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Rank-based Markov chains for regional income distribution dynamics

Rank-based Markov chains for regional income distribution dynamics Markov chains have become a mainstay in the literature on regional income distribution dynamics and convergence. Despite its growing popularity, the Markov framework has some restrictive characteristics associated with the underlying discretization income distributions. This paper introduces several new approaches designed to mitigate some of the issues arising from discretization. Based on the examination of rank distributions, two new Markov-based chains are developed. The first explores the movement of individual economies through the income rank distribution over time. The second provides insight on the movements of ranks over geographical space and time. These also serve as the foundation for two new tests of spatial dynamics or the extent to which movements in the rank distribution are spatially clustered. An illustration of these new methods is included using income data for the lower 48 US states for the years 1929–2009. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Geographical Systems Springer Journals

Rank-based Markov chains for regional income distribution dynamics

Journal of Geographical Systems , Volume 16 (2) – Aug 2, 2013

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References (51)

Publisher
Springer Journals
Copyright
Copyright © 2013 by Springer-Verlag Berlin Heidelberg
Subject
Economics / Management Science; Regional/Spatial Science; Geographical Information Systems/Cartography; Computer Appl. in Social and Behavioral Sciences; Landscape/Regional and Urban Planning; Geography (general); Simulation and Modeling
ISSN
1435-5930
eISSN
1435-5949
DOI
10.1007/s10109-013-0189-0
Publisher site
See Article on Publisher Site

Abstract

Markov chains have become a mainstay in the literature on regional income distribution dynamics and convergence. Despite its growing popularity, the Markov framework has some restrictive characteristics associated with the underlying discretization income distributions. This paper introduces several new approaches designed to mitigate some of the issues arising from discretization. Based on the examination of rank distributions, two new Markov-based chains are developed. The first explores the movement of individual economies through the income rank distribution over time. The second provides insight on the movements of ranks over geographical space and time. These also serve as the foundation for two new tests of spatial dynamics or the extent to which movements in the rank distribution are spatially clustered. An illustration of these new methods is included using income data for the lower 48 US states for the years 1929–2009.

Journal

Journal of Geographical SystemsSpringer Journals

Published: Aug 2, 2013

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