Stanford Professors Use GPS Data to Measure Racial Segregation

– both quotes from “How Segregated Are We? Stanford Researchers Examine Exposure to Racial Diversity,” Stanford News

Stanford economists Susan Athey and Matthew Gentzkow introduce a new method for measuring racial segregation. They analyze “experienced segregation” – the amount of exposure people have to other races as they go about their daily lives. While a common basis for determining segregation has been to focus on where people live, Professors Athey and Gentzkow compiled GPS data from smartphones to analyze movement patterns.

In a conversation with Stanford News, Professor Gentzkow explained the value of analyzing peoples’ experience of segregation across all aspects of their lives:

“Until now, we’ve calculated how segregated neighborhoods are, or how segregated schools or workplaces are, but those are coarse approximations to what we might also care about, which is how segregated people’s experiences are in all of the different places they are at – home, work, school, shopping, the movies, walking down the street, going to a park and so on,” said Gentzkow, who is a professor of economics in the School of Humanities and Sciences.

“Our study tries to measure that more directly using GPS data,” he said. “It gives us a picture of which activities and which places are pulling towards segregation and away from segregation.”

In their paper, “Experienced Segregation,” co-written with Tobias Schmidt, formerly with the Stanford Institute for Economic Policy Research (SIEPR) and Billy Ferguson, a graduate student at the Stanford Graduate School of Business, Professors Athey and Gentzkow found that across most metropolitan areas of the United States, people’s actual experiences, as captured by the new measure, are substantially less segregated than what residential segregation measures might indicate.

The Stanford News article, “How Segregated Are We? Stanford Researchers Examine Exposure to Racial Diversity,” summarizes how the researchers acquired and analyzed the GPS data:

The researchers examined aggregated anonymous GPS signal data from a sample of more than 17 million smartphones from January to April in 2017, representing about 5 percent of the U.S. population across 366 metropolitan areas.

To compute experienced isolation, they analyzed the movement patterns of those devices by looking at the GPS pings logged from a range smartphone apps, down to every 500 square feet – or roughly, a city-block radius – throughout the course of a day.

The researchers did not directly know the race of the smartphone users, so they relied instead on the home locations of each device and census data to designate the race as white or non-white.

The device’s whereabouts were matched against a dataset the researchers compiled of tens of millions of establishments and public points of interest across the U.S.

The “Experienced Segregation” study shows that people spend a lot of time outside their neighborhoods. And when they do, they’re more likely to encounter greater diversity than they find at home. Racial integration, the researchers found, is highest at entertainment, retail, and eating establishments, while time spent at locations like churches and schools is somewhat more racially isolated.

Below are a few excerpts from “Experienced Segregation” by Susan Athey, Matthew Gentzkow, Tobias Schmidt, and Billy Ferguson:

Key Findings

We find that the isolation people actually experience is substantially lower than residential measures would suggest. People spend substantial time away from their home neighborhoods, and when they do they are much more likely to encounter diverse others than they would at home. Commercial places like restaurants and retail shops are a particularly strong force pulling against segregation, while local amenities such as churches and schools tend to remain more segregated. One implication is that public goods that are tied to residential boundaries should be a particular focus of efforts to combat segregation. They also suggest that the negative effects of segregation are likely higher for those like children and the elderly whose exposure is more tied to their local neighborhoods.

Broader Implications of the Findings

These findings have several broader implications. They suggest that standard measures overstate the overall extent of segregation in the United States, and they highlight important forces such as commercial activity that reduce it. They suggest that residential measures may nevertheless be a good proxy when the main goal is to assess relative levels of segregation across cities. Finally, they suggest a more nuanced view of where the negative effects of segregation are likely to be largest. For example, local public goods such as schools or police services that are explicitly tied to residential boundaries are more likely to be provided in segregated environments. Any negative effects of segregation are likely higher for children and those who do not work, and others whose exposure is more tied to their local neighborhoods. Policies which affect the spatial distribution of commercial or leisure activities, or the transportation cost of accessing these activities, may be as or more effective than policies explicitly targeting housing.

• “Experienced Segregation” by Susan Athey, Matthew Gentzkow, Billy A. Ferguson, and Tobias Schmidt (NBER Working Paper No. 27572, July 2020)
• “How Segregated Are We? Stanford Researchers Examine Exposure to Racial Diversity” (Stanford News, August 3, 2020)