Beauty and Professional Success: A Meta-Analysis - Kseniya Bortnikova; Tomas Havranek; Zuzana Irsova (ZBW - Leibniz Information Centre for Economics, 2024)
Common wisdom suggests that beauty helps in the labor market. We show that two factors combine to explain away the mean beauty premium reported in the literature. First, correcting for publication bias reduces the premium by at least a third. Second, controlling for cognitive ability negates the premium for all occupations except sex workers, a point further underscored by the similarity of the beauty effect on earnings and productivity. The second factor implies a positive link, perhaps genetic, between beauty and intelligence. We find little evidence of substantial attenuation bias that could offset publication and omitted-variable biases. The empirical literature is inconsistent with discrimination based solely on tastes for beauty. To obtain these results we collect 1,159 estimates of the effect of beauty on earnings or productivity reported in 67 studies and codify 33 aspects that reflect estimation context, including the potential intensity of attenuation bias. We employ recently developed techniques to account for publication bias and model uncertainty.
Keywords: C83; J24; J31; 330; Beauty premium; productivity; meta-analysis; model uncertainty; publication bias; p-hacking