“Psychological Ghetto Tax”: The Poor Pay More to Avoid Discrimination

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Seven out of ten people face an increase in inequality (United Nations 2020), and the COVID-19 pandemic exacerbated this by increasing inequality in two forms: between and within countries (The Economist 2022). As such, lowering inequality is classified as one of the United Nations Sustainable Development Goals (#10), conceived to reduce inequalities and discrimination worldwide (The Global Goals 2023). But how exactly does inequality and its resulting discrimination actually affect people? Can inequality and discrimination hinder everyday consumption decisions? If so, what can be done about it?

A recent Journal of Marketing Research article by Jorge Jacob, Yan Vietes, Rafael Goldszmidt, and Eduardo B. Andrade explored how anticipation of socioeconomic-status (SES)-based discrimination affects the price sensitivity of poor, but not rich, consumers. Although low-SES consumers tend to be more price-sensitive—and for good reason—results from five studies reveal that low-SES (vs. high-SES) consumers are willing to pay more and even accept low-value rewards to avoid more affluent commercial settings such as upscale retail stores. The authors document that this self-defeating behavior occurs because these consumers anticipate greater discrimination in upscale commercial settings. The authors refer to this as a “psychological ghetto tax,” a version of the well-documented “ghetto tax” phenomenon in which lower-income individuals end up paying more due to mobility costs, lack of information, location, and other factors.

Although low–socioeconomic status (SES) consumers tend to be more price-sensitive, results from five studies reveal that low-SES consumers are willing to pay more and even accept low-value rewards to avoid more affluent commercial settings such as upscale retail stores.

Acknowledging the relevance of this topic for a wide range of stakeholders (e.g., consumers, companies, and public policy makers), we reached out to the authors for some behind-the-scenes insights into the research process and their perspectives on the topic.

Q: How did you develop the overall idea for the project? Was the initial inspiration to determine the cause of suboptimal financial decisions among the poor, understand downstream consequences of perceived low SES stigma, or something completely different?

A: (This response is on a more personal note by the first author Jorge Jacob)

I lived in a neighborhood with extreme social inequality during my childhood. I noticed that my lower-income friends frequented malls and stores in higher-income neighborhoods less frequently than our wealthier colleagues. Even when the transportation price to go from one point to another in our neighborhood was the same as traveling outside our neighborhood. I noticed that they often paid more for a sporting item than they would pay at a retail store in another neighborhood. A few years later, I was working in a large telecom company with over 70 million customers. There was a vast majority of low-income and a minority of high-income customers, as in any unequal country. The company built stores in higher-income neighborhoods, targeting high-income customers. The stores were more upscale, more comfortable, and more quickly solved customers’ problems than those that targeted low-income clients. Although targeting high-income customers, any customer could attend these stores regardless of income. It caught my attention that, although many low-income customers frequented regions with these high-quality stores, usually for work, they rarely entered one of these stores.

The final insight for the hypothesis of this study came in the first month of my PhD when I attended a lecture by a professional born in Favela da Mare, currently a professor and manager of one of the most important NGOs in the region. In an informal part of his speech, he commented that his son wouldn’t have the courage to enter a store in a mall in a wealthy city neighborhood to search for better prices and often ended up paying more for the same item at a store in his neighborhood. He attributed this to a fear of slanted eyes and income discrimination. My advisors, Eduardo Andrade and Rafael Goldzmidt, and my PhD colleague Yan Vieites agreed to investigate whether this phenomenon affected a significant number of low-income consumers.

Q: What challenges did you face when conducting this research? In what aspects was conducting research with low-SES consumers different? Are there any tips (and/or pitfalls) for researchers and managers on how to approach this consumer segment?

A: One of this project’s main challenges was to carry out a study with procedures that are accurate to the reality of consumers who might not be from the same social group as the researchers. A second major difficulty was recruiting participants in regions where many would not have easy access to computers or the internet. For these two difficulties, we counted on the support of local NGOs throughout the project since its beginning. We also had local residents joining the project as research assistants. Their participation enriched the project intellectually and helped us deal with the logistics, such as working with people who could recruit residents of the regions where our study took place. At all times, we maintained contact with local NGOs and with local research assistants who participated in the execution and elaboration of the project. For this reason, I believe that our main tip for researchers is that they rely as much as possible on the continuous participation in the project of people close to the studied population, especially when researchers do not belong to the same social group as their sample.

Q: You identify that the “psychological ghetto tax” prevents low-SES consumers from exerting price sensitivity. How would you explain the “psychological ghetto tax” for practitioners and in what other contexts do you think it could impact this consumer segment?

A: “Ghetto tax” is a term already well-known by scientists and many practitioners that shows the cost of being poor. Some studies in the United States show that higher prices are prevalent in some low-income neighborhoods due to the lack of competition and the prevalence of corner stores. One study also shows that people with access to a car would have more access to affordable goods and services elsewhere, while those without a car would deal with the higher local prices. Our study reveals that low-income consumers also have a psychological cost of being poor. While their lack of transportation makes them less likely to search for cheaper options in other areas of the city, we show that the expectations of prejudice in more upscale neighborhoods or stores may also operate in the same direction. This psychological ghetto tax is thus the consequence of low-income consumers’ expected discrimination in commercial settings with intergroup contact.

Q: Were you surprised that the anti-discriminatory inclusion statement in the study was the least successful intervention in mitigating the psychological ghetto tax? Does this point to a broader problem that decision makers communicate inclusivity ineffectively?

A: It was not a big surprise for us that the anti-discriminatory inclusion statement was the least successful intervention. We knew from previous research that, sometimes, diversity interventions may backfire by making the discriminated social identities and other related aspects more salient. For that reason, we guess that as this intervention blatantly highlights a reality shared by many stigmatized customers and proposes a series of measures to address discrimination, the anti-discriminatory practices statement may also have made such negative experiences overly salient to low-SES consumers. Along these lines, we think policymakers and companies should be cautious and identify whether diversity interventions make the threat of prejudice more salient instead of mitigating this fear.

Q: While you acknowledge that high population density and extreme economic disparities are common characteristics of megacities, what are other aspects that can strengthen or weaken the generalizability of the results to other countries? For example, would the results be insightful for companies from other parts of the globe (e.g., North America, Europe)?

A: We are pretty confident that results may hold for any country with high socioeconomic inequality and strong intergroup relations, like most U.S. cities or any large city worldwide. We think that some characteristics of cities and stores can increase or reduce this effect. For instance, this effect may be higher in cities like Rio de Janeiro, where wealthy and humble consumers live very close to each other. However, we guess that in stores in wealthy areas with diverse staff (e.g., with members of different socioeconomic backgrounds and races), we should expect this effect to be lower.

Q: If you were to be given the power to do so, what is one policy you’d like to implement to help low-SES customers make better marketplace decisions?

A: We would not say that low-income consumers make worse decisions. We think they just tend to make decisions less psychologically painful. However, we think that constant diversity training for all the employees of the companies may help mitigate discriminatory behavior harming low-income consumers. Along with that, policies capable of reducing income inequality may be capable of avoiding the psychological ghetto tax in the long term.