FOREIGN APPROACHES TO IDENTIFYING IMBALANCES IN AGRICULTURAL WORKFORCE SUPPLY
DOI 10.33305/257-132
Issue № 7, 2025, article № 14, pages 132-138
Section: ABROAD
Language: Russian
Original language title: ЗАРУБЕЖНЫЕ ПОДХОДЫ К ВЫЯВЛЕНИЮ ДИСБАЛАНСОВ В КАДРОВОМ ОБЕСПЕЧЕНИИ СЕЛЬСКОГО ХОЗЯЙСТВА
Keywords: WORKFORCE SUPPLY, AGRICULTURE, LABOR MARKET IMBALANCES, FOREIGN APPROACHES, ECONOMETRIC MODELING, REGIONAL CHARACTERISTICS, LABOR RESOURCES, EDUCATIONAL PROGRAMS, MIGRATION
Abstract: The article is devoted to the analysis of foreign approaches to identifying imbalances in agricultural workforce supply, which is a pressing issue for many countries, including Russia. The study examines the main methodological approaches to assessing labor demand and supply, as well as identifying regional imbalances. The analysis of approaches to assessing agricultural labor needs abroad suggests that they can be adapted to Russian conditions. The use of statistical methods and econometric models is most effective in evaluating workforce needs and the effectiveness of educational programs. The experience of Australia in macroeconomic forecasting using the MONASH model, which takes into account technological changes and demographic trends, as well as the experience of EU countries in creating integrated data collection systems, such as Labour Market Information Systems and the CEDEFOP model, can be useful for adapting educational programs to the needs of the industry at the regional level. These systems make it possible to forecast professional and qualification imbalances and adjust educational programs in accordance with the real needs of the labor market. Taking into account regional characteristics, as in China, where labor supply analysis considers climatic and geographical factors, and analyzing the role of labor migration, as in the UK, can also be applied to develop targeted measures to support agriculture in Russia and address interregional differences in workforce supply for agricultural enterprises.
Authors: Sedova Nadezhda Vasilevna