Nonparametric employment subscenter identification

Daniel P McMillen

Research output: Contribution to journalArticlepeer-review

Abstract

A two-stage procedure is proposed for identifying urban employment subcenters. The first stage identifies candidate subcenters as significant positive residuals in a smoothed employment density function. Subcenters are those sites that provide significant explanatory power in the second-stage, semiparametric employment density function estimation. The procedure can be applied to either aggregated or disaggregated data, does not require detailed knowledge of the study area, and is easily reproducible by other researchers. Results are presented for five previously studied cities-Chicago, Dallas, Houston, Los Angeles, and San Francisco-and a new one, New Orleans.

Original languageEnglish (US)
Pages (from-to)448-473
Number of pages26
JournalJournal of Urban Economics
Volume50
Issue number3
DOIs
StatePublished - Jan 1 2001

Keywords

  • Employment density
  • Fourier expansion
  • Nonparametric
  • Population density
  • Semiparametric
  • Subcenters

ASJC Scopus subject areas

  • Economics and Econometrics
  • Urban Studies

Fingerprint

Dive into the research topics of 'Nonparametric employment subscenter identification'. Together they form a unique fingerprint.

Cite this