E3S Web Conf.
Volume 175, 2020XIII International Scientific and Practical Conference “State and Prospects for the Development of Agribusiness – INTERAGROMASH 2020”
|Number of page(s)||11|
|Section||Agricultural Planning and Economics|
|Published online||29 June 2020|
Prospects for development of Russian agricultural industry in the context of export-oriented strategy implementation in the agro-industrial complex
The Federal agrarian scientific center of Rostov, All-Russian Research Institute of Economics and Standards, 41, st. Chehova, 344006, Rostov-on-Don, Russia
2 Don State Technical University, 1, pl. Gagarina, 344002, Rostov-on-Don, Russia
3 Rostov State University of Economics (RSUE), 69, st. Bolshaya Sadovaya, 344002, Rostov-on-Don, Russia
* Corresponding author: firstname.lastname@example.org
The research concept consists in the development of theoretical and empirical approaches for analysis and assessment of Russian agricultural production development trends in the context of exportoriented strategy implementation in the agro-industrial complex. The research is conducted using complex of methods of mathematical modeling in economics, including extrapolation methods (linear and non-linear trend models for analyzing the time dynamics of production and economic variables), scenario forecasting, Delphi approach. The projected parameters of the export potential of Russian agricultural production are developed and represented in the paper. Based on the data of 2009-2018, the development state is analyzed and trends become visible of the farm stock structure by farming categories in the Russian Federation and staple food production, including meat, milk, vegetables, potatoes, grain and sunflower. Three forecasting scenarios of staple food production per capita in the Russian Federation for the period up to 2025 are developed and proved (base case, best-case and worst-casescenarios).
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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