Live Blog: Urban’s First “Research-A-Thon” Explores Public Housing and Proximity to Jobs
At fact-finding organizations like the Urban Institute, research projects may take months, sometimes years, to produce and publish. But what would it take to dramatically accelerate that process, and what could we learn from doing so?
Today, Urban’s researchers are exploring those questions as they embark on the first-ever “Research-A-Thon.” Over the course of one day, a team of researchers and communications professionals will analyze data, organize findings in written and visual formats, and package it all together for the public.
After brainstorming, the research team from Urban’s Metropolitan Housing and Communities Policy Center decided to focus their efforts on public housing assistance and low-wage workers. When the Research-A-Thon concludes, the researchers hope to better understand the role of housing assistance in helping low-wage workers live closer to jobs and opportunity.
11:45 AM, 12/16/2019
A quick update: the Research-A-Thon team completed their brief on December 10, but it needs to go through additional code checks and quality assessments before it’s ready for publishing. You can read the full findings—with a few changes from those reported here—in early January 2020.
5:00 PM, 12/10/19
After hours of writing, coding, mapping, and snacking, the research team is now pulling everything together for their final publication (title TBD) that will be published either tonight or early tomorrow.
Before signing off, I spoke with Institute associate Nancy Pindus about the policy landscape surrounding assisted housing and spatial mismatch in the labor market.
“We’re thinking about this problem in terms of spatial issues and structural issues,” she explained. “Spatial issues obviously involve the distance between jobs and where people live, while structural issues involve other barriers to work that need to be addressed.”
On the spatial side:
“The US Department of Housing and Urban Development and local public housing agencies can look for opportunities to locate new housing in areas with a surplus of jobs. They can also help residents reach those jobs by providing shuttle buses, for instance.”
“They can also identify private landlords in areas with jobs available and encourage them to accept vouchers.”
On the structural side:
“We need to think about the amenities that encourage people to move or live there, like schools or grocery stores, or antidiscrimination laws and how they are enforced. We should also strengthen employers’ partnerships with public housing: letting workers know about jobs, letting employers know about skills that residents might have, and providing training that is accessible to residents.”
4:00 PM, 12/10/19
The preliminary results are in! (Emphasis on the word preliminary.)
As senior fellow Brett Theodos explained, “It seems job access is not great for households receiving housing assistance, but it’s also equally not great for unassisted low-income households. For both groups, job access is worse than it is for middle- and upper-income households.”
Here’s a sentence from the forthcoming report (the numbers and wording are subject to change):
“We see that the average assisted household is surrounded by roughly 3,500 more job seekers than jobs in a reasonable commuting distance. This is only modestly better than unassisted low-income households, which have roughly 3,700 more job seekers than jobs.”
Theodos discussed the implications, should these results hold after technical review and testing. “On average, investments in federal housing don’t appear to help low-income people live closer to job opportunities that they would have accessed otherwise.”
Research analyst Brady Meixell noted the strengths and weaknesses of the job data the team analyzed. “Snag is one job-search engine out of many. That being said, Snag is the largest online marketplace for hourly work, which aligns with our research objective. Snag captures a segment of the population that other data sources don’t fully capture.”
Meixell added, “It could be the case that Snag is more popularly used in one area of the country, but it’s difficult to assess how it compares against other job data sources.”
3:00 PM, 12/10/19
The two immediately noted that Greenleaf stands just a two-minute walk from the Wharf, a $2 billion development filled with new businesses and luxury residences. The disparity between the two areas was striking. “I looked up rent for a one-bedroom studio at the Wharf, and it was $1,800,” said Peffley. “So that gives you a sense of how the area has gentrified.”
The photo below (taken by Peffley) shows Greenleaf and it's taller, newer neighbor.
Rajasekaran explained how qualitative efforts like this fit into research goals.
“If this was a long-term research project, we would probably go into a public housing complex, interview tenants, and get a qualitative picture of the economic environment,” explained Rajasekaran. “That would allow us to better test our hypothesis that public housing near employment centers can decrease spatial mismatch. But it was still informative to visit a real public housing project and see the proximity of everything.”
1:50 PM, 12/10/19
The writing team has completed the literature review, and they’ve sent it to senior editor Meghan Ashford-Grooms for copyediting.
Ananya Hariharan, who is on the writing team with Leiha Edmonds and Nancy Pindus, explained how her team tackled the challenge. “We’re lucky because there has been a lot of research on this topic, broadly speaking, including Urban research. So it was nice to cite our colleagues and build on their work.”
“This has also been a much more collaborative process than usual. Right now, eight people are writing sections of the final paper, and it will be our job to make it read smoothly.”
Hariharan also briefly summarized their review of existing evidence.
“The concept of spatial mismatch was originally proposed in 1968 by a professor named John Kain. Since then, some empirical evidence has supported the theory, and some has refuted it. More recent efforts to expand on Kain’s work have incorporated theories of racial prejudice.”
“We also reviewed the evidence on public housing and housing vouchers, which are essentially two different mechanisms for people to receive housing assistance,” she explained. “Public housing places tenants in government-owned buildings, whereas vouchers allow tenants to live with a private landlord.”
Hariharan provided a snapshot of the labor market’s relationship with public housing:
“Central-city neighborhoods typically have the most job opportunities, even despite a recent trend of jobs moving to suburbs. And since public housing tends to be in city centers, this suggests less spatial mismatch for people living in public housing.”
And potential challenges facing people using housing vouchers:
“Employers may discriminate against voucher holders for many reasons. For instance, they may not want their patrons to interact with low-income people. There is prejudice that comes with being low-income and prejudice that comes with being nonwhite, and oftentimes, voucher holders are nonwhite.”
So, although the research team isn’t attempting to explain causes of spatial mismatch, if spatial mismatch affects voucher holders, it may be driven by discrimination or racial prejudice from employers.
11:05 AM, 12/10/19
The Research-A-Thon is officially underway!
The researchers began the day by reviewing their goal: examining the relationship between assisted housing locations (including public housing, project-based vouchers, and housing choice vouchers) and “spatial mismatch,” or the mismatch between where jobs are located and where job seekers live. The researchers will then compare this relationship to the proximity of low-income households who do not live in assisted housing to jobs across US cities.
Senior research associate Christina Stacy, who is leading the Research-A-Thon, described the value of this line of questioning. “Many Americans may hold negative perceptions of assisted housing, especially regarding its relationship to property values or crime. Meanwhile, few have attempted to pinpoint the economic benefits of assisted housing, such as increased job opportunities for assisted housing residents and greater availability of employees for nearby businesses, both of which could theoretically boost a neighborhood’s economy.”
The researchers then broke into four teams:
- Writing. This team will review previous research on this topic and start preparing the templates for publication.
- Data cleaning. This team is working to prepare various datasets for analysis:
- Subsidized housing data can show the number of public housing units at both the census tract and zip code levels.
- Data from Snag, the largest online marketplace for hourly jobs, can help reveal spatial mismatch in the labor market.
- American Community Survey (ACS) data can reveal the approximate number of households in each Census tract that are within the income eligibility for public housing.
- Data analysis. This team will use the data to calculate the average spatial mismatch rates for zip codes with public housing units and compare that to spatial mismatch rates for other low-income households in each region.
- Creative. This team will explore assisted housing developments near Urban’s headquarters in Southwest DC. By taking photos and looking around at local businesses, this team may provide a real-world glimpse of assisted housing’s role in a local economy.
Stay tuned for more updates!
Illustration by KittyVector via Shutterstock.