THE METHOD OF TIME COMPONENT FOR FORECAST ESTIMATION OF THE GROSS REGIONAL PRODUCT OF THE VORONEZH REGION

DOI

10.24411/1816-1863-2019-11110

Section

Geoecology

Title

THE METHOD OF TIME COMPONENT FOR FORECAST ESTIMATION OF THE GROSS REGIONAL PRODUCT OF THE VORONEZH REGION

Сontributors
  1. N. V. Yakovenko, Ph. D. (Geography), Dr. Habil., Associate Professor, Head of the Department of Socio-economic Geography and Regional Studies,
  2. P. A. Kanapukhin, Ph. D. (Economics), Dr. Habil., Associate Professor, Head of the Department of Marketing,
  3. E.V. Mishon, Ph. D. (Economics), Dr. Habil., Professor of the Department of Labour Economics and Principles of Management,
  4. T. A. Romashchenko, Ph. D. (Economics), Dr. Habil., Professor of the Department of Economics, Marketing and Commerce,
  5. I.V. Komov, Ph. D. (Geography), Associate Professor of the Department of Socio-economic Geography and Regional Studies,
  6. R. V. Ten, Postgraduate of the Department of Socio-economic Geography and Regional Studies, Voronezh State University, e-mail.: This email address is being protected from spambots. You need JavaScript enabled to view it., Voronezh, Russia
Abstract

The analysis and forecasting of various factors of social and economic stability, parameters of competition and conditions of development of different spheres of the socio-economic system of the region are a necessary objective tool for assessing the level of social and economic development. Among these factors, the gross regional product (GRP) is one of the integrating indicators of regional economic development. It allows us to determine the place of the region in the territorial division of labor, to make interregional comparisons and to predict social and economic development. The research, aimed at developing the optimal mathematical tools for the regional level, has been carried out for a long period of time. However, there is still no adaptive calculation system. This is due to the methodological issues, the cause of which lies in the heterogeneity and limited comparability of socio-economic information.

The article deals with the issue of the analysis of the dynamics and forecasting the gross regional product (GRP), based on the method of time trends. One of the elements of the research novelty is the making of the correlation and regression equation of the GRP from a number of factors, the assessment of their significance, connection, as well as determining the possibility to use the model for the prediction of the GRP. Based on statistical data, the GRP calculations applying an additive time series model have been carried out.

Keywords

gross regional product (GRP), additive model, the Voronezh Region, correlation, dynamics analysis, forecasting

References
  1. Komov I. V., Yakovenko N. V. “Klaster” kak slozhnaya organizacionno-ekonomicheskaya sistema: podhody k definicii ponyatiya [“Cluster” as a complex organizational and economic system: approaches to the definition of the concept]. Izvestiya Tulskogo gosudarstvennogo universiteta. Nauki o Zemle. 2016. No. 1. P. 188—196. [in Russian]
  2. Yekovenko N. V. Konceptualnye aspekty formirovaniya i razvitiya klasterov v socialno-ekonomiko-geograficheskoj sisteme regiona [Conceptual aspects of the formation and development of clusters in the socio-economic and geographical system of the region] / N. V. YBkovenko, I. V. Komov, O. V. Didenko, E. A. Drobyshev. Regional Environmental Issues. 2015. No. 6. P. 61—66. [in Russian]
  3. YBkovenko N. V. Model ustojchivogo razvitiya i socialno-ekonomicheskij monitoring goroda [Sustainable development model and socio-economic monitoring of the city]. Regional Environmental Issues. 2010. No. 3. P. 118—126. [in Russian]
  4. Yakovenko N. V., Didenko O. V. Sovremenoe sostoyanie i prioritety v razvitii malogo i srednego predprinimatelstva Voronezhskoj oblasti [Current state and priorities in the development of small and medium-sized enterprises in the Voronezh Region]. Izvestiya Tulskogo gosudarstvennogo universiteta. Nauki o Zemle. 2017. No. 2. P. 186—195. [in Russian]
  5. Best M. Silicon Valley and the resurgence of Route 128: Systems integration and regional innovation. Ed. By J. Dunning. Regions, globalization, and the knowledge-based economy. Oxford, UK: Oxford University Press, 2000. P. 459—484. DOI: 10.1093/0199250014.001.0001.
  6. Kozinova A. T. Ekonometricheskij analiz valovogo vnutrennego produkta Rossii i ego vzaimosvyazej s in- vesticiyami v osnovnoj kapital, chislennostyu zanyatogo v ekonomike naseleniya, dobychej nefti i gaza [Econometric analysis of the gross domestic product of Russia and its interrelations with investments in fixed capital, the number of employed in the economy, oil and gas production]. Economic analysis: theory and practice. 2016. No. 2 (449). P. 183—196. [in Russian]
  7. Ismikhanov Z. N., Nazhmutdinova S. A., Abdulaev N. A. Trendovye modeli dlya prognozirovaniya socialno-ekonomicheskogo razvitiya regiona (na materialah Respubliki Dagestan) [Trend models for forecasting socio-economic development of the region: a case study of the Republic of Dagestan]. Economics and entrepreneurship. 2015. No. 3—2. P. 307—311. [in Russian]
  8. Nizhegorodtsev R. M., Piskun E. I., Kudrevich V. V. Prognozirovanie pokazatelej socialno-ekonom icheskogo razvitiya regiona. [Forecasting of indicators of social and economic development of the region]. Regional economy. 2017. Vol. 13. No. 1. P. 38—48. [in Russian]
  9. Federalnaya sluzhba gosudarstvennoj statistiki [Federal State Statistics Service]. Available at: http:// www.gks.ru/, date of access 12.12.2018.