打印

作者

来源

来源 JOURNAL OF URBAN ECONOMICS,Vol.62,P.519-541

语言

英文

关键字

Urban economics;Agglomeration;Subcenters;Employment density;Nonparametric;Intraurban employment dynamics

作者单位

School of Policy, Planning, and Development, University of Southern California, Los Angeles, CA 90089-0626, USA"}]}]}],"floats":[],"footnotes":[],"affiliations":{"aep-affiliation-id2":{"#name":"affiliation","$":{"id":"aep-affiliation-id2;School of Policy, Planning, and Development, University of Southern California, Los Angeles, CA 90089-0626, USA"}]}},"attachments":[],"correspondences":{},"scopusAuthorIds":{},"articles":{}},"authorMetadata":[],"banner":{"expanded":false},"biographies":{},"body":{},"browser":{"name":"IE","engine":"Trident

摘要

While it is well recognized that US metropolitan areas are polycentric, there is little consensus as to the appropriate method for identifying concentrations of employment within them. Existing methods suffer from strong assumptions about parametric form, misspecification, or reliance on local knowledge to calibrate model parameters. This paper introduces a new nonparametric method for identifying subcenters. Results indicate that this, more flexible, nonparametric approach yields greater accuracy with regard to both urban and suburban centers compared with other approaches. This approach should provide better data for the numerous topics that depend on the spatial accounting of employment within metropolitan areas.