Key Indicators of a Complex Economic System Forecast

Abstract

One of the necessary components in the tasks of improving business efficiency is the forecasting of key indicators of economic activity. A large number of different indicators are complex related, and the result of a change in a single indicator or group entails changes in other indicators, which is typical for a large enterprise. The purpose of the work is to propose methods and analytical tools for forecasting key indicators of a complex economic system. A hybrid approach to forecasting a complex economic system has been developed which makes it possible to forecast individual technical and economic indicators, taking into account the dynamics and trends in the entire set of indicators reflecting various aspects of the enterprise's activities. The proposed methodology combines several approaches and contains a number of limitations. At the first stage, a complex system of indicators is decomposed into groups. For each group of indicators, systems of simultaneous equations of multiple regression are determined. Next, the selection of regression models is carried out using regression statistics and economically justified restrictions. Regression models for each indicator are complemented by adaptive model. Synthesis of the result is obtained as a moving average of the forecast. The proposed instrumental methods of analysis are recommended as analytical tools for business analysis for various purposes. Approbation of the proposed analytical forecasting tools according to official reporting data was carried out on a case study of estimating the cost of three large industrial enterprises of the sugar industry in the Volga Federal District.