Acta Scientific Agriculture (ASAG)(ISSN: 2581-365X)

Review Article Volume 7 Issue 1

Assessment Method the Development of Agriculture in the Region

Ivanova Tatiana* and Ivanova Anna

Department of Research Center for Labor Economic, FSBEI HE "Russian University of Economics named after G.V. Plekhanov", Russian Federation

*Corresponding Author: Ivanova Tatiana, Department of Research Center for Labor Economic, FSBEI HE "Russian University of Economics named after G.V. Plekhanov", Russian Federation.

Received: June 29, 2022; Published: December 22, 2022


The article developed a universal method for assessing the pace of agricultural development (on the example of the Chuvash Republic). Its algorithm includes the following actions: 1) index analysis of the main economic indicators related to the functioning of the region's agriculture for 2011-2020; 2) development of a formula for calculating an integral indicator characterizing their changes; 3) determining the pace of development of the industry. Next, the forecast for three scenarios (optimistic, probabilistic and pessimistic) for 2021–2023 is presented, and for the optimistic one, confidence intervals of the predicted values of the integral indicator characterizing the pace of agricultural development are calculated. This technique mathematically supports and economically substantiates the effectiveness of managerial decision-making related to the development of strategies, projects and programs for the development of agriculture in the Chuvash Republic.

Keywords: Chuvash Republic; Agriculture, Forecasting; Assessment Method; Integral Indicator; Development


  1. Albeaik S., et al. “729 new measures of economic complexity. (Addendum to Improving the Economic Complexity Index)” (2017).
  2. Bongiorno EG and Goia A. “Describing the concentration of income populations by functional principal component analysis on Lorenz curves”. Journal of Multivariate Analysis 170 (2019): 10-24.
  3. Brummitt CD., et al. “Machine-learned patterns suggest that diversification drives economic development”. Journal of the Royal Society Interface (2018).
  4. Brunton SL., et al. “Discovering governing equations from data by sparse identification of nonlinear dynamical systems”. Proceedings of the National Academy of Sciences of the United States of America15 (2016): 3932-3937.
  5. Hruschka DJ., et al. “Material wealth in 3D: Mapping multiple paths to prosperity in low- and middle- income countries”. PloS One9 (2017): e0184616.
  6. Ivanova T., et al. “Forecasting agricultural production as a tool for effective industry management (on the example of the Chuvash Republic)”. Smart Innovation, Systems and Technologies (Springer) 247 (2022): 393-402.
  7. Ivanova T., et al. “Methodology for assessing the rates of reproduction social infrastructure of agriculture”. E3S Web of Conferences 291 (2021): 05035.
  8. Ivanova T., et al. “Forecasting the development of social infrastructure agriculture of the Chuvash Republic”. E3S Web of Conferences (EDP Sciences) 291 (2021): 05031.
  9. Lou Y., et al. “Sparse Partially Linear Additive Models”. Journal of Computational and Graphical Statistics4 (2016): 1126-1140.
  10. Minina NN. “Formation of equity capital of agricultural organizations of the Republic of Belaru”. Achievements of Science and Technology of the Agro-Industrial Complex1 (2018): 50-56.
  11. Orlov V., et al. “Assessment of the influence of social factors on reproduction of personnel potential in agriculture of Russia, PbWOSCE-2018: Business technologies for sustainable urban development”. E3S Web Conference (2019): 110.
  12. Orlov V., et al. “Mathematical modeling of economic factors impact: reproduction of personnel potential in agriculture sector of Russia”. IOP Conference Series: Earth and Environmental Science (2020): 433.
  13. Orlov V., et al. “Mathematical modeling in forecasting reproduction processes in agriculture”. Lecture Notes in Networks and Systems (Atlantis Press) 246 (2022): 330-338.
  14. Tacchella A., et al. “A dynamical systems approach to gross domestic product forecasting”. Nature Physics 8 (2008): 861-865.
  15. Tahamipour M and Mahmoudi M. “The role of agricultural sector productivity in economic growth: the case of Iran’s economic development plan”. Macrothink Institute: Research in Applied Economics 10.1 (2018).
  16. Tyapkina M. “Consumption as the main element of the reproduction process in agriculture”. International Scientific and Practical Conference "Agriculture and Food Security: Technologies, Innovations, Markets, Human Resources" (FIES 2019). BIO Web of Conferences 17 (2020): 00240.
  17. Materials of the Federal Service of State Statistics [Electronic Resource].
  18. Stavtsev AN and Miroshnikov GA. “State support for the renewal of the material and technical base of the agro-industrial complex of the Republic of Belarus”. RJOAS49 (2016).


Citation: Ivanova Tatiana and Ivanova Anna. “Assessment Method the Development of Agriculture in the Region". Acta Scientific Agriculture 7.1 (2023): 53-57.


Copyright: © 2023 Ivanova Tatiana and Ivanova Anna. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


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