Abstract
Employees who receive part of their compensation as tips may be subject to a type of discrimination that is not regulated or prohibited. This discrimination affects not only earnings, but employment. In many US states, employers are able to pay a reduced minimum wage to employees who receive regular tips, as long as the tips are sufficient to bring earnings to the standard minimum wage. Employers therefore have a financial incentive to hire and retain only those workers who are expected to receive adequate tips. Although case study surveys of customers and tipped employees suggest that discrimination in tipping exists and may lead to discrimination in hiring, no large-scale empirical analysis has been undertaken on this topic. In this paper, we identify patterns of gender and racial employment across US states that are linked to the gap between the standard minimum wage and the sub-minimum wage. Importantly, our analysis suggests that white women benefit from consumer discrimination in tipping. In contrast, there is evidence of employer discrimination against minority men and women, most robustly for Black men and women, with regional variation for other groups.
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Notes
It is worth noting that an often-cited source for the under-reporting of tips in the USA is IRS (1990) which indicates that less than half of tipped income is reported for tax purposes. For theoretical work on the factors that may influence under-reporting of tips, see Anderson and Bodvarsson (2005).
Data limitations require a binary men/women distinction in gender.
We reluctantly use the term “quality” throughout the theory and empirical work to capture all characteristics that may affect that wages that a person might earn in other (i.e. skilled) occupations as this is common in the labour economics literature.
In many restaurants, tipped employees are required to share a portion of their tips with back of house staff. As long as this proportion is not 100%, the model still holds with minor adjustments to notation.
Even and MacPherson (2014) find that an increase in the tipped minimum wage, holding minimum wage constant, leads to an increase in income for tipped employees. In contrast, Anderson and Bodvarsson (2005a) find no impact on reported income when the gap between the minimum wages is reduced. Lynn (2020) finds that while a cross-section comparison of states yields a negative relationship between tip size and the tipped minimum wage, this correlation is not robust in panel data. As well, Lynn (2022), using a survey of Amazon.Com MTurk workers, tests for whether state differences in the gap between the minimum wage and tipped-minimum wage are associated with differences in tipping and finds that individuals from states with a larger gap self-report higher levels of tipping. Jones (2016) relies on W2 data, linked with survey responses, and shows that reported tip income falls as the tipped minimum wage increases. However, self-reports of tip income are unreliable. Moreover, as pointed out by a referee, many employers require employees only to report sufficient tip amounts to cover the tip credit. As the tip credit falls (i.e. tipped minimum wage increases), the reporting burden also declines.
This assumption could be relaxed. In this strict form, this implies that all utility gain that consumers receive from being served by their preferred type is transferred to the employee through the tip. The consumer is indifferent between being served by a worker of type A and paying a high tip and being served by a worker of type B and paying a lower tip. We could relax this to allow the consumer to retain some of the added utility of being served by a waiter of their preferred type. In this less strict form, employers would be even more likely to react to consumer preferences since worker type would also impact sales volume.
More recent years of the ACS were not included to avoid issues surrounding sub-state level minimum wages which have become more popular in recent years. (See https://laborcenter.berkeley.edu/inventory-of-us-city-and-county-minimum-wage-ordinances/ for more information)
Regressions were run on the larger categories of tipped and “like-tipped” occupations. Results are qualitatively similar, but less precise as would be expected with more diverse categories.
North includes PA, NH, ME, NJ, NY, RI, VT, CT and MA. Midwest includes IN, KS, WI, IO, ND, MO, OH, IL, MI, SD, NE and MN. South includes AL, KT, LA, MS, NC, OK, SC, TN, TX, VI, GA, AR, FL, DE, WV, MD and DC. West includes UT, WY, ID, NM, AZ, MT, NV, CO, HI, WA, AK, OR and CA.
Individual characteristics included in each regression are age group, head/spouse indicator, education completion level, current student, strong English skills, immigrant group, marital status, metro group, race and gender. State-level variables included are standard minimum wage and the gap between the minimum wage and the tipped minimum wage, the percent of the working age population who are Black, Hispanic, Other Race, Recent immigrant (< 10 years), long-term immigrant (> 10 years), strong in English skills, unemployed and not in the labour force. State-level characteristics include the proportion of the working age (16–54) population in the state who are black, Hispanic, other race, recent migrants, long-term migrants, speak English well, are unemployed and are not in the labour force. Also included are the state average hours worked, average total income and the size of the tipped and like-tipped workforce relative to the population.
Results from linear probability models yield consistent results.
More diverse categories of sex and gender are not available in the ACS data.
Black Hispanics are coded as Black. Other race is included as a control variable separate from the base category of non-Hispanic white. However, as this is a diverse group and discrimination is likely to vary within the group, we do not discuss the results for this category.
Full regression results are available on request. All regressions include the full set of controls. Coefficients are presented as odds ratios.
This is a necessary but not sufficient condition. For example, it may be that women are over-represented in tipped occupations due to gender preferences for tipped employment. The changes in employment when the tipped employment becomes less desirable are more informative to distinguish discrimination.
The age coefficients are difficult to interpret, as we suspect that age may be correlated with quality (i.e. ability to obtain a non-entry level position) but is also likely to be a characteristic that is unequally tipped.
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Acknowledgements
We would like to thank seminar participants at Grand Valley State University, Lakehead University, the University of British Columbia Okanagan, the University of Manitoba, and the University of Victoria for helpful suggestions and feedback. We also would like to thank the editor Gary Hoover, and two anonymous referees, for their excellent comments which improved the overall quality of the paper.
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JC performed the data and empirical work and prepared the tables and figures. JC and RC wrote the main manuscript text. All authors reviewed the manuscript.
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Compton, J., Compton, R.A. Disentangling Customer and Employer Discrimination Using State Variation in the Tipped Minimum Wage. J Econ Race Policy (2024). https://doi.org/10.1007/s41996-023-00134-y
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DOI: https://doi.org/10.1007/s41996-023-00134-y