Economic Analysis: Theory and Practice
 

Methodological approaches to forecasting the industrial development based on the simulation of economic agents' expectations

Vol. 16, Iss. 11, NOVEMBER 2017

Received: 23 August 2017

Received in revised form: 22 September 2017

Accepted: 23 October 2017

Available online: 29 November 2017

Subject Heading: ECONOMIC ADVANCEMENT

JEL Classification: B50, С02, C21, C22, C43

Pages: 2028–2042

https://doi.org/10.24891/ea.16.11.2028

El'shin L.A. University of Management TISBI, Kazan, Zelenodolsk, Republic of Tatarstan, Russian Federation Leonid.Elshin@tatar.ru

Importance Researching the mechanisms and methods of scenario-specific forecasting of socio-economic systems is an important scientific and methodological issue that is of particular relevance in the environment of dynamically developing and evolving external and internal factors. The article deals with their definition and identification, assesses specific impacts on future changes in the industrial development of the national economy.
Objectives The aim is to test the mechanisms for scenario modeling of industrial sectors of the Russian economy based on the assessment of expectations of economic agents generating transformation processes in the national economic system.
Methods I apply tools of cross-correlation analysis of major systemically important factors impacting the expectations of economic agents, and tools for designing probit and logit models and multiple choice models. The study also employs taxonomic analysis, indicative methods, etc.
Results I formulated methodological approaches to simulate the growth of industrial sectors of economy on the basis of assessment of expectations. Their testing enabled elaboration of estimates of Russian industrial development for the period up to 2020. The findings may be useful for public administration authorities to make short- and medium-term forecasts for the industrial development.
Conclusions and Relevance The findings revealed trends in the industrial growth of the national economy over the medium term, depending on designed scenarios for institutional environment development.

Keywords: scenario forecasting, industrial development, expectation, economic agent, modeling

References:

  1. Safiullin M., Elshin L., Prygunova M. Methodological approaches to forecasting the mid-term cycles of economic systems with the predominant type of administrative-command control. Journal of Economics and Economic Education Research, 2016, vol. 17, special iss. 2, pp. 277–287. URL: http://www.alliedacademies.org/articles/jeeer-special-issue-2.pdf
  2. Nelson C.R., Plosser C.I. Trends and Random Walks in Macroeconomic Time Series: Some Evidence and Implications. Journal of Monetary Economics, 1982, vol. 10, iss. 2, pp. 139–162. URL: https://doi.org/10.1016/0304-3932(82)90012-5
  3. Russell С., Russell W.M.S. Population Crises and Population Cycles. London, Galton Institute, 1999.
  4. Kondrat'ev N.D. Problemy ekonomicheskoi dinamiki [Problems of economic dynamics]. Moscow, Ekonomika Publ., 1989, 536 p.
  5. Suslov D.A. [Reproduction cycle of social and economic development of regions]. Statistika i Ekonomika = Statistics and Economics, 2008, no. 4, pp. 19–23. (In Russ.)
  6. Smirnov S.V., Frenkel' A.A., Kondrashov N.V. [Indexes of regional economic activity]. Voprosy Statistiki, 2016, no. 12, pp. 29–38. (In Russ.)
  7. Safiullin M.R., El'shin L.A., Shakirova A.I. Ob otsenke delovoi i ekonomicheskoi aktivnosti regiona [On assessment of business and economic activity of the region]. Moscow, Ekonomika Publ., 2011, 111 p.
  8. Dubovitskii S.V. [Forecasting the economic growth and financial dynamics under globalization and instability]. Obshchestvo i ekonomika = Society and Economics, 2005, no. 3, pp. 129–136. (In Russ.)
  9. Gubin V.A., Shchepakin M.B. [About the economic nature of crisis and crisis management]. Upravlenie ekonomicheskimi sistemami: elektronnyi nauchnyi zhurnal, 2010, no. 4. URL: https://cyberleninka.ru/article/v/ob-ekonomicheskoy-prirode-krizisa-i-antikrizisnogo-upravleniya (In Russ.)
  10. Belinskii S.P. [Research methods main series in econometrics]. Gumanitarnye nauki i obrazovanie v Sibiri = Humanities and Education in Siberia, 2016, no. 4, pp. 49–53. (In Russ.)
  11. Dem'yanov R.S. [Use of Box-Jenkins Method for Time Series Forecasting]. Nauka-rastudent.ru, 2017, no. 3. (In Russ.) URL: http://nauka-rastudent.ru/39/4071/
  12. Bakhtizin A.R. [Agent-focused models: Theory and practice]. Analiz i modelirovanie ekonomicheskikh i sotsial'nykh protsessov: Matematika. Komp'yuter. Obrazovanie = Analysis and Modeling of Economic and Social Processes: Mathematics, Computer, Education, 2015, vol. 22, no. 3, pp. 76–83. (In Russ.)
  13. Makarov V.L., Bakhtizin A.R. Sotsial'noe modelirovanie – novyi komp'yuternyi proryv (agent-orientirovannye modeli) [Social modeling: A new computer breakthrough (agent-based models)]. Moscow, Ekonomika Publ., 2013, 295 p.
  14. Bonabeau E. Agent-based Modeling: Methods and Techniques for Simulating Human Systems. PNAS, 2002, vol. 99(3), pp. 7280–7287. URL: https://doi.org/10.1073/pnas.082080899
  15. Davis J.S., Hecht G., Perkins J.D. Social Behaviors, Enforcement and Tax Compliance Dynamics. The Accounting Review, 2003, vol. 78, iss. 1, pp. 39–69. URL: https://doi.org/10.2308/accr.2003.78.1.39

View all articles of issue

 

ISSN 2311-8725 (Online)
ISSN 2073-039X (Print)

Journal current issue

Vol. 16, Iss. 11
November 2017

Archive