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dc.contributor.advisorP. Christopher Zegras.en_US
dc.contributor.authorLeape, Jonathan Hoagland.en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Urban Studies and Planning.en_US
dc.coverage.spatials-bl---en_US
dc.date.accessioned2020-09-15T22:06:04Z
dc.date.available2020-09-15T22:06:04Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/127612
dc.descriptionThesis: M.C.P., Massachusetts Institute of Technology, Department of Urban Studies and Planning, May, 2020en_US
dc.descriptionThesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Urban Studies and Planning, May, 2020en_US
dc.descriptionCataloged from the official PDF of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 95-106).en_US
dc.description.abstractIn the wake of the 2008 financial crisis, the Brazilian federal government launched My House, My Life (PMCMV), an ambitious program to build subsidized housing for over five million low-income families. While the program has been praised for its scale, early evidence suggests that its beneficiaries may be struggling. Complaints of high utility bills, militia exploitation and intolerable commutes have surfaced alongside studies showing that beneficiaries may be unable to hold a formal job upon moving. In Rio de Janeiro, many housing units are awarded via random lottery, creating a rare opportunity to infer the causal impacts of the program. In this thesis, I track the employment activity and earnings of over 28,000 participants, half of whom were awarded 90%-subsidized units, between 2011 and 2017. Contradicting most theory and evidence, I find that moving to a PMCMV unit increased earnings by 13% and the likelihood of employment by 2% after four years.en_US
dc.description.abstractSince beneficiaries generally sacrifice both safety and access to jobs in moving, other factors, such as residential stability or the need to cover higher living costs, may explain the increase in labor market activity. Outcomes vary significantly among types of participants and project locations, revealing opportunities for the government to target follow-up assistance and improve project locations. The types of lottery winners most likely to move differ from those who are most likely to see their formal incomes increase. Men, non-whites, favela residents and the college educated are less likely to move, even though they are at least as likely to benefit. Furthermore, participants are more likely to move to projects far from downtown even though such projects generate weaker income benefits. Participants also revealed a preference for nearby PMCMV units, but those who moved far experienced the same income benefits.en_US
dc.description.abstractThese findings indicate that lottery winners are either misinformed about how moving might impact their potential earnings or make their decision to move based on other factors.en_US
dc.description.statementofresponsibilityby Jonathan Hoagland Leape.en_US
dc.format.extent135 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectUrban Studies and Planning.en_US
dc.titleWinning the housing lottery in Rio de Janeiro : curse or cure?en_US
dc.typeThesisen_US
dc.description.degreeM.C.P.en_US
dc.description.degreeS.M. in Transportationen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Urban Studies and Planningen_US
dc.identifier.oclc1193557102en_US
dc.description.collectionM.C.P. Massachusetts Institute of Technology, Department of Urban Studies and Planningen_US
dc.description.collectionS.M.inTransportation Massachusetts Institute of Technology, Department of Urban Studies and Planningen_US
dspace.imported2020-09-15T22:06:03Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentUrbStuden_US


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