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Cross ranking of cities and regions: Population versus income

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journal contribution
posted on 21.08.2015, 08:38 by Roy Cerqueti, Marcel Ausloos
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.

History

Citation

Journal of Statistical Mechanics: Theory and Experiment, (2015) P07002

Author affiliation

/Organisation/COLLEGE OF SOCIAL SCIENCE/School of Management

Version

AM (Accepted Manuscript)

Published in

Journal of Statistical Mechanics: Theory and Experiment

Publisher

Institute of Physics Publishing

eissn

1742-5468

Acceptance date

04/06/2015

Copyright date

2015

Available date

01/07/2016

Publisher version

http://iopscience.iop.org/1742-5468/2015/7/P07002/

Notes

The file associated with this record is under embargo for 12 months from the date of publication.

Language

en