu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

We study the nature of home bias in online employment, wherein the employers prefer workers from their own home countries. Using a unique large-scale dataset from a major online labor market containing employers' consideration set of workers and their ultimate selection of workers, we first estimate employers' home bias in their online employment decisions. Moreover, we find that employers from countries with high traditional values, lower diversity, and smaller user base (or population size), tend to have a stronger home bias. Further, we disentangle two types of home bias, i.e., statistical and taste-based, using a quasi-natural experiment wherein the platform introduces a monitoring system to facilitate employers to easily observe workers' progress in time-based projects. After matching comparable fixed-price projects as a control group using coarsened exact matching, our difference-in-difference estimations show that the home bias in online employment is primarily driven by statistical discrimination.

Original languageEnglish (US)
Title of host publicationProceedings of the 22nd Pacific Asia Conference on Information Systems - Opportunities and Challenges for the Digitized Society
Subtitle of host publicationAre We Ready?, PACIS 2018
EditorsMotonari Tanabu, Dai Senoo
PublisherAssociation for Information Systems
ISBN (Electronic)9784902590838
StatePublished - 2018
Event22nd Pacific Asia Conference on Information Systems - Opportunities and Challenges for the Digitized Society: Are We Ready?, PACIS 2018 - Yokohama, Japan
Duration: Jun 26 2018Jun 30 2018

Publication series

NameProceedings of the 22nd Pacific Asia Conference on Information Systems - Opportunities and Challenges for the Digitized Society: Are We Ready?, PACIS 2018

Conference

Conference22nd Pacific Asia Conference on Information Systems - Opportunities and Challenges for the Digitized Society: Are We Ready?, PACIS 2018
Country/TerritoryJapan
CityYokohama
Period6/26/186/30/18

Keywords

  • Discrimination
  • Employment
  • Gig economy
  • Home bias
  • Online labor market
  • Quasi-natural experiment

ASJC Scopus subject areas

  • Information Systems

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