Measuring spatial dynamics in metropolitan areas

Sergio J. Rey, Luc Anselin, David C. Folch, Daniel Arribas-Bel, Myrna L. Sastré Gutiérrez, Lindsey Interlante

Research output: Contribution to journalArticlepeer-review

36 Scopus citations


This article introduces a new approach to measuring neighborhood change. Instead of the traditional method of identifying "neighborhoods" a priori and then studying how resident attributes change over time, this approach looks at the neighborhood more intrinsically as a unit that has both a geographic footprint and a socioeconomic composition. Therefore, change is identified when both aspects of a neighborhood transform from one period to the next. The approach is based on a spatial clustering algorithm that identifies neighborhoods at two points in time for one city. The authors also develop indicators of spatial change at both the macro (city) level and the local (neighborhood) scale. The authors illustrate these methods in an application to an extensive database of time-consistent census tracts for 359 of the largest metropolitan areas in the United States for the period 1990-2000.

Original languageEnglish (US)
Pages (from-to)54-64
Number of pages11
JournalEconomic Development Quarterly
Issue number1
StatePublished - Jan 2011
Externally publishedYes


  • neighborhood change
  • regionalization

ASJC Scopus subject areas

  • Development
  • Economics and Econometrics
  • Urban Studies


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