The Geography of Economic Segregation

Richard Florida and Charlotta Mellander
Additional contact information
Richard Florida: Martin Prosperity Institute, Rotman School of Management, University of Toronto, 105 St. George Street, Toronto, ON M5S 3E6, Canada

Social Sciences, 2018, vol. 7, issue 8, 1-17

Abstract: This study examines the key factors that are associated with the geography of economic segregation across US metros. It connects the sociological literature on the extent and variation of economic segregation to the urban economics literature on the factors associated with urban and regional performance. It advances the hypothesis that economic segregation will be greater in larger, denser, more knowledge-based regions as well as in light of racial factors and income inequality. It utilizes measures of Income, Educational, and Occupational Segregation along with a combined measure of Overall Economic Segregation. Our findings are in line with the hypothesis and indicate that economic segregation is associated with larger, denser, more highly educated metros. Economic segregation is also to a certain extent related with race and ethnicity, commuting style, and income inequality.

Keywords: economic segregation; regional performance; population; size; density; knowledge economies; inequality; race; ethnicity (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
https://www.mdpi.com/2076-0760/7/8/123/pdf (application/pdf)
https://www.mdpi.com/2076-0760/7/8/123/ (text/html)

Related works:
Working Paper: The Geography of Economic Segregation (2017)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jscscx:v:7:y:2018:i:8:p:123-:d:160237

Access Statistics for this article

Social Sciences is currently edited by Ms. Yvonne Chu

More articles in Social Sciences from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().