IDEAS home Printed from https://ideas.repec.org/a/aiy/jnjaer/v22y2023i4p861-891.html
   My bibliography  Save this article

Experimental System-Dynamic Model of an Influence of a Level of Education on a Spatial Differentiation of a Population of Russian Regions

Author

Listed:
  • Vladimir N. Timokhin
  • Dmitry B. Berg
  • Andrei G. Shelomentsev

Abstract

The study is devoted to the problem of the spatial differentiation of population income in Russia's regions. The objective of the study is the development of a system-dynamic model for the calculation of spatial differentiation trajectories of income parameters due to various scenarios. Regional features of the human capital development level influencing the spatial differentiation of population income in the Russian regions are assumed. The formulation of the mathematical problem is based on the results of regression analysis of the influence of time series values of socio-demographic factors on population incomes differentiation (Gini coefficient). A specialist application, PowerSim Studio Express 10, was used for model design. Rosstat data on households in the Russian regions were used for calculation of the model experimental trajectories. The main research methods are the following: dynamic analysis of time series; econometric and system-dynamic modeling. As a result of the study, a system-dynamics experimental model was proposed. It was tested in application to eight regions with the most reliable statistical relationship between socio-demographic factors and the Gini index. Numerical experiments were used to simulate real economic processes of convergence and divergence in order to identify the main trends and features of territorial income differentiation depending on local priorities of vocational education development. It was shown that an increase in the level of education, both higher professional and secondary vocational, mainly leads to increased income differentiation. The theoretical significance of the results obtained lies in the deepening of the understanding of the regional features of human capital development influencing the spatial differentiation of population income. The practical significance of the study lies in the expansion of instrumental support for decision-making in the implementation of state policy in the field of regulating the population incomes differentiation at the regional level.

Suggested Citation

  • Vladimir N. Timokhin & Dmitry B. Berg & Andrei G. Shelomentsev, 2023. "Experimental System-Dynamic Model of an Influence of a Level of Education on a Spatial Differentiation of a Population of Russian Regions," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 22(4), pages 861-891.
  • Handle: RePEc:aiy:jnjaer:v:22:y:2023:i:4:p:861-891
    DOI: https://doi.org/10.15826/vestnik.2023.22.4.035
    as

    Download full text from publisher

    File URL: https://journalaer.ru//fileadmin/user_upload/site_15934/2023/05_Timokhin_Berg_SHelomencev.pdf
    Download Restriction: no

    File URL: https://libkey.io/https://doi.org/10.15826/vestnik.2023.22.4.035?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
    ---><---

    References listed on IDEAS

    as
    1. Alberto Alesina & Dani Rodrik, 1994. "Distributive Politics and Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(2), pages 465-490.
    2. Altunbaş, Yener & Thornton, John, 2019. "The impact of financial development on income inequality: A quantile regression approach," Economics Letters, Elsevier, vol. 175(C), pages 51-56.
    3. Barro, Robert J, 2000. "Inequality and Growth in a Panel of Countries," Journal of Economic Growth, Springer, vol. 5(1), pages 5-32, March.
    4. Nie, Haifeng & Xing, Chunbing, 2019. "Education expansion, assortative marriage, and income inequality in China," China Economic Review, Elsevier, vol. 55(C), pages 37-51.
    5. Ruslan Grigoryev & Marat Kramin & Timur Kramin & Asiya Timiryasova, 2015. "Inequality of Income Distribution and Economics Growth in the Regions of Russia in the Post-Crisis Period," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(3), pages 102-113.
    6. Jay W. Forrester, 2016. "Learning through System Dynamics as Preparation for the 21st Century," System Dynamics Review, System Dynamics Society, vol. 32(3-4), pages 187-203, July.
    7. S. A. Suspitsyn, 2021. "Set of Methods and Procedures for Analyzing and Forecasting the Development of the Eastern Regions of the Russian Federation," Regional Research of Russia, Springer, vol. 11(1), pages 65-77, December.
    8. Mark D. Partridge, 2005. "Does Income Distribution Affect U.S. State Economic Growth?," Journal of Regional Science, Wiley Blackwell, vol. 45(2), pages 363-394, May.
    9. Vyacheslav Lokosov & Yelena Ryumina & Vladimir Ulyanov, 2015. "Regional Differentiation of Human Potential Indicators," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 185-196.
    10. Fabrizi, Enrico & Trivisano, Carlo, 2016. "Small area estimation of the Gini concentration coefficient," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 223-234.
    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. Ghosh, sudeshna, 2017. "Education Attainment Forecasting and Economic Inequality United States," MPRA Paper 89712, University Library of Munich, Germany.
    2. Bebonchu Atems, 2013. "A Note On The Differential Regional Effects Of Income Inequality: Empirical Evidence Using U.S. County-Level Data," Journal of Regional Science, Wiley Blackwell, vol. 53(4), pages 656-671, October.
    3. Marrero, Gustavo A. & Rodríguez, Juan G., 2013. "Inequality of opportunity and growth," Journal of Development Economics, Elsevier, vol. 104(C), pages 107-122.
    4. Adelaide Duarte & Marta Simões, 2010. "Regional growth in Portugal: assessing the contribution of earnings and education inequality," GEMF Working Papers 2010-11, GEMF, Faculty of Economics, University of Coimbra.
    5. Marta Simões & João Andrade & Adelaide Duarte, 2013. "A regional perspective on inequality and growth in Portugal using panel cointegration analysis," International Economics and Economic Policy, Springer, vol. 10(3), pages 427-451, September.
    6. Kennedy, Tom & Smyth, Russell & Valadkhani, Abbas & Chen, George, 2017. "Does income inequality hinder economic growth? New evidence using Australian taxation statistics," Economic Modelling, Elsevier, vol. 65(C), pages 119-128.
    7. Anping Chen & Nicolaas Groenewold, 2011. "Regional Equality and National Development in China: Is There a Trade‐Off?," Growth and Change, Wiley Blackwell, vol. 42(4), pages 628-669, December.
    8. Huang, Ho-Chuan (River) & Fang, WenShwo & Miller, Stephen M. & Yeh, Chih-Chuan, 2015. "The effect of growth volatility on income inequality," Economic Modelling, Elsevier, vol. 45(C), pages 212-222.
    9. David Castells-Quintana & Vicente Royuela, 2017. "Tracking positive and negative effects of inequality on long-run growth," Empirical Economics, Springer, vol. 53(4), pages 1349-1378, December.
    10. Mehmet Balcilar & Rangan Gupta & Wei Ma & Philton Makena, 2021. "Income inequality and economic growth: A re‐examination of theory and evidence," Review of Development Economics, Wiley Blackwell, vol. 25(2), pages 737-757, May.
    11. Karen Davtyan, 2016. "Interrelation among Economic Growth, Income Inequality, and Fiscal Performance: Evidence from Anglo-Saxon Countries," Hacienda Pública Española / Review of Public Economics, IEF, vol. 217(2), pages 37-66, June.
    12. David Castells-Quintana & Vicente Royuela, 2014. "Agglomeration, inequality and economic growth," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(2), pages 343-366, March.
    13. Veronica Amarante, 2014. "Revisiting Inequality and Growth: Evidence for Developing Countries," Growth and Change, Wiley Blackwell, vol. 45(4), pages 571-589, December.
    14. Shinhye Chang & Matthew W. Clance & Giray Gozgor & Rangan Gupta, 2019. "A Reconsideration of Kuznets Curve across Countries: Evidence from the Co-summability Approach," Working Papers 201970, University of Pretoria, Department of Economics.
    15. Fuad Hasanov & Oded Izraeli, 2011. "Income Inequality, Economic Growth, And The Distribution Of Income Gains: Evidence From The U.S. States," Journal of Regional Science, Wiley Blackwell, vol. 51(3), pages 518-539, August.
    16. Roberto Ezcurra, 2007. "Is Income Inequality Harmful for Regional Growth? Evidence from the European Union," Urban Studies, Urban Studies Journal Limited, vol. 44(10), pages 1953-1971, September.
    17. Mcknight, Abigail, 2019. "Understanding the relationship between poverty, inequality and growth: a review of existing evidence," LSE Research Online Documents on Economics 103458, London School of Economics and Political Science, LSE Library.
    18. Łukasz Piętak, 2022. "Regional disparities, transmission channels and country's economic growth," Journal of Regional Science, Wiley Blackwell, vol. 62(1), pages 270-306, January.
    19. repec:ira:wpaper:201405 is not listed on IDEAS
    20. David Castells & Vicente Royuela, 2012. "Agglomeration, Inequality and Economic Growth: Cross-section and panel data analysis," ERSA conference papers ersa12p492, European Regional Science Association.
    21. Muhammad Shahbaz, 2010. "Income inequality‐economic growth and non‐linearity: a case of Pakistan," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 37(8), pages 613-636, July.

    More about this item

    Keywords

    system dynamics; simulation modeling; development scenarios; experimental trajectories; territorial disproportions; differentiation of living standards; convergence/divergence of income of the population.;
    All these keywords.

    JEL classification:

    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

    Statistics

    Access and download statistics

    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:aiy:jnjaer:v:22:y:2023:i:4:p:861-891. 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: Natalia Starodubets (email available below). General contact details of provider: https://edirc.repec.org/data/seurfru.html .

    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.