Probability Economics: Supply and Demand, Price and Force in the Price-Quantity Space

Abstract

This essay is the sequel of a series of articles we have written, dedicated to the elaboration of a complex of fundamentally new economic models, which we named probability economics. In all of these models we implement the concept of uncertainty and probability, step by step. Specifically, in this paper we set out the General Stationary Probability Price-Quantity Space Model, which is an important generalization of the simple Stationary Probability Price Space Model, developed by the author in previous works. This generalization is carried out as follows. For each good traded in the L-good market of an economy, we treat price and quantity as two independent variables and then introduce into the theory the idea of the (2 x L)-dimensional “price-quantity” space by analogy with the price space of the simple model. In other words, the concept of uncertainty and probability of a buyer’s and seller’s choice in the market is equally applied to the price and quantity of goods. Thus, supply and demand functions of both individual agents and the market as whole are (2 x L + 1)-dimensional surfaces within the framework of the General Stationary Probability Price-Quantity Space Model. The probabilistic nature of an agent’s quantity choice significantly changes the meaning of supply and demand functions as well as significance and numerical values of market forces and prices. In addition, taking into account these quantity freedom degrees significantly expands the scope of application of the probability economics for description of market phenomena. Therefore, probability economics, as it was already clarified in previous works, is positioned by us as a new quantitative method for description, analysis, and investigation of the model, as well as real economies and markets. This article is primarily addressed to those interested in the background of economics, with a specific interest in the axiomatic basis for modern economic theory.