other jobs they might consider.

This paper makes three contributions. First, we provide causal evidence that customer discrimination lowers the measured productivity of female employees in the workplace by a meaningful margin. Studies on the impact of customer discrimination are scarce and find mixed evidence (Bar and Zussman, 2017; Combes et al., 2016; Holzer and Ihlanfeldt, 1998; Kahn and Sherer, 1988; Leonard et al., 2010; Nardinelli and Simon, 1990). Our study differs in two key ways. First, we use an experimental design to isolate customer discrimination rather than methodologies that may not fully control for differences in unobservable characteristics of workers and customers. Second, we can measure worker productivity rather than relying on wages or hiring outcomes. This provides new insights in how customer discrimination affects workers and for how tests of discrimination may be biased by assuming fixed worker productivity.<sup>7</sup> Our results also contribute to a growing literature that shows how upstream discriminatory processes can impact the final productivity measures often used for academic and policy analysis (Glover et al., 2017; Hengel, 2022; Parsons et al., 2011).

This paper is also related to a literature on how customer discrimination affects goods sellers in marketplaces or product markets through audit or correspondence-type studies (List, 2004; Doleac and Stein, 2013; Ayres et al., 2015; Kricheli-Katz and Regev, 2016).<sup>8</sup> While this literature has found more evidence of discrimination, the implications for _workers_ in the labor market remain unclear for a number of reasons. First, List (2004) and Doleac and Stein (2013) find that customers statistically discriminate against minorities in markets for secondhand baseball cards and iPod sellers because they make assumptions about the product or seller’s quality from the identity of the seller. We would not expect customers to statistically discriminate among workers who are selling the same products at the same company. This could explain why we do not find evidence of differential customer bargaining.<sup>9</sup> Second, engaging real workers at an established company means we can study customer discrimination in a real labor market setting, and we can test whether this discrimination exists among individuals who have selected into this job based on their comparative advantage.

Third, this paper documents how consumers’ preferences can create meaningful barriers to women’s success in labor markets in developing countries. Recent work documents a variety of other possible constraints: norms and bargaining dynamics within the household (Lowe and McKelway, 2021; Bursztyn et al., 2020; Dean and Jayachandran, 2019; Heath and Tan, 2020; Field et al., 2021; McKelway, 2021a,b); workplace attributes (Subramanian, 2021), safety during commutes (Borker, 2021), market demand (Hardy and Kagy, 2020), and employer discrimination (Jayachandran, 2015; Duflo, 2012; Sin et al., 2020). Most relatedly, Delecourt and Ng (2021), uses an audit-study approach to show that customers do not discriminate against female-led small business vegetable sellers in India. While similar in ob-

> 7 Nardinelli and Simon (1990) is an exception as they define productivity of baseball players to be their entertainment value which they observe through the price of baseball cards.

> 8 This paper also contributes to other literatures on bias in student evaluations of teachers (MacNell et al., 2015; Mengel et al., 2019) or by audience members for academic economists (Dupas et al., 2021).

> 9 It is also hard to compare the magnitude of our estimates to this literature. For example, List (2004) and Doleac and Stein (2013) find reductions in 3-30% and 11% in the price offered for the product to the minority seller, respectively, which is much smaller than the 51% reduction we observe in the probability a transaction occurs.

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