Studies on   Regional Wealth Inequalities

Marcel Ausloos 

University of Liege, Institute of Physics, SUPRATECS (ULg), B5, Liège 4000, Belgium
University of Leicester, University Road, Leicester LE17RH, United Kingdom


I will review techniques and results examining regional wealth inequalities based  on research recently worked out with Roy Cerqueti (Univ. Macerata).  In brief, correlations between macro-economy and micro-economy features are searched for. See the following papers:
 R.  Cerqueti and MA, Statistical Assessment of Regional Wealth Inequalities: the Italian Case, Quality and Quantity, in press   (2014) doi: 10.1007/s11135-014-0111-y
 R.  Cerqueti and MA, Evidence of economic regularities and disparities of Italian regions from aggregated tax income size data, Physica A 421 (2015) 187-207   doi:10.1016/j.physa.2014.11.027
 R. Cerqueti and MA, Cross Ranking of Cities and Regions: Population vs. Income,   J. Stat. Mech.  7(2015) P07002  doi:10.1088/1742-5468/2015/07/P07002
 R. Cerqueti and MA, Socio-economical Analysis of Italy: the case of hagiotoponym cities,   The Social Science Journal, in press   (2015)   doi:10.1016/j.soscij.2015.03.004
 MA and R. Cerqueti, Religion-based Urbanization Process in Italy: Statistical Evidence from Demographic and Economic Data,  Quality and Quantity in press (2015).  doi:  10.1007/s11135-015-0220-2
The data pertains to Italy (IT),  over the period 2007-2011: the number of cities in regions, the number of inhabitants in cities and in regions, as well as  the aggregated tax income of the cities and of regions, - but the ideas can be carried forward to other countries or systems.    Frequency-size plots and cumulative distribution function plots,   scatter plots and rank-size plots are displayed.  The rank-size rule (for IT) is  found not to be a standard power law, as in many other studies, but a doubly decreasing power law; the Kendall $\tau$  and the Spearman $\rho$ rank correlation coefficients are calculated. Yearly data  of the aggregated tax income is transformed into a few indicators: the  Gini, Theil, and Herfindahl-Hirschman indices. Numerical results confirm that  IT  is  divided into  very different regional realities.  Communities can be,  very clearly,  distinguished, when specific criteria are numerically sound.  Attention is given to  cultural aspects  through linguistic and religiosity criteria and the historical evolution of  IT urbanization process.  A specific urban distribution modeling is presented for the doubly decreasing power law, emphasizing the "phase system", based on urn filling  statistics theory.


Related papers
  1. Investigating random, 50/50 symmetric weighted, competitive and cooperative fully connected networks: the random matrix approach.
  2. Modelling and Forecasting the Kurtosis of Financial Markets: insights provided using Irrational fractional Brownian Motion.
  3. SME investment best strategies
  4.  Shortening review time in peer review with Cartesian Genetic Programming
  5. Threshold Model for Triggered Financial Bubbles on Networks
  6. Clusters in weighted macroeconomic networks: the EU case
  7. Interacting agent model describing some evolution of economic entities under varying spatio-temporal economic conditions.
  8. Structural and magnetic properties of nanosized barium hexaferrite powders obtained by microemulsion techniques
  9. Correlations between the most developed economies - network analysis

Presentation: Invited oral at 8 Ogólnopolskie Sympozjum "Fizyka w Ekonomii i Naukach Społecznych", by Marcel Ausloos
See On-line Journal of 8 Ogólnopolskie Sympozjum "Fizyka w Ekonomii i Naukach Społecznych"

Submitted: 2015-09-01 12:19
Revised:   2015-09-01 12:19