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Rank-based Markov chains for regional income distribution dynamics

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  • Sergio Rey

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. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Sergio Rey, 2014. "Rank-based Markov chains for regional income distribution dynamics," Journal of Geographical Systems, Springer, vol. 16(2), pages 115-137, April.
    • Handle: RePEc:kap:jgeosy:v:16:y:2014:i:2:p:115-137
    DOI: 10.1007/s10109-013-0189-0
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    Cited by:

    1. Enrico Fabrizi & Gianni Guastella & Stefano Marta & Francesco Timpano, 2016. "Determinants of Intra-Distribution Dynamics in European Regions: An Empirical Assessment of the Role of Structural Intervention," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 107(5), pages 522-539, December.
    2. Levi John Wolf & Sergio Rey, 2016. "On the lumpability of regional income convergence," Letters in Spatial and Resource Sciences, Springer, vol. 9(3), pages 265-275, October.
    3. Wenze Yue & Yuntang Zhang & Xinyue Ye & Yeqing Cheng & Mark R. Leipnik, 2014. "Dynamics of Multi-Scale Intra-Provincial Regional Inequality in Zhejiang, China," Sustainability, MDPI, vol. 6(9), pages 1-22, August.
    4. Pauhofová, Iveta & Želinský, Tomáš, 2017. "On the Regional Convergence of Income at District Level in Slovakia," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 65(10), pages 918-934.
    5. Jonathan Reades & Jordan De Souza & Phil Hubbard, 2019. "Understanding urban gentrification through machine learning," Urban Studies, Urban Studies Journal Limited, vol. 56(5), pages 922-942, April.

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    More about this item

    Keywords

    Spatial dynamics; Markov; Regional income distributions; Convergence; R11; C21; C46;
    All these keywords.

    JEL classification:

    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

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