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Home Bias in Global Employment

Author

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  • Chen Liang

    () (Department of Information Systems, W.P. Carey School of Business, Arizona State University, USA)

  • Yili Hong

    () (Department of Information Systems, W.P. Carey School of Business, Arizona State University, USA)

  • Bin Gu

    () (Department of Information Systems, W.P. Carey School of Business, Arizona State University, USA)

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 platform, we identify employers’ home bias in their online employment decisions. Moreover, we find that employers from countries with high traditional values, lower diversity, and smaller (user) population size, tend to have a stronger home bias. Further, we investigate the nature of employers’ home bias using a quasi-natural experiment wherein the platform introduces a monitoring system to facilitate employers to keep track of workers’ progress in time-based projects. After matching comparable fixed-price projects as a control group using propensity score matching, our difference-in-difference estimations show that the home bias does exist in online employment, and at least 40.93% of home bias is driven by statistical discrimination.

Suggested Citation

  • Chen Liang & Yili Hong & Bin Gu, 2017. "Home Bias in Global Employment," Working Papers 17-06, NET Institute.
  • Handle: RePEc:net:wpaper:1706
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    More about this item

    Keywords

    home bias; global employment; statistical discrimination; taste-based discrimination; quasi-natural experiment; Gig economy;

    JEL classification:

    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • J78 - Labor and Demographic Economics - - Labor Discrimination - - - Public Policy (including comparable worth)
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J82 - Labor and Demographic Economics - - Labor Standards - - - Labor Force Composition

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