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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01sf2687954
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dc.contributor.advisorCarmona, Rene-
dc.contributor.authorWang, Catherine-
dc.date.accessioned2019-08-16T15:31:12Z-
dc.date.available2019-08-16T15:31:12Z-
dc.date.created2019-04-08-
dc.date.issued2019-08-16-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01sf2687954-
dc.description.abstractSurging housing prices in Chinese cities like Beijing have raised concerns about asset bubbles and housing affordability. Beijing has typically directly regulated housing market growth using Home Purchase Restriction (HPR) policies (increasing down payments, restricting eligibility), the effects of which have been measured in existing literature. However, in Beijing, public education accessibility also has a strong impact on the housing market, as parents bid up home prices near top primary schools as a way to guarantee enrollment. In April 2017, due to concerns about the financial risks associated with speculation over “school district houses,” the Beijing Municipal Government announced that buying an apartment would no longer guarantee enrollment in top ranked public schools, by adding an element of randomization to school district assignment in each of the six core districts. This thesis is the first to specifically examine how an indirect perturbation, i.e. Beijing's April 2017 education policy change (AEP), affects the Beijing housing market. We combine a newly released dataset of individual housing transactions in Beijing between 2010-late 2017 with a dataset that we manually create containing information on all the primary schools in Beijing. Using these two datasets, we test six hypotheses, which differently measure the impact of AEP. We find support for the existing scholarly consensus that access to higher quality schools positively impacts housing prices. Furthermore, we show that districts with higher average and lower variance in education quality are less impacted by the April education policy change. We also find evidence that the lag between the April 2017 policy announcement and June 2017 implementation strongly affects buyer behavior, as we identify a price spike for certain homes. We attribute this spike to buyers feeling more urgency to buy ``at-risk'' homes that previously guaranteed access to top primary schools, before the new policy change goes into effect.en_US
dc.format.mimetypeapplication/pdf-
dc.language.isoenen_US
dc.titleSchool Zone Scramble: How Beijing's Changing Education Policy Impacts Housing Pricesen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2019en_US
pu.departmentOperations Research and Financial Engineering*
pu.pdf.coverpageSeniorThesisCoverPage-
pu.contributor.authorid961114120-
pu.certificateFinance Programen_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2022

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