Generalization of the Aoki-Yoshikawa sectoral productivity model based on extreme physical information principle

This paper presents a continuous variable generalization of the Aoki-Yoshikawa sectoral productivity model. Information theoretical methods from the Frieden-Soffer extreme physical information statistical estimation methodology were used to construct exact solutions. Both approaches coincide in first order approximation. The approach proposed here can be successfully applied in other fields of research.

The intensity of the random variable intercept in the sector of negative probabilities

We consider properties of the measurement intensity $rho$ of a random variable for which the probability density function represented by the corresponding Wigner function attains negative values on a part of the domain. We consider a simple economic interpretation of this problem. This model is used to present the applicability of the method to the analysis of the negative probability on markets where there are anomalies in the law of supply and demand (e.g. Giffens goods). It turns out that the new conditions to optimize the intensity $rho$ require a new strategy. We propose a strategy (so-called $grave{a}$ rebours strategy) based on the fixed point method and explore its effectiveness.