IDEAS home Printed from https://ideas.repec.org/a/spr/rrorus/v13y2023i2d10.1134_s2079970523700612.html
   My bibliography  Save this article

Determinants of Economic Growth in Regions with Different COVID-19 Incidence Rates

Author

Listed:
  • M. A. Kaneva

    (Institute of Economics and Industrial Engineering, Siberian Branch, Russian Academy of Sciences)

Abstract

— The article examines the incidence of COVID-19 in Russia within a framework of the endogenous growth model. All regions of Russia were divided into three groups according to the incidence rate values, for each of which threshold regression models were constructed for 2008–2018, where the threshold is the stock of human capital. For group 1, two thresholds were identified, and a negative statistically significant relationship was found between public health expenditure and GRP per capita. This indicates the inefficiency of investments in terms of their opportunity cost. The regional health systems of group 1 require federal assistance. For groups 2 and 3, the dependence is also negative, but insignificant, indicating the need to modernize their healthcare systems, at least in developing the infectious service.

Suggested Citation

  • M. A. Kaneva, 2023. "Determinants of Economic Growth in Regions with Different COVID-19 Incidence Rates," Regional Research of Russia, Springer, vol. 13(2), pages 296-304, June.
    • Handle: RePEc:spr:rrorus:v:13:y:2023:i:2:d:10.1134_s2079970523700612
    DOI: 10.1134/S2079970523700612
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1134/S2079970523700612
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1134/S2079970523700612?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Michael Lokshin & Martin Ravallion, 2008. "Testing for an economic gradient in health status using subjective data," Health Economics, John Wiley & Sons, Ltd., vol. 17(11), pages 1237-1259.
    2. S. P. Zemtsov & V. L. Baburin, 2020. "COVID-19: Spatial Dynamics and Diffusion Factors across Russian Regions," Regional Research of Russia, Springer, vol. 10(3), pages 273-290, July.
    3. Qunyong Wang, 2015. "Fixed-effect panel threshold model using Stata," Stata Journal, StataCorp LP, vol. 15(1), pages 121-134, March.
    4. Kolomak, E. A., 2020. "Economic effects of pandemic-related restrictions in Russia and their spatial heterogeneity," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 6(3), pages 154-161.
    5. Xiaofei Li & Fen Chen & Songbo Hu & Baogui Xin, 2021. "Spatial Spillover Effect of Government Public Health Spending on Regional Economic Growth during the COVID-19 Pandemic: An Evidence from China," Complexity, Hindawi, vol. 2021, pages 1-10, March.
    6. Maria Kaneva & Galina Untura, 2019. "The impact of R&D and knowledge spillovers on the economic growth of russian regions," Growth and Change, Wiley Blackwell, vol. 50(1), pages 301-334, March.
    7. Michael Lokshin & Martin Ravallion, 2008. "Testing for an economic gradient in health status using subjective data," Health Economics, John Wiley & Sons, Ltd., vol. 17(11), pages 1237-1259, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. M. A. Kaneva, 2021. "Health Capital Estimates for Russian Regions in 2004–2018," Regional Research of Russia, Springer, vol. 11(4), pages 524-532, October.
    2. Koen Decancq, 2014. "Copula-based measurement of dependence between dimensions of well-being," Oxford Economic Papers, Oxford University Press, vol. 66(3), pages 681-701.
    3. Valerii Baidin & Christopher J. Gerry & Maria Kaneva, 2021. "How Self-Rated is Self-Rated Health? Exploring the Role of Individual and Institutional Factors in Reporting Heterogeneity in Russia," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(2), pages 675-696, June.
    4. Raskina, Yulia & Podkorytova, Olga & Kuchakov, Ruslan, 2022. "Health determinants and the reporting heterogeneity bias in Russia: Anchoring vignettes approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 66, pages 118-143.
    5. Ravallion, Martin & Himelein, Kristen & Beegle, Kathleen, 2013. "Can subjective questions on economic welfare be trusted ? evidence for three developing countries," Policy Research Working Paper Series 6726, The World Bank.
    6. Ren Mu, 2014. "Regional Disparities In Self‐Reported Health: Evidence From Chinese Older Adults," Health Economics, John Wiley & Sons, Ltd., vol. 23(5), pages 529-549, May.
    7. Koen Decancq & María Ana Lugo, 2009. "Measuring inequality of well-being with a correlation-sensitive multidimensional Gini index," Working Papers 124, ECINEQ, Society for the Study of Economic Inequality.
    8. Ravallion, Martin, 2012. "Poor, or just feeling poor ? on using subjective data in measuring poverty," Policy Research Working Paper Series 5968, The World Bank.
    9. Baron-Epel, Orna & Kaplan, Giora, 2009. "Can subjective and objective socioeconomic status explain minority health disparities in Israel?," Social Science & Medicine, Elsevier, vol. 69(10), pages 1460-1467, November.
    10. ZHAO, Guochang, 2015. "Can money ‘buy’ schooling achievement? Evidence from 19 Chinese cities," China Economic Review, Elsevier, vol. 35(C), pages 83-104.
    11. Kiendrebeogo,Youssouf & Ianchovichina,Elena & Kiendrebeogo,Youssouf & Ianchovichina,Elena, 2016. "Who supports violent extremism in developing countries ? analysis of attitudes based on value surveys," Policy Research Working Paper Series 7691, The World Bank.
    12. Simplice A. Asongu & Nicholas M. Odhiambo, 2020. "Insurance Policy Thresholds for Economic Growth in Africa," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 32(3), pages 672-689, July.
    13. Ostadzad, Ali Hossein, 2022. "Innovation and carbon emissions: Fixed-effects panel threshold model estimation for renewable energy," Renewable Energy, Elsevier, vol. 198(C), pages 602-617.
    14. Mara Leticia Rojas & María María Ibáñez Martín & Carlos Dabús, 2023. "Is Debt Always Harmful for Economic Growth? Evidence from Developing Countries," Working Papers 292, Red Nacional de Investigadores en Economía (RedNIE).
    15. Polemis, Michael & Tselekounis, Markos, 2019. "Does deregulation drive innovation intensity? Lessons learned from the OECD telecommunications sector," MPRA Paper 92770, University Library of Munich, Germany.
    16. He, Yiqing & Ding, Xin & Yang, Chuchu, 2021. "Do environmental regulations and financial constraints stimulate corporate technological innovation? Evidence from China," Journal of Asian Economics, Elsevier, vol. 72(C).
    17. Khan, Muhammad Atif & Gu, Lulu & Khan, Muhammad Asif & Oláh, Judit, 2020. "Natural resources and financial development: The role of institutional quality," Journal of Multinational Financial Management, Elsevier, vol. 56(C).
    18. Xiao-Ying Dong & Qiying Ran & Yu Hao, 2019. "On the nonlinear relationship between energy consumption and economic development in China: new evidence from panel data threshold estimations," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 1837-1857, July.
    19. Moralles, Herick Fernando & Moreno, Rosina, 2020. "FDI productivity spillovers and absorptive capacity in Brazilian firms: A threshold regression analysis," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 257-272.
    20. Jishnu Das & Quy-Toan Do & Jed Friedman & David McKenzie, 2008. "Mental Health Patterns and Consequences: Results from Survey Data in Five Developing Countries," The World Bank Economic Review, World Bank, vol. 23(1), pages 31-55, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:rrorus:v:13:y:2023:i:2:d:10.1134_s2079970523700612. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.