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Sexism, household decisions, and the gender wage gap

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  • Owen, Ann L.
  • Wei, Andrew

Abstract

We develop an index of local sexism for the United States using publicly available Google Trends data. We shed light on the correlates of local sexism and find that the most important factors that predict it are the economic outcomes of men. Finally, we show that online sexism is associated with higher levels of the residual gender wage gap, the wage gap after controlling for education, occupation, industry, and age. We find evidence for a direct association of sexism with the wage gap, consistent with labor market discrimination and an indirect association that works through household decisions which themselves are associated with wages.

Suggested Citation

  • Owen, Ann L. & Wei, Andrew, 2021. "Sexism, household decisions, and the gender wage gap," Labour Economics, Elsevier, vol. 72(C).
    • Handle: RePEc:eee:labeco:v:72:y:2021:i:c:s092753712100097x
    DOI: 10.1016/j.labeco.2021.102062
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    Cited by:

    1. Gutiérrez, Antonio, 2023. "La brecha de género en el emprendimiento y la cultura emprendedora: Evidencia con Google Trends [Entrepreneurship gender gap and entrepreneurial culture: Evidence from Google Trends]," MPRA Paper 115876, University Library of Munich, Germany.
    2. Ann L. Owen & Andrew Wei, 2024. "Hostile Sexism and the 2016 Presidential Election," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 50(3), pages 238-258, June.
    3. Kuhn, Andreas, 2022. "The Times Have Changed: Tracking the Evolution of Gender Norms over Time," IZA Discussion Papers 15621, IZA Network @ LISER.
    4. Eleni Yitbarek & Nicky Nicholls & Michelle Pleace, 2025. "Do opinions on fair salaries vary with gender in South Africa?," ERSA Working Paper Series, Economic Research Southern Africa, vol. 0.
    5. Emily Y. Lin & Joel Slemrod & Evelyn Smith & Alexander Yuskavage, 2025. "Who’s on (the 1040) first? Determinants and consequences of spouses’ name order on joint returns," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 32(4), pages 957-994, August.
    6. Gutiérrez, Antonio, 2022. "Movilidad urbana y datos de alta frecuencia [Urban mobility and high frequency data]," MPRA Paper 114854, University Library of Munich, Germany.
    7. Ann Owen & Andrew Wei, 2022. "Tweets, sexism, and the 2016 presidential election," Economics Bulletin, AccessEcon, vol. 42(1), pages 244-254.

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    Keywords

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    JEL classification:

    • J10 - Labor and Demographic Economics - - Demographic Economics - - - General
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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