BIO Web Conf.
Volume 37, 2021International Scientific-Practical Conference “Agriculture and Food Security: Technology, Innovation, Markets, Human Resources” (FIES 2021)
|Number of page(s)||5|
|Published online||27 October 2021|
Scenario forecasting of the economic effects of agricultural modernization in digital economy
1 Kazan State Agrarian University, Kazan, 420015, Russia
2 Kaluga branch of Financial University under the Law of the Russian Federation, Kaluga, 248016, Russia
3 Kursk State University, Kursk, 305000, Russia
4 Southwest State University, Kursk, 305021, Russia
* Corresponding author: firstname.lastname@example.org
This paper studies the international models of digital development of the agricultural sector of economy and its structural elements used in the emerging models of innovative development of the Russian Federation. Various scenarios of forecasting of the economic effects of agricultural production development are presented. It allowed drawing a conclusion about the low level of compliance of digital economy with the necessary science-intensive indicator of gross domestic product, which requires radical government intervention and the reorganization of economy as a whole. It is possible to state that, first of all, it is necessary to create an appropriate theoretical knowledge base, using which it would be possible to carry out the process of training the necessary skills and competencies in the development of digital economy in Russian universities. International exchange of students and post graduate students is also extremely productive in terms of the development of new technologies. This is illustrated by the US agrarian statistical analysis in the field of modernization effects. Thus, the problem of scenario forecasting of the economic effects of agricultural modernization in digital economy is quite relevant and requires additional scientific research in this direction.
© The Authors, published by EDP Sciences, 2021
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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