Integral structural complexity index of regional economies

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

Current scientific discussions are focused on identifying professions and types of economic activity that will become most in demand in the future and determine priority areas for diversification of regional economies. Analysis of such trends is important for forecasting the dynamics of GRP. The purpose of this work is to construct an integral index of structural complexity on the basis of four basic indices of economic complexity of regional economies, calculated by the authors on the basis of data on the structure of employment, the structure of the distribution of enterprises and the structure of GRP. According to Rosstat for 2019 and 2022, four basic complexity indices were formed for 85 regions: the index of complexity of GRP structures based on data on production by types of economic activity (TEA); index of complexity of employment structures of the regions by TEA; index of regional employment structures by occupational groups; index of complexity of distribution structures of enterprises in the regions by TEA. The analysis of 0–1 matrices for all four economic complexity indices under consideration is carried out. The leading positions in the four corresponding ratings are occupied by Moscow, St. Petersburg, the Novosibirsk Region, and the Moscow Region. Four integral indices of structural complexity of regional economies were constructed. Their advantages and disadvantages are analyzed. It is shown that the structural complexity of the regional economy has an impact on GRP. Moreover, one of the integral indices is significant in the production function of the GRP of 85 regions according to the data of 2019 and 2022.

Full Text

Restricted Access

About the authors

M. Yu. Afanasiev

Central Economics and Mathematics Institute, RAS

Author for correspondence.
Email: mi.afan@yandex.ru
Russian Federation, Moscow

А. А. Gusev

Central Economics and Mathematics Institute, RAS

Email: gusevalexeyal@yandex.ru
Russian Federation, Moscow

References

  1. Айвазян С. А. (2012). Анализ качества и образа жизни населения (эконометрический подход). М.: Наука. 432 с. ISBN: 978-5-02-037968-8 [Ayvazyan S. A. (2012). Analysis of the quality and lifestyle of life of the population (econometric approach). Moscow: Nauka. 432 p. ISBN: 978-5-02-037968-8 (in Russian).]
  2. Айвазян С. А., Афанасьев М. Ю., Кудров А. В. (2016). Модели производственного потенциала и оценки технологической эффективности регионов РФ с учетом структуры производства // Экономика и математические методы. Т. 52. № 1. С. 28–44. [Ayvazyan S. A., Afanasiev M.Yu., Kudrov A. V. (2016). Models of production potential and assessment of technological efficiency of the regions of the Russian federation taking into account the structure of production. Economics and Mathematical Methods, 52 (1), 28–44 (in Russian).]
  3. Айвазян С. А., Афанасьев М. Ю., Кудров А. В. (2018). Об учете природной ренты в индикаторах регионального развития // Вестник ЦЭМИ РАН. T. 1. № 1. doi: 10.33276/S0000006-9-1 [Ayvazyan S. A., Afanasiev M. Yu., Kudrov A. V. (2018). On the consideration of natural resource rent in regional development indicators. Bulletin of CEMI RAS, 1, 1. doi: 10.33276/S0000006-9-1 (in Russian).]
  4. Афанасьев М. Ю., Гусев А. А. (2023). Ситуационное моделирование траекторий экономической сложности регионов // Экономика и математические методы. Т. 59. № 4. С. 58–70. doi: 10.31857/S042473880028217-7 [Afanasiev M.Yu., Gusev A. A. (2023). Situational modeling of trajectories of economic complexity of regions. Economics and Mathematical Methods, 59 (4), 58–70. doi: 10.31857/S042473880028217-7 (in Russian).]
  5. Афанасьев М. Ю., Гусев А. А., Нанавян А. М. (2023). Оценка профессиональной структуры занятого населения в российских регионах на основе концепции экономической сложности // Экономические и социальные перемены: факты, тенденции, прогноз. Т. 16. № 6. С. 91–107. doi: 10.15838/esc.2023.6.90.5 [Afanasiev M. Yu., Gusev A. A., Nanavyan A. M. (2023). Assessment of the professional structure of the employed population in Russian regions based on the concept of economic complexity. Economic and Social Changes: Facts, Trends, Forecast, 16, 6, 91–107. doi: 10.15838/esc.2023.6.90.5 (in Russian).]
  6. Афанасьев М. Ю., Гусев А. А., Нанавян А. М. (2024). Интегральный индекс сложности структур занятости российских регионов // Экономические и социальные перемены: факты, тенденции, прогноз. В печати. [Afanasiev M.Yu., Gusev A. A., Nanavyan A. M. (2024). Integral index of the complexity of employment structures in Russian regions. Economic and Social Changes: Facts, Trends, Forecast. In press (in Russian).]
  7. Афанасьев М. Ю., Ильин Н. И. (2022). Новые ориентиры для выбора приоритетных направлений диверсификации экономики на базе системы ситуационных центров // Экономика и математические методы. Т. 58. № 4. С. 29–44. doi: 10.31857/S042473880023017-7 [Afanasiev M.Yu., Ilyin N. I. (2022). New guidelines for choosing priority areas for economic diversification based on the system of situation centers. Economics and Mathematical Methods, 58, 4, 29–44. doi: 10.31857/S042473880023017-7 (in Russian).]
  8. Афанасьев М. Ю., Кудров А. В. (2021). Экономическая сложность и вложенность структур региональных экономик // Экономика и математические методы. Т. 57. № 3. С. 67–78. doi: 10.31857/S042473880016410-0 [Afanasiev M.Yu., Kudrov A. V. (2021). Economic complexity and nesting of structures of regional economies. Economics and Mathematical Methods, 57, 3, 67–78. doi: 10.31857/S042473880016410-0 (in Russian).]
  9. Гусев А. А. (2024). Сравнительный анализ подходов к оценке экономической сложности регионов России по структуре ВРП // Региональная экономика и управление: электронный научный журнал. № 3 (79). #7917. [Gusev A. A. (2024). Comparative analysis of approaches to assessing the economic complexity of Russian regions by the structure of GRP. Regional Economy and Management: Electronic Scientific Journal, 3 (79). Art. #7917 (in Russian).]
  10. Ивахненко Т. Ю., Полбин А. В., Синельников-Мурылев С.Г. (2024). Экономическая сложность и неравенство доходов в регионах России // Вопросы экономики. № 5. С. 105–127. doi: 10.32609/0042-8736-2024-5-105-127 [Ivakhnenko T.Yu., Polbin A. V., Sinelnikov-Murylev S.G. (2024). Economic complexity and income inequality in the regions of Russia. Voprosy Ekonomiki, 5, 105–127 (in Russian).]
  11. Любимов И. Л., Гвоздева М. А., Казакова М. В., Нестерова К. В. (2017). Сложность экономики и возможность диверсификации экспорта в российских регионах // Журнал Новой экономической ассоциации. № 2 (34). С. 94–122. [Lyubimov I. L., Gvozdeva M. A., Kazakova M. V., Nesterova K. V. (2017). The complexity of the economy and the possibility of diversification of exports in Russian regions. Journal of the New Economic Association, 2 (34), 94–122 (in Russian).]
  12. Регионы России. Социально-экономические показатели. 2022 (2022). Стат. сб. М.: Росстат. 1122 с. [Regions of Russia. Socio-economic indicators. 2022 (2022). Stat. collection. Moscow: Rosstat. 1122 p. (in Russian).]
  13. Чеплинските И. Р., Лукин Е. В. (2024). Особенности экспортной специализации регионов СЗФО в рамках концепции экономической сложности // Экономические и социальные перемены: факты, тенденции, прогноз. Т. 17. № 2. С. 81–95. doi: 10.15838/esc.2024.2.92.4 [Cheplinskite I. R., Lukin E. V. (2024). Features of export specialization of the regions of the Northwestern Federal District within the framework of the concept of economic complexity. Economic and Social Changes: Facts, Trends, Forecast, 17, 2, 81–95. doi: 10.15838/esc.2024.2.92.4 (in Russian).]
  14. Чупин А. Л., Засько В. Н., Морковкин Д. Е., Донцова О. И. (2024). Модель роста экономики региона на основе индекса экономической сложности // Финансы: теория и практика. Т. 28. № 3. С. 52–60. doi: 10.26794/2587-5671-2024-28-3-52-60 [Chupin A. L., Zas’ko V.N., Morkovkin D. E., Dontsova O. I. (2024). Regional economic growth model based on the economic complexity index. Finance: Theory and Practice, 28, 3, 52–60 (in Russian).]
  15. Balassa B. (1965). Lafayrade liberalization and “revealed” comparative advantage. The Manchester School, 33, 99–123.
  16. Hartmann D. (2017). Linking economic complexity, institutions, and income inequality. World Development, 93, 75–93.
  17. Hausmann R., Hidalgo C. A., Bustos S., Coscia M., Simoes A., Yıldırım M. A. et al. (2014). The atlas of economic complexity: Mapping paths to prosperity. Cambridge: MIT Press. 368 p.
  18. Hausmann R., Hwang J., Rodrik D. (2006). What you export matters. Journal of Economic Growth, 12 (1), 1–25.
  19. Hausmann R., Klinger B. (2006). Structural transformation and patterns of comparative advantage in the product space. CID Working Paper, 128.
  20. Herrera W., Strauch J., Bruno M. (2020). Economic complexity of Brazilian states in the period 1997–2017. Area Development and Policy, 6 (2), 1–19. doi: 10.1080/23792949.2020.1761846
  21. Hidalgo C. A. (2021). Economic complexity theory and applications. Nature Reviews Physics, 3 (2), 92–113.
  22. Hidalgo C. A., Hausmann R. (2009). The building blocks of economic complexity. Proceedings of the National Academy of Sciences, 106 (26), 10570–10575.
  23. Sciarra C., Chiarotti G., Ridolfi L. (2020). Reconciling contrasting views on economic complexity. Nat Commun, 11, 3352. doi: 10.1038/s41467-020-16992-1

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2. Fig. 1. Matrix 0-1 region-FEA by GRP structure

Download (235KB)
Indexing metadata
3. Fig. 2. Matrix 0-1 region-occupational group by occupational employment

Download (187KB)
Indexing metadata
4. Fig. 3. Matrix 0-1 region-WEA by the number of enterprises

Download (198KB)
Indexing metadata
5. Fig. 4. Matrix 0-1 region-WEA by number of employed persons

Download (200KB)
Indexing metadata
6. Fig. 5. Point-region in the space of nINT1 index values on the abscissa axis and nINT2 index values on the ordinate axis

Download (26KB)
Indexing metadata
7. Fig. 6. Point - region in the space of nINT1 index values on the abscissa axis and nINT4 index values on the ordinate axis.

Download (29KB)
Indexing metadata
8. Fig. 7. Point - region in the space of nINT1 index values on the abscissa axis and nINT3 index values on the ordinate axis.

Download (27KB)
Indexing metadata
9. Fig. 8. Dependence of GRP (ordinate axis) on the nINT4 index (abscissa axis).

Download (62KB)
Indexing metadata
10. Fig. 9. Dependence of GRP with excluded natural rent (ordinate axis) on the nINT4 index (abscissa axis)

Download (62KB)
Indexing metadata
11. Fig. 10. Regions in the space of the first two principal components of the GRP structure by FEA

Download (95KB)
Indexing metadata

Copyright (c) 2025 Russian Academy of Sciences