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Title: Cross ranking of cities and regions: Population versus income
Authors: Cerqueti, Roy
Ausloos, Marcel
First Published: 1-Jul-2015
Publisher: Institute of Physics Publishing
Citation: Journal of Statistical Mechanics: Theory and Experiment, (2015) P07002
Abstract: This paper explores the relationship between the inner economical structure of communities and their population distribution through a rank-rank analysis of official data, along statistical physics ideas within two techniques. The data is taken on Italian cities. The analysis is performed both at a global (national) and at a more local (regional) level in order to distinguish 'macro' and 'micro' aspects. First, the rank-size rule is found not to be a standard power law, as in many other studies, but a doubly decreasing power law. Next, the Kendall τ and the Spearman ρ rank correlation coefficients which measure pair concordance and the correlation between fluctuations in two rankings, respectively, - as a correlation function does in thermodynamics, are calculated for finding rank correlation (if any) between demography and wealth. Results show non only global disparities for the whole (country) set, but also (regional) disparities, when comparing the number of cities in regions, the number of inhabitants in cities and that in regions, as well as when comparing the aggregated tax income of the cities and that of regions. Different outliers are pointed out and justified. Interestingly, two classes of cities in the country and two classes of regions in the country are found. 'Common sense' social, political, and economic considerations sustain the findings. More importantly, the methods show that they allow to distinguish communities, very clearly, when specific criteria are numerically sound. A specific modeling for the findings is presented, i.e. for the doubly decreasing power law and the two phase system, based on statistics theory, e.g. urn filling. The model ideas can be expected to hold when similar rank relationship features are observed in fields. It is emphasized that the analysis makes more sense than one through a Pearson Π value-value correlation analysis.
DOI Link: 10.1088/1742-5468/2015/07/P07002
eISSN: 1742-5468
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2015, IOP Publishing Ltd and SISSA Media. Deposited with reference to the publisher’s archiving policy available on the SHERPA/RoMEO website.
Description: The file associated with this record is under embargo for 12 months from the date of publication.
Appears in Collections:Published Articles, School of Management

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