Power-law distributions in economics: a nonextensive statistical approach

Silvio M. Duarte Queiros; Celia Anteneodo; Constantino Tsallis

doi:10.1117/12.619469

23 May 2005 Power-law distributions in economics: a nonextensive statistical approach (Invited Paper)

Silvio M. Duarte Queiros, Celia Anteneodo, Constantino Tsallis

Author Affiliations +

Proceedings Volume 5848, Noise and Fluctuations in Econophysics and Finance; (2005) https://doi.org/10.1117/12.619469
Event: SPIE Third International Symposium on Fluctuations and Noise, 2005, Austin, Texas, United States

Abstract

The cornerstone of Boltzmann-Gibbs (BG) statistical mechanics is the Boltzmann-Gibbs-Jaynes-Shannon entropy S_BG≡ -k &sh; dx f(x) ln f(x), where k is a positive constant and f(x) a probability density function. This theory has exibited, along more than one century, great success in the treatment of systems where short spatio/temporal correlations dominate. There are, however, anomalous natural and artificial systems that violate the basic requirements for its applicability. Different physical entropies, other than the standard one, appear to be necessary in order to satisfactorily deal with such anomalies. One of such entropies is S_q ≡ k (1-&sh; dx [f(x)]^q)=(1-q) (with S₁ = S_BG), where the entropic index q is a real parameter. It has been proposed as the basis for a generalization, referred to as nonextensive statistical mechanics, of the BG theory. S_q shares with S_BG four remarkable properties, namely concavity (8q > 0), Lesche-stability (8q > 0), finiteness of the entropy production per unit time (q 2 <), and additivity (for at least a compact support of q including q = 1). The simultaneous validity of these properties suggests that S_q is appropriate for bridging, at a macroscopic level, with classical thermodynamics itself. In the same natural way that exponential probability functions arise in the standard context, power-law tailed distributions, even with exponents out of the Levy range, arise in the nonextensive framework. In this review, we intend to show that many processes of interest in economy, for which fat-tailed probability functions are empirically observed, can be described in terms of the statistical mechanisms that underly the nonextensive theory.

Citation Download Citation

Silvio M. Duarte Queiros, Celia Anteneodo, and Constantino Tsallis "Power-law distributions in economics: a nonextensive statistical approach (Invited Paper)", Proc. SPIE 5848, Noise and Fluctuations in Econophysics and Finance, (23 May 2005); https://doi.org/10.1117/12.619469

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