The impact of digital inequality on population income in Russian regions: an analysis using the generalized method of moments

Cover Page

Cite item

Full Text

Abstract

In the conditions of increasing digitalization of the economy, the problem of digital inequality is becoming particularly relevant, especially at the regional level. The present study is aimed at quantifying the impact of digital inequality on household incomes in the subjects of the Russian Federation. The generalized method of moments (GMM) is used as the main method of analysis, which allows us to eliminate endogeneity problems characteristic of the relationship between income and the level of digitalization. Using panel data for 73 Russian regions for the period 2014-2022, we estimate the impact of various indicators of digital accessibility (fixed and mobile broadband access, level of internet penetration) on real, median and average per capita incomes of the population. The results show a statistically significant positive impact of digital access, especially mobile infrastructure, on household incomes, with differences in the strength and direction of the effects depending on the income indicator used. The paper emphasizes the importance of taking into account macroeconomic factors (GDP, inflation, consumer spending) when interpreting the results and designing digital development policies.

About the authors

Anastasia A. Kurilova

Togliatti State University

Author for correspondence.
Email: aakurilova@yandex.ru
ORCID iD: 0000-0002-1943-5675

Professor of Institute of Finance, Economics and Management, associate professor, Doctor of Economic Sciences

 

Russian Federation, 59, Ushakov Str., Togliatti, Samara region, 445020, Russian Federation

Oksana M. Syardova

Togliatti State University

Email: s.syardova@tltsu.ru

Associate Professor, Institute of Finance, Economics, and Management, Associate Professor, Candidate of Economic Sciences

 

Russian Federation, 59, Ushakov Str., Togliatti, Samara region, 445020, Russian Federation

References

  1. Gradusova, V. N., Lipatova, L. N., & Strokan, E. V. (2023). The impact of the COVID-19 pandemic on the digitalization of the economy in the Arctic regions of Russia. North and the Market: Forming the Economic Order, 26(4), 142–156. https://doi.org/10.37614/2220-802X.4.2023.82.010. EDN: https://elibrary.ru/CLUEUN
  2. Zemtsov, S. P., Demidova, K. V., & Kichaev, D. Yu. (2022). Internet diffusion and interregional digital inequality in Russia: Trends, factors, and the impact of the pandemic. Baltic Region, 14(4), 57–78. https://doi.org/10.5922/2079-8555-2022-4-4. EDN: https://elibrary.ru/LDZLAY
  3. Imasheva, I. Yu., & Kramin, T. V. (2022). Digital inequality: Modernizing Kuznets’ curve in the digital age. Russian Journal of Economics and Law, 16(4), 716–727. https://doi.org/10.21202/2782-2923.2022.4.716-727. EDN: https://elibrary.ru/CEAVOM
  4. Kasimova, T. M., Magomedova, S. R., & Rabadanova, M. G. (2021). Assessment of the level of information and communication technologies development and their impact on regional economy. Fundamentalnye Issledovaniya, (5), 13–18. https://doi.org/10.17513/fr.43032. EDN: https://elibrary.ru/DTOQQL
  5. Klokovskaya, A. V. (2024). Approaches to shaping state policy for reducing digital economy development differentiation across Russian regions. Financial Markets and Banks, (8), 184–188. EDN: https://elibrary.ru/ECRJKV
  6. Nikolaev, M. A., Makhotaeva, M. Yu., & Gusarova, V. N. (2020). Analysis of the impact of digitalization processes on regional economic development. π Economy, 13(4), 46–56. https://doi.org/10.18721/JE.13404. EDN: https://elibrary.ru/PRGGYS
  7. Nikonova, M. A. (2023). Spread of ICT in Russian regions as a factor in reducing digital inequality. Analysis and Modeling of Economic and Social Processes: Mathematics. Computer. Education, 30, 60–67. https://doi.org/10.20537/mce2023econ05. EDN: https://elibrary.ru/ZBHABQ
  8. Prokopyev, E. A. (2020). Factors of the digital divide among Russian regions. Drukerovsky Vestnik, 6(38), 123–140. https://doi.org/10.17213/2312-6469-2020-6-123-140. EDN: https://elibrary.ru/QOLGOV
  9. Sheludyakov, I. S., & Lebedeva (Krassa), E. N. (2023). Digital inequality in Russian regions: Challenges and solutions. Progressive Economy, 23–43. https://doi.org/10.54861/27131211_2023_2_23. EDN: https://elibrary.ru/JMNEQU
  10. Yastrebov, A. P. (2023). Managing regional innovation infrastructure through development of information and communication technologies and technology parks. Regional Economy and Management: Electronic Scientific Journal, 4(76), 1–10. Retrieved from: https://eee-region.ru/article/7645. EDN: https://elibrary.ru/HTWAWA
  11. de Clercq, M., D’Haese, M., & Buysse, J. (2023). Economic growth and broadband access: The European urban-rural digital divide. Telecommunications Policy, 47(6). https://doi.org/10.1016/j.telpol.2023.102579. EDN: https://elibrary.ru/XNYFEH
  12. Mikhaylova, A. A., & Hvaley, D. V. (2023). Geography of the mobile internet in the border and interior regions of Russia. Baltic Region, 15(3), 140–166. https://doi.org/10.5922/2079-8555-2023-3-8. EDN: https://elibrary.ru/RGQIPQ
  13. Mitrofanova, I. V., Chernova, O. A., & Pleshakova, M. V. (2024). Investment platforms for implementing an inclusive development agribusiness model. In A. Inshakova, D. Matytsin, & E. Inshakova (Eds.), Remote Investment Transactions in the Digital Age (Intelligent Systems Reference Library, Vol. 250, pp. 227–236). Springer, Cham. https://doi.org/10.1007/978-3-031-51536-1_21
  14. Sysolyatin, A. V., Sozinova, A. A., Kazakov, M. Y., Kurennaya, V. V., & Fomichenko, S. A. (2023). Regional aspects of the digital divide and its overcoming in the sustainable development goals. In E. G. Popkova (Ed.), Smart Green Innovations in Industry 4.0 for Climate Change Risk Management (Environmental Footprints and Eco-design of Products and Processes, pp. 411–418). Springer, Cham. https://doi.org/10.1007/978-3-031-28457-1_42
  15. Varlamova, J., & Kadochnikova, E. (2023). Modeling the spatial effects of digital data economy on regional economic growth: SAR, SEM and SAC models. Mathematics, 11(16), 3516. https://doi.org/10.3390/math11163516. EDN: https://elibrary.ru/ECTTXN
  16. Zhang, W., Zhao, S., Wan, X., & Yao, Y. (2021). Study on the effect of digital economy on high-quality economic development in China. PLoS ONE, 16(9). https://doi.org/10.1371/journal.pone.0257365. EDN: https://elibrary.ru/XNOTIF

Supplementary files

Supplementary Files
Action
1. JATS XML
Download


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).