Guzel Salimova, Alisa Ableeva, Gamir Khabirov, Zariya Zalilova, Tatiana Lubova, Elena Kabashova, Aidar Sharafutdinov, Gulnaz Valieva, Liana Saifutdinova
Federal State Budgetary Educational Establishment of Higher Education “Bashkir State Agrarian University”, Ufa 450001, Bashkortostan, Russia
Salimova, G., Ableeva, A., Khabirov, G., Zalilova, Z., Lubova, T., Kabashova, E., Sharafutdinov, A., Valieva, G., & Saifutdinova, L. (2019). Labour productivity in agricultural production system: the case of Russia. Bulgarian Journal of Agricultural Science, 25 (Suppl. 2), 206–216
The article presents the results of a complex space-time empirical study of labour productivity in agriculture of the Russian Federation as an indicator of production efficiency. The index analysis of factors influence on the size of production volume of branch and level of labour productivity in dynamics was carried out. The increase in the cost of agricultural produce in the Russian Federation was due to the growth of labour productivity. The share of workers of agricultural enterprises in the regions, which have reached the highest level of productivity and efficiency, is increasing. As a result of grouping the Russian Federation regions on the level of labour productivity in agriculture and summary data on subjects with the maximum and minimum level of efficiency of agricultural production, the generalized characteristics of prospects of increase in labour productivity are received. The trend of changing in this indicator generally reflects changes in other indicators of production. However, the increase in labour productivity is not followed by a corresponding increase in wages. The choice of exogenous variables is substantiated and correlation and regression models of labour productivity are constructed. The analysis of the dependence of the level of labour productivity on the factors led to the conclusion that the course chosen in modern conditions for technical equipment, the introduction of digital technologies in crop and livestock production, elements of precision farming while maintaining the identified patterns will lead to increased productivity in agriculture.