The piece highlight’s Esteban’s research on income segregation by neighborhood using used aggregated anonymous location data from mobile phones to estimate the distribution of time that different income groups spend in different venues. This allowed him and his team to identify the regions in America where the rich and poor hardly ever interact.
In the article you can see how NYC and Boston compare on income segregation, and also dig into specific places. For example, check cashing and pawn shops have high income segregation, while science museums and sports stadiums have low income segregation.
Special thanks to @Niki_Kaz and@Karissa_from_SafeGraph for introducing us in this Dewey community. Esteban and I may never have met and gotten the chance to work on this piece if it weren’t for this group!
This is FASCINATING research! And love to see the collaboration - I knew your platform was a great match with what @Esteban_Moro_MIT and his team were looking into. Thank you for you and your team’s work, Esteban.
Love seeing Community members come together on projects like these! I had previously read @Esteban_Moro_MIT ’s paper but enjoyed the little anecdotes that were exclusive to this guest post. For example, I never knew about the idea of “poor doors”, address differentiation, and similar tactics to stratify people from different incomes.
I’m also a little surprised that most major US cities have almost identical income segregation. Have you been able to look at this across different countries? I’m wondering if countries, like Japan, that have a very robust public transit system allows for less inequality relative to the US. My thinking is that if people are more interconnected via public transit they have a wider variety of the places they can visit and aren’t confined to a single location. Generally, I think public transit is also a little more within financial reach than the large expense of owning and operating a car.
Hey @Sam_Dennis_Jr_UW-Madison - have you looked at this piece by Esteban and Jeremy? I know your background is in environmental design but with more of an angle on human health and well-being. Wondering if you’ve ever considered income inequality when it comes to your environmental design work?
@Angela_Rout_UBC I think you might have already interacted with this team, but thought I’d flag again since your work looks at the design of physical spaces. Would be interesting to see how similar analyses could be done looking at parks in Canada!
Hey all! Yes I would love to connect! @Jeremy_Ney and @Esteban_Moro_MIT This is a great article and a really nice way to get work out to different audiences. We are doing a study to explore equity in use of urban parks in the Pacific Northwest, especially in extremely hot weather, I think there is a lot of interesting overlap for sure!
fantastic work! i really enjoyed reading it and definitely got inspired by it! Thanks to all the authors for the amazing work. I’m trying to use mobility data to study the effect of income inequality. but most papers that use safegraph data seem to be covid-related. will be really appreciated it if anyone could recommend similar work like this one! Thank you!