Artikel

Spatial analysis of regional and income inequality in the United States

Understanding the spatial or geographical dependence of income inequality and regional inequality is crucial in the study of inequality. This paper employs a multi-scale, multi-mechanism framework to map and analyze historical patterns of regional and income inequality in the United States (US) by using state and regional panel data spanning over a century. To explore the patterns systematically and see the role of spatial partitioning, we organize the data around several established geographical partitions before conducting various geographical information system (GIS) analyses and statistical techniques. We also investigate the spatial dependence of income inequality and regional inequality. We find that spatial autocorrelation exists for both types of inequality in the US. However, the magnitude of spatial dependence for regional inequality is declining whereas it is volatile for income inequality over time. While income inequality has been at its peak in the most recent decades, we also notice that regional inequality is at its lowest point. As for the choice of partitioning, we observe that within inequality dominates for Census Divisions and Bureau of Economic Analysis (BEA) regions. Conversely, we see that between inequality overall contributes the most to the inequality among Census Regions.

Language
Englisch

Bibliographic citation
Journal: Economies ; ISSN: 2227-7099 ; Volume: 9 ; Year: 2021 ; Issue: 4 ; Pages: 1-21 ; Basel: MDPI

Classification
Wirtschaft
Economywide Country Studies: U.S.; Canada
General Regional Economics (includes Regional Data)
Regional Development Planning and Policy
Equity, Justice, Inequality, and Other Normative Criteria and Measurement
Subject
GIS
income inequality
regional inequality
spatial analysis

Event
Geistige Schöpfung
(who)
Khan, Muhammad Salar
Siddique, Abu Bakkar
Event
Veröffentlichung
(who)
MDPI
(where)
Basel
(when)
2021

DOI
doi:10.3390/economies9040159
Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Khan, Muhammad Salar
  • Siddique, Abu Bakkar
  • MDPI

Time of origin

  • 2021

Other Objects (12)