A closer look at neighborhood data

By PHS 795 Student Grace Shea:

This project, called “The Equality of Opportunity Project,” was started by a Harvard grad and economist, Raj Chetty, who was interested in studying the effects of socio-ecological factors on a person’s long-term trajectory. This website shows much of the research that has been done by him and his staff using “Big Data” to analyze some of the financial and health outcomes associated with one’s neighborhood. This project was also featured on one of the Freakonomics Radio podcasts sessions, which you can find on the website. Primarily, I think this website can serve as a huge resource for many in the Public Health field because they provide all of their data to the public including lecture videos from a similar class that Dr. Chetty taught. The lectures are available via Youtube with links on the website.


In this link, you can scroll to the Local Area Rankings for Commuting Zones (Counties is also an option). The list provided shows the commuting (primarily urban) centers where your adult income is estimated based on where you live as a child if you are in the bottom 25th percentile for family income. Essentially, this data attempts to predict the causal effects of where you live if you are in a low-income family. Capture

If you look at the list provided, Seattle is at the top of the list. To understand this list, let’s use Seattle as an example. If a child were to grow up in the Seattle metro area instead of an average place, he/she would make about 12% more at age 26. The average level of household income at age 26 is $26,000, so this 12% gain translates to $3,120 of additional income.

If you look a bit further down, Madison is on that list. All kids in Madison have a 7.4% chance of making more as adults with boys at 10.4% and girls at 3.9%. My question to the class is why do we think we see such a significant gender gap for adult income for children in Madison. Additionally, do we think that a 7.4% increase in income is meaningful for predicting their long-term outcomes? How does this compare to the bottom of the list where in Fayetteville, NC, children have a -17.8% chance of making more money as an adult than their family’s current income? Can we use this data to predict where future public health efforts will be needed?


2 thoughts on “A closer look at neighborhood data

  1. Thanks for mentioning this was on Freakonomics…otherwise it would’ve bugged me a little bit not knowing where I had heard of Raj Chetty and this project before!

    The gender gap in Madison looks like a gulf to me and is quite troubling. Perhaps it is because of that “cultural, institutional” layer surrounding an individual like we talked about yesterday using Scott and opioids. Culturally, boys are encouraged into higher paying professions like computer science and engineering while girls are guided towards nurturing roles like teaching and caring for family members (unpaid work). Since their jobs are more likely to be of lesser income, women are often the default family members to give up their careers to go into unpaid work in the first place. Perhaps this can explain some of the gap, but it is such a divide I hope others can comment with other ideas as to why this exists in Madison.

    As for using this data in a public health realm, I think it is certainly feasible for a state or county health department to look at where disparities are greatest and predict where resources may be best allocated. Adults in communities like Fayetteville NC are probably going to need more social support programs than adults in nearby Raleigh-Durham, NC, for example, so if a department had jurisdiction over both those entities this metric may help. I’d expect this map to track fairly well with other indicators we’ve talked about in class so far such as unemployment, opioid overdoses, obesity, etc.


  2. I think Kelsey made a good point that men are encouraged and more men go into computer science type jobs more often. And near Madison is Epic, which is heavily fits into the category of jobs that men gravitate towards, and Epic pays pretty good. So in part I think that the jobs that are available here in Madison are jobs and companies that are stereotypically males, like Epic and Covance.
    I do think that this data can be impactful if used correctly. Agencies can look to see where the disparities lie and try to create programs and initiatives that lower the gap.


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