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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01pz50gz56r
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dc.contributor.advisorMassey, Douglas S-
dc.contributor.authorTannen, Jonathan-
dc.contributor.otherPublic and International Affairs Department-
dc.date.accessioned2016-09-27T15:46:36Z-
dc.date.available2016-09-27T15:46:36Z-
dc.date.issued2016-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01pz50gz56r-
dc.description.abstractDo neighborhoods “spread”? American cities are often highly segregated, divided into large regions of blocks with similar ethnic and racial composition with sharp boundaries between them. While most neighborhood research uses fixed boundaries, mostly Census tracts, I argue that boundaries are not predetermined, but emerge endogenously and can move over time. In this dissertation, I ask to what extent, over the last decade, has population change occured by these boundaries moving in space, and to what extent by the overall internal mix of these regions changing? Neighborhood change that occurs by within-cluster change would be large-scale, gradual, and diffuse, whereas change by boundary movements would be sharp, occur to specific blocks, and perhaps continue to segregate residents’ use of space. In Chapter 1, I develop a Bayesian algorithm, the Space-Time Chinese Restaurant Process (Space-Time CRP), to identify these spatial clusters of households’ race and ethnicity from block-level Census data, with boundaries that can move over time. I examine the changes in those ethnoracial clusters in Philadelphia, PA from 2000 to 2010, and decompose Philadelphia’s ethnoracial change to find a previously unmeasured dynamic: more-White and Asian clusters are growing spatially, even as all clusters are internally becoming more Black and more Hispanic. In Chapter 2, I replicate the analysis for the 100 largest U.S. central cities. In most of the cities, the overall trend was one of internal changes, led by increasing proportions Hispanic and Asian. However, I find that population change by boundary movement was prevalent in denser cities, and usually by Whiter clusters expanding into Blacker clusters. While all cities experienced gradual increases in non-White populations within clusters, the gentrification of dense cities occured by the sharper change of Whiter clusters expanding. In Chapter 3, I measure the change in number and type of businesses as a boundary moves. Businesses are a compelling symbol and perhaps agent of neighborhood change. I find that business change is typically a lagging indicator around gentrifying boundaries, with businesses changing only after the demographic change has occured. In neighborhoods experiencing increasing non-White populations, businesses change in advance of the boundary’s approach.-
dc.language.isoen-
dc.publisherPrinceton, NJ : Princeton University-
dc.relation.isformatofThe Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog: <a href=http://catalog.princeton.edu> catalog.princeton.edu </a>-
dc.subjectBoundaries-
dc.subjectChange-
dc.subjectEmergence-
dc.subjectGentrification-
dc.subjectNeighborhoods-
dc.subjectUrban-
dc.subject.classificationPublic policy-
dc.titleMeasuring cities' internal demographic change as the movement of emergent boundaries-
dc.typeAcademic dissertations (Ph.D.)-
pu.projectgrantnumber690-2143-
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