Neighbors and networks: The role of social interactions on the residential choices of housing choice voucher holders

Ellen, Ingrid Gould; Suher, Michael; Torrats-Espinosa, Gerard

doi:10.1016/j.jhe.2018.09.005

Cited by 11 publications

(10 citation statements)

References 21 publications

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“…Our results show that households that had one additional neighbor who recently leased up were nearly 3 percent more likely to lease up themselves. These estimates add to recent evidence that social interactions with neighbors may influence where voucher users choose to live (Ellen, Suher, & Torrats‐Espinosa, ), and complement a broader literature that shows peers affect program take‐up (Aizer & Currie, 2004; Dahl, Loken, & Mogstad, ; Duflo & Saez, ; Figlio, Hamersma, & Roth, ).…”

Section: Introductionsupporting

confidence: 70%

“…We can relate many of the variables in our data to the probability of finding a unit, the expected benefits of leasing, and the costs associated with search. The probability of finding a unit is related to the supply of suitable units, the number of landlords willing to lease to housing voucher recipients, and the family's search strategy, which may be informed by those in its social network (Ellen, Suher, & Torrats‐Espinosa, ). Variables in our data that may relate to the probability of finding a unit include the number of adults and children in the household, because larger units may be more difficult to find within the allotted search time (Popkin & Cunningham, ) .…”

Section: Modelmentioning

confidence: 99%

“…Black household heads are 5.4 percentage points more likely than whites to lease up, a result that is counter to a long literature demonstrating racial discrimination in rental markets (e.g., Desmond, ) but consistent with results from one of the studies most similar to our own (Mills et al., ). This may also reflect the possibility that, because Chicago is a city with a high degree of racial segregation where most voucher recipients are black, black households are more readily able to tap into social networks that facilitate their housing search than non‐black households (Ellen, Suher, & Torrats‐Espinosa, ).…”

Section: Predicting Voucher Usementioning

confidence: 99%

See 2 more Smart Citations

Housing Voucher Take‐Up and Labor Market Impacts

Chyn

Hyman

Kapustin

2018

J Policy Anal Manage

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Low participation rates in government assistance programs are a major policy concern in the United States. This paper studies take‐up of Section 8 housing vouchers, a program in which take‐up rates are quite low among interested and eligible households. We link 18,109 households in Chicago that were offered vouchers through a lottery to administrative data and study how baseline employment, earnings, public assistance, arrests, residential location, and children's academic performance predict take‐up. Our analysis finds mixed evidence of whether the most disadvantaged or distressed households face the largest barriers to program participation. We also study the causal impact of peer behavior on take‐up by exploiting idiosyncratic variation in the timing of voucher offers. We find that the probability of lease‐up increases with the number of neighbors who recently received voucher offers. Finally, we explore the policy implications of increasing housing voucher take‐up by applying reweighting methods to existing causal impact estimates of voucher receipt. This analysis suggests that greater utilization of vouchers may lead to larger reductions in labor market activity. Differences in take‐up rates across settings may be important to consider when assessing the external validity of studies identifying the effects of public assistance programs.

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Section: Introductionsupporting

confidence: 70%

Section: Modelmentioning

confidence: 99%

Section: Predicting Voucher Usementioning

confidence: 99%

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Housing Voucher Take‐Up and Labor Market Impacts

Chyn

Hyman

Kapustin

2018

J Policy Anal Manage

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“…Our selection model rules out the possibility of interference. While there is reason to believe this assumption is violated in the context of MTO(Ellen, Suher, & Torrats-Espinosa, 2019), we leave relaxing this assumption to future work because doing so creates significant new obstacles to identification(Sobel, 2006;Manski, 2013).…”

mentioning

confidence: 99%

Evidence of Neighborhood Effects from Moving to Opportunity: LATEs of Neighborhood Quality

Aliprantis

Richter

2020

The Review of Economics and Statistics

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This paper estimates neighborhood effects on adult labor market outcomes using the Moving to Opportunity (MTO) housing mobility experiment. We propose and implement a new strategy for identifying transition-specific effects that exploits identification of the unobserved component of a neighborhood choice model. Estimated Local Average Treatment Effects (LATEs) are large, result from moves between the first and second deciles of the national distribution of neighborhood quality, and pertain to a subpopulation of nine percent of program participants.

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“…Our selection model rules out the possibility of interference. While there is reason to believe this assumption is violated in the context of MTO(Ellen et al (2018)), we leave relaxing this assumption to future work because doing so creates significant new obstacles to identification(Sobel (2006),Manski (2013)). …”

mentioning

confidence: 99%