On one statistical method for analyzing economic processes balancedness

封面
  • 作者: Bogatov E.M.1,2, Demidova E.G.3
  • 隶属关系:
    1. Starooskolsky Technological Institute named after A.A. Ugarov, Branch of the Federal State Autonomous Educational Institution of Higher Education “National Research Technological University ‘MISIS’ ”
    2. Branch of the Federal State Autonomous Educational Institution of Higher Education “National Research Technological University ‘MISIS’ ” in the town of Gubkin
    3. Starooskolsky Technological Institute named after A. A. Ugarov (Branch) of the Federal State Autonomous Educational Institution of Higher Education “National Research Technological University «MISIS»”
  • 期: 卷 60, 编号 1 (2024)
  • 页面: 121-132
  • 栏目: Mathematical analysis of economic models
  • URL: https://rjmseer.com/0424-7388/article/view/653317
  • DOI: https://doi.org/10.31857/S0424738824010103
  • ID: 653317

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详细

The paper proposes a statistical approach to determining the stability and sustainability of economic processes based on the analysis of the dynamics of averages and standard deviations of one or more industry average indicators characterizing these processes. According to this approach, a method for constructing acceptable limits for the change in and similar to the method used in quality control of technological processes by means of Shewhart or Hotelling control charts is proposed. Going beyond the acceptable limits of the indicators ͞X (S̅) will signify the instability (unsteadiness) of the corresponding process; a process that has the property of stability and sustainability at the same time is defined as balanced. The method of analysis of economic processes presented in the paper differs from the traditional one — it allows not only to compare the retrospective indicators of the analyzed enterprise with the industry average or recommended value, but also to determine the trend in the behavior of the analyzed process within acceptable limits. The boundaries are set on the basis of a statistical analysis of the indicators of this process for a homogeneous sample, which includes similar companies. In addition, the authors’ methodology allows us to assess the dynamics of the spread of indicator values, which is also an important factor in the study of economic processes. The method was tested as part of the analysis of the financial and economic process, characterized by the coefficients of financial stability and profitability of sales of a number of Russian metallurgical companies observed over a period of ten years (2012–2021).

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作者简介

E. Bogatov

Starooskolsky Technological Institute named after A.A. Ugarov, Branch of the Federal State Autonomous Educational Institution of Higher Education “National Research Technological University ‘MISIS’ ”; Branch of the Federal State Autonomous Educational Institution of Higher Education “National Research Technological University ‘MISIS’ ” in the town of Gubkin

编辑信件的主要联系方式.
Email: embogatov@inbox.ru
俄罗斯联邦, Gubkin; Stary Oscol

E. Demidova

Starooskolsky Technological Institute named after A. A. Ugarov (Branch) of the Federal State Autonomous Educational Institution of Higher Education “National Research Technological University «MISIS»”

Email: dmitrikeg@mail.ru
俄罗斯联邦, Stary Oscol

参考

  1. Арошидзе А. А. (2021). Особенности подходов к пониманию экономической устойчивости в контексте устойчивого развития предприятий // Экономика, предпринимательство и право. Т. 11. № 4. С. 785– 798. [Aroshidze A. A. (2021). Features of approaches to understanding economic sustainability in the context of sustainable development of enterprises. Journal of Economics, Entrepreneurship and Law, 11, 4, 785–798 (in Russian).]
  2. Арсланов Ш. Д. (2022). Современные вызовы и альтернативные возможности инвестиционного развития регионов // Региональные проблемы преобразования экономики. № 9 (143). С. 49–56. [Arslanov Sh.D. (2022). Modern challenges and alternative opportunities for investment development of regions. Regional Problems of Transformation of the Economy, 9 (143), 49–56 (in Russian).]
  3. Демидова Е. Г., Демидов В. И. (2023). Интегральная оценка экономического потенциала компании // Финансовая экономика. № 2. С. 23–28. [Demidova E. G., Demidov V. I. (2023). Integral assessment of the company’s economic potential. The Financial Economy, 2, 23–28 (in Russian).]
  4. Зотова Е. В., Маркина Я. Ю. (2020). Устойчивость экономики и проблемы ее обеспечения в современной России. В сб.: «Научные исследования в социально-экономическом развитии общества. Материалы Национальной научно-практической конференции». Р. Р. Хайров (отв. ред.). С. 150–157. [Zotova E. V., Markina Ya.Yu. (2020). Sustainability of the economy and problems of its provision in modern Russia. In: Scientific research in the socio-economic development of society. Materials of the National Scientific and Practical Conference. R. R. Xajrov (resp. ed.), 150–157 (in Russian).]
  5. Клячкин В. Н. (2011). Модели и методы статистического контроля многопараметрического технологического процесса. М.: ФИЗМАТЛИТ. 196 с. [Klyachkin V. N. (2011). Models and methods of statistical control of a multiparametric technological process. Moscow: FIZMATLIT. 196 p. (in Russian).]
  6. Клячкин В. Н. (2014). Статистические методы в управлении качеством: компьютерные технологии. М.: Финансы и статистика. 304 с. [Klyachkin V. N. (2014). Statistical methods in quality management: Computer technologies. Moscow: Finansy` i Statistika. 304 p. (in Russian).]
  7. Кобзарь А. И. (2006). Прикладная математическая статистика. Для инженеров и научных работников. М.: ФИЗМАТЛИТ. 816 с. [Kobzar A. I. (2006). Applied mathematical statistics. For engineers and researchers. Moscow: FIZMATLIT. 816 p. (in Russian).]
  8. Кремер Н. Ш. (2001). Теория вероятностей и математическая статистика. М.: ЮНИТИ-ДАНА. 543 с. [Kremer N. S. (2001). Probability theory and mathematical statistics. Moscow: UNITI-DANA. 543 p. (in Russian).]
  9. Кумэ Х. (ред.) (1990). Статистические методы повышения качества. М.: Финансы и статистика. 304 с. [Kume H. (ed.) (1990). Statistical methods of quality improvement. Moscow: Finansy` i Statistika. 304 p. (in Russian).]
  10. Логанина В. И., Федосеев А. А. (2007). Статистические методы контроля и управления качеством продукции. Ростов-на-Дону: Феникс. 222 с. [Loganina V. I., Fedoseev A. A. (2007). Statistical methods of product quality control and management. Rostov-on-Don: Fenix. 222 p. (in Russian).]
  11. Рогова В. А. (2011). Понятие устойчивости в экономической науке: эволюция, содержание, типы. В кн.: «Государственное и муниципальное управление. Ученые записки Северо-Кавказской академии государственной службы (СКАГС)». № 3. С. 222–228. [Rogova V. A. (2011). Sustainability as a category of economic science: Evolution, content, types. In: South Russian Institute of the Russian Presidential Academy of National Economy and Public Administration (SRI RANEPA), 3, 222–228 (in Russian).]
  12. Соловьёв В. П., Богатов Е. М. (2021). Организация эксперимента. Старый Оскол: Тонкие наукоемкие технологии. 256 с. [Soloviev V. P., Bogatov E. M. (2021). Organization of the experiment. Stariy Oskol: Tonkie naukoemkie texnologii. 256 p. (in Russian).]
  13. Степнов М. Н. (2005). Статистические методы обработки результатов механических испытаний. Справочник. 2-е изд. М.: Машиностроение. 399 с. [Stepnov M. N. (2005). Statistical methods of processing the results of mechanical tests. Handbook. 2nd ed. revised and supplemented. Moscow: Mashinostroenie. 399 p. (in Russian).]
  14. Чернобровин В. П. (2020). Черная металлургия России в динамике (1970–2018 гг.) // Вестник ЮУрГУ. Серия «Металлургия». Т. 20. № 1. С. 7–17. doi: 10.14529/met200101 [Chernobrovin V. P. (2020). Ferrous metallurgy of Russia in dynamics (1970–2018). Bulletin of the South Ural State University. Ser. Metallurgy, 20, 1, 7–17. doi: 10.14529/met200101 (in Russian).]
  15. Штанский В. А. (2008). Конкурентоспособность металлургического комплекса России в долгосрочной перспективе // Вестник РАЕН. Т. 8. № 2. С. 122–127. [Shtansky V. A. (2008). Competitiveness of the metallurgical complex of Russia in the long term. Bulletin of Russian Academy of Natural Sciences, 8, 2, 122–127 (in Russian).]
  16. Штанский В. А., Краснова Н. А. (2011). Стимулы и факторы различных форм интеграции российских металлургических компаний в условиях глобализации мировой экономики // Экономика промышленности. № 3. С. 3–10. [Shtansky V. A., Krasnova N. A. (2011). Incentives and factors of various forms of integration of Russian metallurgical companies in the context of globalization of the world economy. Russian Journal of Industrial Economics, 3, 3–10 (in Russian).]
  17. Юзов О. В., Седых А. М., Афонин С. З. (2009). Тенденции изменения экономических показателей развития черной металлургии России // Экономика промышленности. № 1. С. 2–7. [Yuzov O. V., Sedykh A. M., Afonin S. Z. (2009). Trends in economic indicators of the development of ferrous metallurgy in Russia. Russian Journal of Industrial Economics, 1, 2–7 (in Russian).]
  18. Aparizi F., Carrion A., Jabaloyes J. (1999). Statistical properties of the [S] multivariate control chart. Communications in Statistics — Theory and Methods, 28, 11, 2671–2686.
  19. Ryan T. P. (2011). Statistical methods for quality improvement. N.Y.: John Wiley & Sons. 676 p.

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