Labour productivity in agricultural production system: the case of Russia
Keywords:
production efficiency, agriculture, labour productivity, wages, performance indicators, activities, complex analysisAbstract
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.
References
Ableeva, A. M., Salimova, G. A. & Zalilova, Z. A. (2017). Factors and reserves of increase of efficiency of agricultural production. International Journal of Applied Engineering Research, 12(24), 15821-15829.
Aganbegyan, A. G. (2017). Investments in fixed assets and human capital: Two interconnected drivers of socioeconomic growth. Studies on Russian Economic Development, 28(4), 361-363.
Arefiev, N. G., Kuznetsov, S. A. & Ponomarev, K. A. (2015). How can we estimate causal relationships from observed correlations? Comparison of approaches used in economics and computer science. Economic Journal of Higher School of Economics, 19(3), 457-496.
Ayvazyan, S. A. & Afanasyev, M. Y. (2015). Assessment of innovative activity of regions in the Russian Federation. Journal of Economics, 1, 7.
Blanc, S., Brun, F. & Di Vita, G. (2018). Traditional beekeeping in rural areas: profitability analysis and feasibility of pollination service. Quality – Access to Success, 19, 72-79.
Brezis, E. S. & Gilad, B. (2018). Productivity gap between sectors and double duality in labour markets. Open Economies Review, 29(4), 725-749.
Danko, T. P., Ekimova, K. V., Bolvachev, A. I., Zarova, E. V., Shemetkova, O. L., Solovyova, M. G. & Sekerin, V. D. (2016). Assessment of the competitive potential of the region through an integrated system of rating positioning. International Journal of Economic Research, 13(6), 2361-2367.
De Pinto, A., Li, M., Haruna, A., Kwon, H.-Y., Hyman, G. G., Creamer, B., Garcia, J. B. V., Tapasco, J., Martinez, J. D. & Martinez, M. A. L. (2016). Low emission development strategies in agriculture. An agriculture, forestry, and other land uses (afolu) perspective. World Development, 87, 180-203.
Emran, S. & Shilpi, F. (2018). Agricultural productivity, hired labour, wages, and poverty: Evidence from Bangladesh. World Development, 109, 470-482.
Featherstone, A. M. (2018). The farm economy: future research and education priorities. Applied Economic Perspectives and Policy, 40(1), 136-154.
Gabitov, I. I., Mudarisov, S. G., Ismagilov, R. R., Asylbaev, I. G., Gafurov, I. D. & Ableeva, A. M. (2014). System of machinery and equipment for the implementation of innovative technologies in crop production and livestock breeding in the Republic of Bashkortostan. Ministry of agriculture of the Russian Federation, Ministry of agriculture of the Republic of Bashkortostan, Bashkir State Agrarian University, National Academy of Sciences of Belarus, Scientific and Practical Center of the National Academy of Sciences of Belarus on agricultural mechanization. Ufa.
Gabitov, I. I., Badretdinov, I. D., Mudarisov, S. G., Khasanov, E. R., Lukmanov, R. L., Nasyrov, R. R., Tuktarov, M. F., Atnagulov, D. T., Timeriashev, I. A. & Pavlenko, V. A. (2018). Modelling the process of heap separation in the grain harvester cleaning system. Journal of Engineering and Applied Sciences, 13, 6517-6526.
Gallardo, R. K. & Sauer, J. (2018). Annual review of resource economics. Annual Review of Resource Economics, 10, 185-206.
Iqbali, N. & Sial, M. H. (2018). Semi-parametric analysis of agricultural production under dichotomy of inputs. Agricultural Economics-Zemedelska Ekonomika, 64(8), 378-388.
Lavrovskii, B. L. (2015). Russian and world trends in productivity. Studies on Russian Economic Development, 26(3), 278-284.
Lukmanov, D. D., Habirov, G. A., Kushubakova, B. K., Akhmadieva, A. F., Ismagilov, K. R., Fanisov, R. F., Iskuzhina, G. R., Valieva, G. R., Atazhanova, A. A. & Yumaguzhina, J. R. (2018). Private land ownership development and investments in the agrarian sector of emerging economies. Journal of Engineering and Applied Sciences, 13, 8760-8767.
Melin, H., Saari, T., Sippola, M., Efendiyev, A. G. & Balabanova, Е. S. (2018). Comparing Finnish and Russian work life. The World of Russia: Sociology, Ethnology, 27(2), 90-108.
Mkhitarian, V., Karelina, M. & Ivanova, T. (2016). Empirical analysis of the trend in mergers and acquisitions of Russian holding companies. Model Assisted Statistics and Applications, 11(1), 39-57.
Moutinho, V., Robaina, M. & Macedo, P. (2018). Economic-environmental efficiency of European agriculture – a generalized maximum entropy approach. Agricultural Economics – Zemedelska Ekonomika, 64(10), 423-435.
Mudarisov, S. (2017). Specifying two-phase flow in modelling pneumatic systems performance of farm machines. Journal of Mechanical Engineering Research and Developments, 40(4), 706-715.
Official Website of the Federal State Statistics Service: http://www.gks.ru
Pospelov, I. & Radionov, S. (2015). On the social efficiency in monopolistic competition models. Economic Journal of Higher School of Economics, 19(3), 386-394.
Quinones Pena, T., Paez Rodriguez, B. & Manuel Iglesias, C. (2018). Strategy to contribute to the agricultural professional orientation of adolescents in the community Manuel Sanguily. Avances, 20(1), 78-88.
Salimova, G. A. & Rafikova, N. T. (2007). Statistical study of the level of wages and its impact on production efficiency. Ufa.
Thaler, R. H. & Sunstein, C. R. (2008). Nudge: improving decisions about health, wealth, and happiness. Yale University Press.
Timofti, E., Tomita, P. & Popa, D. (2018). New approaches on the development of the methodology of the integral indicator for estimation of the resources potential and their range in agricultural entities. Scientific Papers – Series Management Economic Engineering in Agriculture and Rural Development, 18(2), 463-470.
Tinbergen, J. (1940). On a method of statistical business-cycle research: a reply. The Economic Journal, 50(197), 141-154.
Todorovska, E., Abu Mhadi, N. & Christov, N. (2018). Cereal genetics and genomics in Bulgaria – challenges and perspectives. Comptes Rendus de l Academie Bulgare des Sciences, 71(2), 143-160.
Yarullin, R., Aipov, R., Gabitov, I., Linenko, A., Akchurin, S., Safin, R., Mudarisov, S., Khasanov, E., Rakhimov, Z., Rakhimov, Z. & Masalimov, I. (2018). Adjustable driver of grain cleaning vibro-machine with vertical axis of eccentric masses rotation. Journal of Engineering and Applied Sciences, 13, 6398-6406.
Zinchenko, A. P. (2017). Studying the problems of economic reproduction in agriculture of Russia. Studies on Russian Economic Development, 28(2), 140-146.
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