ECONOMIC AND MATHEMATICAL MODELS FOR RATIONAL SIZES OF AGRICULTURAL ENTERPRISES DETERMINATION

Abstract

The aim of the article is to build a stochastic economic and mathematical model for determining the rational size of agricultural enterprises. It has been shown that in the context of digitalization, the methodological basis for rationalizing the size of agricultural enterprises is economic and mathematical models that allow not only to simulate the impact of factors, but also to determine the most optimal combination of them for specific economic conditions and forms of ownership. It has been identified that most studies focus mainly on modeling the rational organization of land use, optimization of the size and structure of sown areas, factor analysis of concentration, including the use of production functions, or comparative and DEA analysis of the efficiency of agricultural enterprises of different sizes. It has been confirmed that the determination of the rational size of agricultural enterprises should be based on the results of their distribution by types of specialization and on the basis of a comprehensive economic, environmental and social assessment of the economic output. The scale effect in agriculture is a dynamic value, since for each individual period of time there is a maximum possible (marginal) volume of production that can be achieved with the given costs of production factors. It has been argued that the methodology of stochastic frontier analysis is an effective tool for optimizing the size of agricultural enterprises, allowing taking into account both the main factors of production and to include stochastic dummy variables in the model. Based on the actual data on the results of enterprises' economic activity, the stochastic frontier analysis allows to estimate the current level of production and to make optimization calculations taking into account the best option for the development of the economic system. It has been emphasized that in order to increase the reliability of the results gained and generalize the best practices of agricultural production, it is advisable to use the data envelopment analysis method based on super-efficiency models and the algorithm for selecting advanced farms, which is based on finding the intersection of sets of agricultural enterprises according to DEA models with constant and variable economies of scale regardless of their orientation.