Socio-Economic Forecasting Theory and Methodology: The Stages of Development in Russia
https://doi.org/10.55959/MSU2070-1381-110-2025-73-86
Abstract
The article reviews the development of the theory and methodology for forecasting socio-economic development in Russia, with the aim of identifying the main stages in the formation and transformation of regional forecasting methodologies. The analysis of theoretical propositions and methodological approaches is used to describe the current place of forecasting within the system of strategic planning for socio-economic development at the regional level in the Russian Federation. Through historical analysis and a comparative analysis of scientific research and regulatory documents, four key stages in the evolution of the theory and practice of socio-economic forecasting are identified. The criteria for determining the time limits of the stages have been chosen: the focus on scientific research on socio-economic forecasting and the development of new forecasting methods. The article also briefly describes the current three-level system of socio-economic forecasting, which is based on normative documents at the federal and regional levels. It also defines the key functions and characteristics of long-term and medium-term regional forecasting in the Russian Federation at the current stage.
About the Author
Ekaterina V. Gokhshtand
School of Public Administration, Lomonosov Moscow State University
Russian Federation
Russian Federation
Ekaterina V. Gokhshtand, Postgraduate student,
Moscow.
References
1. Agafonkin G.A., Beliaeva A.A., Kazimirov D.D., Lebed I.C. (2024) Neural network methodology for forecasting the dynamics of socio-economic indicators under sanctions pressure. Novyye vyzovy i formaty ustoychivogo ekonomicheskogo razvitiya v period neopredelennosti: rossiyskiy i zarubezhnyy opyt: II Sbornik nauchnykh statey po rezul’tatam IV mezhdunarodnoy nauchno-prakticheskoy konferentsii «Postroyeniye sistem upravleniya ustoychivym razvitiyem territorii» (April 25–27, 2024) i X yubileynoy nauchno-prakticheskoy konferentsii «Vladimirskiy trakt — doroga k novym tekhnologiyam v turizme» (June 21–24, 2024). Moscow: Ekonomicheskiy fakul’tet MGU imeni M.V. Lomonosova. P. 7-20.
2. Aganbegyan A.G. (2019) Analysis and Forecasting of Socio-Economic Development of Regions (Methodical Notes). Srednerusskiy vestnik obshchestvennykh nauk. Vol. 14. No. 4. P. 15–28. DOI: 10.22394/2071-2367-2019-14-4-15-28
3. Albegov M.M. (ed.) (2001) Kratkosrochnoye prognozirovaniye regional’nogo razvitiya v usloviyakh nepolnoy informatsii [Short-term forecasting of regional development in conditions of incomplete information]. Moscow: Editorial USS.
4. Armstrong J., Green K.C. (2018) Forecasting Methods and Principles: Evidence-Based Checklists. Journal of Global Scholars of Marketing Science. Vol. 28. Is. 2. P. 103–159. DOI: 10.1080/21639159.2018.1441735
5. Auzan A.A. (2015) Strategy for Long-Term Development of Russia: Novelty of Approach. Nauchnyye trudy Vol’nogo ekonomicheskogo obshchestva Rossii. Vol. 196. No. 7. P. 229–241.
6. Bazarov V.A. (1928) Printsipy postroyeniya perspektivnogo plana [Principles of constructing a long-term plan]. Planovoye khozyaystvo. No. 2. P. 38–63.
7. Biankina A.O., Lyasnikov N.V. (2018) N. Kondratiev’s Scientific Heritage as a Basis for Forecasting the Global Economic Trends of the 21st Century. Gosudarstvennoye upravleniye. Elektronnyy vestnik. No. 67. P. 170–180.
8. Bozhenova S.I. (2016) V. A. Bazarov and His View of the Perspective Plan Construction. Izvestiya Sankt-Peterburgskogo gosudarstvennogo ekonomicheskogo universiteta. No. 3(99). P. 110–114
9. Denton F.T., Spencer B.G. (2003) Population Change and Economic Growth: The Long Term Outlook. Quantitative Studies in Economics and Population Research Reports. No. 383.
10. Elliott R.J.R., Schumacher I., Withagen C. (2020) Suggestions for a Covid-19 Post-Pandemic Research Agenda in Environmental Economics. Environmental and Resource Economics. Vol. 76. P. 1187–1213l. DOI: 10.1007/s10640-020-00478-1
11. Gvozdetskiy V. (2001) Plan GOELRO. Mify i real’nost’ [The GOELRO plan. Myths and reality]. Nauka i zhizn’. No. 5. P. 102–109.
12. Izmalkova S.A., Golovina T.A. (2015) Use of the Global Technologies «Big Data» in Management of Economic Systems. Izvestiya Tul’skogo gosudarstvennogo universiteta. Ekonomicheskiye i yuridicheskiye nauki. No. 4–1. P. 151–157.
13. Jantsch E. (1969) New Organizational Forms for Forecasting. Technological Forecasting. Vol. 1. Is. 2. P. 151–161.
14. Jantsch E. (1970) From Forecasting and Planning to Policy Sciences. Policy Sciences. Vol. 1. Is. 1. P. 31–47.
15. Khurshid A., Khan Kh. (2021) How COVID-19 Shock Will Drive the Economy and Climate? A Data-Driven Approach to Model and Forecast. Environmental Science and Pollution Research. Vol. 28. Is. 3. P. 2948–2958. DOI: 10.1007/s11356-020-09734-9
16. Kondrat’yev N.D. (1927) Plan i predvideniye: K voprosu o metodakh sostavleniya perspektivnykh planov razvtiya narodnogo khozyaystva i sel’skogo khozyaystva v chastnosti [Plan and forecasting: On the question of methods of drawing up long-term plans for the development of the national economy and agriculture in particular]. Puti sel’skogo khozyaystva. No. 2. P. 3–36.
17. Kuznetsova V.G. (2019) V.G. Groman and the Transition to a Planned Economy in the USSR in the 1917–1930. Nauchnyy dialog. No. 11. P. 354–365. DOI: 10.24224/2227-1295-2019-11-354-365
18. Len’kov R.V (2000) Model’ otsenki rezul’tatov sotsial’nogo monitoringa dlya protsessa prinyatiya resheniy [A model for evaluating the results of social monitoring for the decision-making process]. Sbornik “Aktual’nyye problemy upravleniya — 2000”. Moscow: Gosudarstvennyy universitet upravleniya. P. 173–176.
19. Leonova N.G. (2023) Analysis of Scientific Approaches to the Study of Interregional Socio-Economic Differentiation: Historical, Socio-Cultural, and Systemic Approaches. Ekonomika, predprinimatel’stvo i pravo. Vol. 13. No. 11. P. 4701–4718. DOI: 10.18334/epp.13.11.119873
20. Makarov S.A. (2020) Foresight and Long-Term Strategy of Regional Development: The Republic of Tatarstan Case. EKO. No. 5(551). P. 175-191. DOI: 10.30680/ECO0131-7652-2020-5-175-192
21. Makasheva N., Samuels W.J., Barnett V. (eds.) (1998) The Works of Nikolai D. Kondratiev. London: Pickering &Chatto.
22. Maklakova E.A. (2015) Historical Background of Developing the Russian Modern System of Strategic Planning. Vestnik Leningradskogo gosudarstvennogo universiteta im. A.S. Pushkina. Vol. 6. No. 4. P. 132–138.
23. Rapach D.E., Strauss J.K., Zhou G. (2010). Out-Of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy. Review of Financial Studies. Vol. 23. Is. 2. P. 821–862. DOI: 10.1093/rfs/hhp063
24. Titova I.N., Glotova A.S. (2020) Variable Forecasting of the Socio-Economic Development of the Region. Vestnik Volgogradskogo gosudarstvennogo universiteta. Ekonomika. Vol. 22. No. 1. P. 35–43. DOI: 10.15688/ek.jvolsu.2020.1.4
25. Tsydypova T.B. (2013) Scientific-Methodological Approaches to Detection of a Social and Economic Forecasting. Statistika i matematicheskiye metody v ekonomike. No. 1. P. 172–176.
26. Vanchikova E.N., Arkhipova M.Yu. (2015) Socio-Economic Forecasting Function as a Regional Management. Vestnik Buryatskogo gosudarstvennogo universiteta. No. 3. P. 42–48.
27. Yoon J. (2021) Forecasting of Real GDP Growth Using Machine Learning Models: Gradient Boosting and Random Forest Approach. Computational Economics. Vol. 57. P. 247–265. DOI: 10.1007/s10614-020-10054-w
28. Zemtsov S.P., Baburin V.L. (2020) Coronavirus in the Regions of Russia: Features and Consequences of the Spread. Gosudarstvennaya sluzhba. Vol. 22. No. 2 (124). P. 48–55. DOI: 10.22394/2070-8378-2020-22-2-48-55
Review
For citations:
Gokhshtand E.V. Socio-Economic Forecasting Theory and Methodology: The Stages of Development in Russia. Public Administration. E-journal (Russia). 2025;(110):73-86. (In Russ.) https://doi.org/10.55959/MSU2070-1381-110-2025-73-86
Views:
66
JATS XML
Email this article 