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dc.contributor.advisorPlane, David A.en_US
dc.contributor.advisorMulligan, Gordon F.en_US
dc.contributor.authorHolland, Sandra Carole*
dc.creatorHolland, Sandra Caroleen_US
dc.date.accessioned2011-12-06T14:21:16Z
dc.date.available2011-12-06T14:21:16Z
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/10150/196084
dc.description.abstractThis study examines the effects of educational submarkets -- schools and districts -- on house prices in the Tucson region. The supposition that homebuyers will pay more to live in a better school district or school attendance area is examined, with the quality of education measured by per-student expenditures and academic achievement. Traditional single-market modeling of the housing market finds that education submarkets have a small but significant effect on housing price. Further modeling, taking explicit account of the spatial nature of the housing market, suggests that in the single-market approach, education submarkets act as proxies for other neighborhood effects and variables omitted from the model. Incorporating the unique location coordinates of the properties and allowing marginal attribute- and location-effects to vary across geographic space in a trend surface approach produces more robust model results and allows the educational submarket effects to be isolated. The results suggest that school districts have a small but significant price effect even after a fluid price surface has been developed, but that intra-district variation remains. These price effects have some relationship with district quality as measured by academic achievement, but the housing market does not reward per-student expenditures. At the intra-district level, middle school quality does not appear to have a significant effect on housing price, at least in the Tucson Unified School District. However, the trend surface approach still proves to be a useful methodology for modeling small, local-scale variations. The use of polynomial expansion and spatial- attribute variable interactions is successful: problems of variable omission are diminished, spatially autocorrelated error terms are reduced and removed, effects of multicollinearity are minimized, and the effects of the educational submarkets may be examined in isolation.
dc.language.isoENen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjecteducationen_US
dc.subjecthedonicen_US
dc.subjecthouse pricesen_US
dc.subjecthousingen_US
dc.subjectqualityen_US
dc.subjectschool districtsen_US
dc.titleHedonic Modeling of the Tucson Housing Market: The Effect of Educational Submarkets on House Pricesen_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.contributor.chairPlane, David Aen_US
dc.contributor.chairMulligan, Gordon Fen_US
dc.identifier.oclc659750595en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberTong, Daoqinen_US
dc.contributor.committeememberDall'Erba, Sandyen_US
dc.identifier.proquest10041en_US
thesis.degree.disciplineGeographyen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.namePh.D.en_US
refterms.dateFOA2018-06-24T18:35:03Z
html.description.abstractThis study examines the effects of educational submarkets -- schools and districts -- on house prices in the Tucson region. The supposition that homebuyers will pay more to live in a better school district or school attendance area is examined, with the quality of education measured by per-student expenditures and academic achievement. Traditional single-market modeling of the housing market finds that education submarkets have a small but significant effect on housing price. Further modeling, taking explicit account of the spatial nature of the housing market, suggests that in the single-market approach, education submarkets act as proxies for other neighborhood effects and variables omitted from the model. Incorporating the unique location coordinates of the properties and allowing marginal attribute- and location-effects to vary across geographic space in a trend surface approach produces more robust model results and allows the educational submarket effects to be isolated. The results suggest that school districts have a small but significant price effect even after a fluid price surface has been developed, but that intra-district variation remains. These price effects have some relationship with district quality as measured by academic achievement, but the housing market does not reward per-student expenditures. At the intra-district level, middle school quality does not appear to have a significant effect on housing price, at least in the Tucson Unified School District. However, the trend surface approach still proves to be a useful methodology for modeling small, local-scale variations. The use of polynomial expansion and spatial- attribute variable interactions is successful: problems of variable omission are diminished, spatially autocorrelated error terms are reduced and removed, effects of multicollinearity are minimized, and the effects of the educational submarkets may be examined in isolation.


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