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dc.contributor.authorMonkkonen, Paavoen_US
dc.contributor.authorZhang, Xiaohuen_US
dc.date.accessioned2011-06-03en_US
dc.date.accessioned2012-06-22T14:12:26Z-
dc.date.available2012-06-22T14:12:26Z-
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/10419/59418-
dc.description.abstractThe spatial distribution of households of different income groups in urban areas has drawn longstanding attention from scholars and policy makers as residential location patterns have important implications for social outcomes and the economic efficiency of cities. Recent research on the measurement of socioeconomic segregation has led to the development of an index that is explicitly spatial and accounts for the ordinal nature of income data. The index allows for a disaggregation of segregation levels by scale and income. This paper applies these new measurement techniques to Hong Kong, an ideal case study due to its high population density, high level of income inequality, and the large share of the population that lives in public housing. Findings show that levels of socioeconomic segregation in Hong Kong are high, similar to those found in the United States. However, the shape of the segregation profile across the income distribution is found to be quite different from the United States, with high-income households much more isolated than low-income households. Explanations for this include the mountainous and island geography of Hong Kong, as well as the importance of public housing in the city.en_US
dc.language.isoengen_US
dc.publisherUniv. of California, Inst. of Urban and Regional Development Berkeley, Califen_US
dc.relation.ispartofseriesWorking Paper, Institute of Urban and Regional Development 2011-03en_US
dc.subject.ddc330en_US
dc.titleSocioeconomic segregation in Hong Kong: Spatial and ordinal measures in a high-density and highly unequal cityen_US
dc.typeWorking Paperen_US
dc.identifier.ppn661227499en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:Working Papers, IURD, UC Berkeley

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