Gender Reveals in the Labor Market: Evidence on Gender Signaling and Statistical Discrimination in an Online Health Care Market
Working Paper 32929
DOI 10.3386/w32929
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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.
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Copy CitationHaoran He, David Neumark, and Qian Weng, "Gender Reveals in the Labor Market: Evidence on Gender Signaling and Statistical Discrimination in an Online Health Care Market," NBER Working Paper 32929 (2024), https://doi.org/10.3386/w32929.Download Citation
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