The article investigates uneven spatial development of the livestock industry in Russia’s regions. It is caused by many factors, including the volume of attracted investments, human resources; and it endangers the food security of territories. The purpose of the study is to assess spatial heterogeneity in the development of the livestock industry in the Sverdlovsk Oblast. To achieve the goal, we set the following tasks: to conduct a spatial autocorrelation analysis of the development of the livestock industry in Sverdlovsk Oblast municipal entities, investigate the impact of human resources investments and costs on the development of spatial heterogeneity in the region’s livestock industry, assess the spatial effects of livestock industry development in territorial systems, design forecast scenarios for its development in the region’s municipal entities up to 2025. Having reviewed theoretical and methodological approaches to assessing spatial heterogeneity at the regional and municipal levels we find out that Russian and foreign researchers use a variety of methods. Their application does not contribute to the comprehensive assessment of spatial heterogeneity in the development of the livestock industry. To solve the problem, we propose a methodological approach, whose novelty consists in the comprehensive application of spatial autocorrelation analysis methods using various matrices of spatial weights, regression analysis using panel data and ARIMA modeling which, when combined, make it possible to determine the impact of investments and other factors on heterogeneity in the development of the livestock industry in the region’s municipalities and design a system of various forecast scenarios. The regression models we constructed have confirmed the differentiated impact of investments and human resources on spatial heterogeneity in the livestock sector in the Sverdlovsk Oblast and outlined the prospects for its development
Keywords
investments, spatial autocorrelation, ARIMA modeling, livestock industry, spatial heterogeneity, Cobb – Douglas production function, scenario forecasting