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Inverted rank distributions: Macroscopic statistics, universality classes, and critical exponents

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  • Eliazar, Iddo
  • Cohen, Morrel H.

Abstract

An inverted rank distribution is an infinite sequence of positive sizes ordered in a monotone increasing fashion. Interlacing together Lorenzian and oligarchic asymptotic analyses, we establish a macroscopic classification of inverted rank distributions into five “socioeconomic” universality classes: communism, socialism, criticality, feudalism, and absolute monarchy. We further establish that: (i) communism and socialism are analogous to a “disordered phase”, feudalism and absolute monarchy are analogous to an “ordered phase”, and criticality is the “phase transition” between order and disorder; (ii) the universality classes are characterized by two critical exponents, one governing the ordered phase, and the other governing the disordered phase; (iii) communism, criticality, and absolute monarchy are characterized by sharp exponent values, and are inherently deterministic; (iv) socialism is characterized by a continuous exponent range, is inherently stochastic, and is universally governed by continuous power-law statistics; (v) feudalism is characterized by a continuous exponent range, is inherently stochastic, and is universally governed by discrete exponential statistics. The results presented in this paper yield a universal macroscopic socioeconophysical perspective of inverted rank distributions.

Suggested Citation

  • Eliazar, Iddo & Cohen, Morrel H., 2014. "Inverted rank distributions: Macroscopic statistics, universality classes, and critical exponents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 450-459.
  • Handle: RePEc:eee:phsmap:v:393:y:2014:i:c:p:450-459
    DOI: 10.1016/j.physa.2013.08.073
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    Cited by:

    1. Luckstead, Jeff & Devadoss, Stephen & Danforth, Diana, 2017. "The size distributions of all Indian cities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 237-249.

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