Non-Linear Models in Economic and Social Research

Abstract

The article shows differences of presented models from models used in exact science. It analyzes the reasons why for mathematic models of economic and social systems we cannot reach the quantitative correlation of modeling results with indicators of real processes. The article discusses the qualitative identity of non-linear effects in mathematic models and real processes in natural scientific, economic and social systems. Irremovable uncertainty of economic and social system behavior and connected with this uncertainty chaotic component were shown as an integral feature of complicated system evolution. For simple natural scientific systems chaotic behavior is only one of possible forms of the dynamic process in line with determined behavior. For complicated systems a chaotic component is dominating. The author explains the impossibility and inefficiency of detailing and formalizing of economic and social system functioning above a certain level. The impact of initial data quality on results of modeling systems with different level of complexity was shown. The author proposes to use the concept of the strange attractor for substantiating the depth of planning and reporting in economic and social systems. Issues of self-organization and depth of forecasting for complicated system are studied. This information is considered to be a tool for managing economic and social systems. Promising variants of developing mathematic modeling in economic and social systems are analyzed.