"Rubbing shoulders: Class segregation in daily activities," by Maxim Massenkoff & Nathan Wilmers, Journal of Public Economics, Volume 244, 2025, 105335, ISSN 0047-2727, https://doi.org/10.1016/j.jpubeco.2025.105335. (https://www.sciencedirect.com/science/article/pii/S0047272725000337). https://doi.org/10.1016/j.jpubeco.2025.105335.
It was found:
- Poor and especially rich Americans are isolated in their daily activities.
- Distance from home explains one-third of class segregation in activities.
- Casual restaurant chains like Olive Garden foster more class mixing than civic spaces.
- Cross-class encounters strongly predict Facebook friendships across economic lines.
The authors used location data to study cross-class encounters. Low-income and especially high-income individuals are socially isolated: they are more likely than other income groups to encounter people from their own class. Counterfactual exercises suggest this is explained largely by residential segregation and firms. Among firms, casual restaurants make the largest positive contribution to cross-class encounters through both scale and their diversity of visitors. Dollar stores and libraries isolate visitors. Our local measure of encounters is strongly associated with cross-class Facebook friendships, which have been previously shown to correlate with intergenerational mobility.
Growing research has shown that places rub off on you (Wilson, 2012, Sampson, 2012). When children move to better neighborhoods at a young age, their adult outcomes improve (Chetty et al., 2016, Chetty and Hendren, 2018), and children growing up in the presence of inventors are more likely to innovate in that area (Bell et al., 2019). The sources of these exposure effects are unclear, but one possibility is that areas that boost mobility have more opportunities for interaction, friendship, and mentorship across class lines (Chetty et al., 2022a).
This article measures opportunities for such cross-class interactions, providing the first national estimates of economic segregation in activities. It is done using intuitive metrics and geolocation data from SafeGraph, which allows for granular income proxies based on the small neighborhoods where people live. A neighborhood’s exposure to others is defined by the other people in the stores, restaurants, shops, parks, and libraries that its residents frequent.
How much do Americans of different income levels mix with one another? Who is exposed to a broad cross-section of income levels, and who is disproportionately exposed to others like themselves? It was found that the most isolated Americans are not the poor, but the rich. Households from the top 20% of neighborhoods by income are twice as likely to encounter other high-income people as would be expected by chance. The bottom 20% of neighborhoods is also isolated, but at about half the rate. Middle-income residents in the US are exposed to a more representative assortment of people. The cross-class encounters that we register in our data are also highly correlated with a measure of cross-class friendships constructed using Facebook data (Chetty et al., 2022a).
How much isolation is due to high- and low-income households frequenting different industries from others (high-end dining rather than fast food) or staying local at residentially segregated neighborhoods? In a counterfactual reweighting exercise (DiNardo et al., 1995), we find that there is only a small role for industry. High-income residents frequent different types of places - e.g., museums instead of libraries and full-service restaurants as opposed to fast food - but equating industry shares across classes would barely shift levels of isolation. On the other hand, people are most isolated when they are closest to home, and the tendency to stay close can account for around one third of the isolation we observe. This suggests that activity segregation partially reflects residential segregation. But even adjusting for distance from home, the majority of activity segregation persists.
The article next examines which specific firms contribute to socio-economic mixing and which exacerbate segregation. Some very poor-serving national chains, like discount general merchandise stores, contribute to segregation. But, consistent with the importance of distance in the reweighting analysis, so do chains that have many local branches: while residents from all income quintiles shop at CVS (the largest pharmacy chain in the U.S.), they shop at CVS stores in their own neighborhoods.
In contrast to these market segmented or highly local businesses, some chains contribute substantially to socio-economic mixing. Specifically, low-price full-service restaurants are frequented by a diverse range of residents: the rich and poor rub shoulders at Olive Garden and Applebee’s. Indeed, the most socio-economically diverse places in America are not public institutions, like schools and parks, but affordable, chain restaurants.
This study expands on recent literature that uses data from mobile phones, social networks, and financial transactions to examine economic segregation (reviewed in Appendix F), providing the first national estimates of experienced class segregation in daily activities. We focus on an intuitive measure of isolation: the share of encounters with one’s own group members, and provide the first decomposition quantifying sources of social isolation for the rich and poor. Finally, we investigate the types of locations that harbor economic integration, even down to the brand level, offering a unique level of granularity for measuring the role of specific brands in hosting economic integration.
It was found that the core concept is exposure: the chance of encountering someone in a certain group, conditional on membership in a certain group. An encounter is when someone is at a place at the same time as someone else (Athey et al., 2021). A place is typically a business establishment, but also includes entities like parks and schools. Exposure was based on the monthly aggregate visits. The high income group has a relatively lower share of visits to essential retail and a relatively higher share of visits to entertainment and full service dining.
Given the importance of national chains and firms to the isolation of high- and low-income neighborhood residents, the specific industries and chains that contribute to and offset isolation are identified. Our establishment-level data allows us to track particular chains and provides the first assessment of particular companies’ contribution to socio-economic mixing.
Class segregation appears not just where people live (Reardon and Bischoff, 2011) and work (Song et al., 2019), but also in the public and commercial places where people spend time and money. This paper establishes that residents of low- and especially high-income neighborhoods are exposed disproportionately to others like themselves.
(Image by storyset on Freepik.com.)
