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Table of Contents | Background
& Objective | Contributors
Spatially Integrated Social Science: Chapter 14
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15 >
Spatial
Analysis of Regional Income Inequality
Sergio J. Rey
Abstract
Questions surrounding regional economic
convergence have commanded a great deal of recent attention
in the economics literature. As in other recent cases in the
social sciences, the application of spatially
explicit methods of data analysis to the convergence question
has yielded important insights on regional economic growth.
By contrast, the literature on regional income inequality,
although somewhat older than the convergence literature, has
been slower to adopt new spatially explicit methods of data
analysis.
This chapter helps to speed that adoption by investigating
the role of spatial dependence and spatial scale in the analysis
of regional income inequality in the United States over the
1929-2000 period. The findings reveal a strong positive relationship
between measures of inequality in state incomes and the degree
of spatial autocorrelation. Additionally, a geographically
based decomposition of inequality highlights a strong positive
relationship between the interregional inequality share (as
opposed to intraregional inequality) and spatial clustering.
Finally, a new approach to inference in regional inequality
analysis is suggested and demonstrated as providing a formal
explanatory framework to complement the broad, but descriptive,
approaches in the existing literature.
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