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The equilibrium and nonequilibrium distribution of money Juan C. Ferrero Centro Laser de Ciencias Moleculares and INFIQC Universidad Nacional de Córdoba, Córdoba. Argentina. Science → Prediction (Control) Events Time Rate Consequences
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The equilibrium and nonequilibrium distribution of money Juan C. Ferrero Centro Laser de Ciencias Moleculares and INFIQC Universidad Nacional de Córdoba, Córdoba Argentina
Science → Prediction (Control) Events Time Rate Consequences Nature→ Spontaneity → Endless approach to (irreversibility) equilibrium (continuous evolution) One approach to the problem is to learn through model calculations of known systems
External input and output ith money level of agent A w (Pi1 n1 + Pi2 n2 + Pi3 n3 +…) w ( P1i ni + P2i ni + P3i ni+…) Interaction transfer into i Interaction transfer out of i
An arbitrary, far from equilibrium distribution evolves to the BG population through near Gaussian distributions
kiB ith money level of agent A ith money level of agent B kiA wAA(Pi1 n1 + Pi2 n2 + Pi3 n3 +…) + wAB(Pi1 n1 + Pi2 n2 + Pi3 n3 wBA( P1i ni + P2i ni + P3i ni+…) + wBB( P1i ni + P2i ni + P3i ni+…) Interaction transfer with A and B into Ai and Bi Interaction transfer with A and B out of AiandBi
The initial BG population evolves to two different BG distributions through BG-like intermediate distributions with different values of b
This provides two criteria for deviation from equilibrium: 1- Near Gaussian distributions 2- Multiple BG distributions with different values of b
Before the crisis: A single Gamma function (bimodality was always present). • As the crisis developed, the low and medium region of the data could only be fit to Gaussian functions. Distortion reached its maximum in May 2003 and returned to a more normal shape in 2004. • A Gaussian shape in the distribution is expected, according to model calculations, for the evolution of a system far from equilibrium.
Conclusions: • In the low and medium range, money follows BG distribution • This implies that a more egalitarian society (world) is obtained increasing the degeneracy (a). • The opposite holds if b increases. • The tail of the distribution shows fractal behaviour (Pareto power law) • The Tsallis function fits the whole range and should be considered (Richmond and Sabatelli(2003), Anazawa et al (2003)) • The distributions can be mono o polymodal, in equilibrium or not • BG distribution does not implies equilibrium (Shuler et al, 1964) • In the approach to equilibrium, the coldest partner wins (lower b) • Criteria for non equilibrium: 1) BG distribution with time dependent b 2) Gaussian shape
Predicting behaviours: Thermodinamical formulation for mono and multicomponent systems Model simulations of countries in crisis, like Argentina (time dependence)