A. N. Gerasimov, E. I. Gromov, Yu. S. Skripnichenko, O. P. Grigoryeva, V. Yu. Skripnichenko. Models and Forecasts of the Export Potential of the Regional Economic System

UDК 332.122

doi: 10.15507/2413-1407.121.030.202204.762-782

Abstract

Introduction. The export potential of the regional agricultural market causes great interest from both the scientific community and government agencies. Many scientific studies are devoted to the search for methods to increase the export potential in order to ensure the sustainable development of regional economic systems. The article proposes and tests the original author’s algorithm for creating a dynamic econometric model for forecasting the volumes of production, sales and exports of the main types of livestock products at the regional level. The purpose of the article is to assess the export potential of the main products of the regional agricultural market based on the built dynamic econometric models.

Materials and Methods. The research is based on a set of empirical data of result and input variables characterizing the production, sales and export of the main livestock products in the region for the period 2010–2020. Research methods include dynamic analysis, econometric modeling and forecasting. The dynamic analysis carried out made it possible to assess the change in the production, sale and export of the main agricultural products in the region, to assess the current trends. Based on the constructed econometric models, the most significant factors influencing the resulting variables were identified, the specifications and verification of the models were carried out. The method of extrapolation of the identified trends made it possible to evaluate the predicted values of the resulting variables for the medium term.

Results. Based on the selected input variables, models of production, sale and export of milk, wool and eggs by agricultural producers in the region were built. From a variety of alternative models, models with the best statistical quality characteristics were selected. The high level of quality of the obtained models made it possible to use them for predictive calculations of the levels of resulting variables for the period 2021–2026. Comparison of the results of the forecasts made it possible to identify the types of livestock products that already have a high level of exportability. In addition, types of products with a low level of exportability were identified, which have a high potential for increase.

Discussion and Conclusion. As a result of using econometric modeling methods, dynamic models were obtained that made it possible to obtain a forecast for the development of livestock in a region with a high export potential in the near future. The practical significance of this article lies in the possibility of influencing the production, sale and export of livestock products in the region through a change in the corresponding set of factor variables of the models. Thus, the resulting dynamic models can be used both by agricultural producers for planning economic activities, and by regional authorities when drawing up regional development programs.

Keywords: dynamic econometric models, forecasting, regional livestock market, export potential of the region

Conflict of interests. The authors declare that there is not conflict of interest.

For citation: Gerasimov A.N., Gromov E.I., Skripnichenko Yu.S., Grigoryeva O.P., Skripnichenko V.Yu. Models and Forecasts of the Export Potential of the Regional Economic System. Regionology. Russian Journal of Regional Studies. 2022;30(4):762–782. doi: https://doi.org/10.15507/2413-1407.121.030.202204.762-782

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Submitted 14.04.2022; approved after reviewing 23.06.2022; accepted for publication 08.07.2022.

About the authors:

Aleksey N. Gerasimov, Head of the Department of Economic Security, Statistics and Econometrics, Stavropol State Agrarian University (12 Zootekhnichesky lane, Stavropol 355017, Russian Federation), Doc. Sci. (Economics), Professor, ORCID: https://orcid.org/0000-0002-1244-4755, Researcher ID: N-2675-2015, Scopus ID: 55978039600, gerasimov_77_77@mail.ru

Evgeny I. Gromov, Professor of the Department of Economic Security, Statistics and Econometrics, Stavropol State Agrarian University (12 Zootekhnichesky lane, Stavropol 355017, Russian Federation), Doc. Sci. (Economics), Professor, ORCID: https://orcid.org/0000-0001-5921-6752, Researcher ID: E-3929-2016, Scopus ID: 55977663300, gromei@mail.ru

Yury S. Skripnichenko, Associate Professor of the Department of Economic Security, Statistics and Econometrics, Stavropol State Agrarian University (12 Zootekhnichesky lane, Stavropol 355017, Russian Federation), Cand. Sci. (Economics), Associate Professor, ORCID: https://orcid.org/0000-0002-7625-5603, Researcher ID: E-3588-2016, Scopus ID: 56328627800, maxim-84@list.ru

Oksana P. Grigoryeva, Associate Professor of the Department of Economic Security, Statistics and Econometrics, Stavropol State Agrarian University (12 Zootekhnichesky lane, Stavropol 355017, Russian Federation), Cand. Sci. (Economics), Associate Professor, ORCID: https://orcid.org/0000-0002-0358-5492, Researcher ID: Т-4204-2018, Scopus ID: 57218949918, ksuta_stav@mail.ru

Victoria Yu. Skripnichenko, Assistant of the Department of Economic Security, Statistics and Econometrics, Stavropol State Agrarian University (12 Zootekhnichesky lane, Stavropol 355017, Russian Federation), ORCID: https://orcid.org/0000-0003-0258-6829, Researcher ID: GRS-3759-2022, Scopus ID: 57224408944, viktoriya.shumskaya@gmail.com

Contribution of the authors:

A. N. Gerasimov – setting the goal and objectives of the study; dynamic analysis; extrapolation; substantiating the conclusions of the study.

E. I. Gromov – collection and aggregation of information; data analysis; specification of econometric models.

Yu. S. Skripnichenko – description of econometric modeling results; assessment of predictive values of indicators; critical analysis and revision of the text.

O. P. Grigoryeva – substantiation of the research methodology; development of an algorithm for predictive calculations.

V. Yu. Skripnichenko – literature review; formulation of conclusions.

The authors have read and approved the final version of the manuscript.

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