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Gender Reveals in the Labor Market: Evidence on Gender Signaling and Statistical Discrimination in an Online Health Care Market

Author

Listed:
  • Haoran He
  • David Neumark
  • Qian Weng

Abstract

We study gender discrimination in an online health care market. Statistical discrimination implies that the impact of gender on prices should decline, and the impact of reviews increase, as reviews accumulate. However, in our context this implication does not hold, because doctors choose how strongly to signal gender. We develop a new test for the implications of statistical discrimination based on this choice. We find evidence consistent with statistical discrimination against female doctors in male-dominated fields, and vice versa. For example, female doctors mask gender more strongly initially in male-dominated fields, and the gender gap in signaling declines as reviews accumulate.

Suggested Citation

  • Haoran He & David Neumark & Qian Weng, 2024. "Gender Reveals in the Labor Market: Evidence on Gender Signaling and Statistical Discrimination in an Online Health Care Market," NBER Working Papers 32929, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:32929
    Note: EH LS
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    More about this item

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J40 - Labor and Demographic Economics - - Particular Labor Markets - - - General
    • J70 - Labor and Demographic Economics - - Labor Discrimination - - - General

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