The Cost of Gendered Attitudes on a Female Candidate: Evidence from Google Trends

Raphael Corbi () and Pedro Picchetti ()

No 2020_08, Working Papers, Department of Economics from University of São Paulo (FEA-USP)

Abstract: How much can negative attitudes towards women affect voting for a female candidate on a major election? We measure gender animus by calculating a proxy based on Google search queries that include gender-charged language. Such approach likely elicits socially sensitive attitudes by limiting the concern of social censoring, circumventing usual difficulties associated with survey-based measurements. We compare the proxy to Hillary Clinton’s vote share in the presidential election of 2016, controlling for the vote share of the previous Democratic presidential candidate, Barack Obama. Our results indicate that a one standard deviation increase in our proxy is associated with a 2 percentage points relative loss for Hillary and suggest that online-based observable behavior can be useful for measuring different kinds of hard-to-measure social attitudes.

Keywords: Gender; Discrimination; Election; Google (search for similar items in EconPapers)
JEL-codes: D72 J16 J7 (search for similar items in EconPapers)
Date: 2020-06-19
New Economics Papers: this item is included in nep-gen and nep-pol
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Citations: View citations in EconPapers (7)

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Journal Article: The cost of gendered attitudes on a female candidate: Evidence from Google Trends (2020)
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