IDEAS home Printed from https://ideas.repec.org/a/aiy/jnjaer/v19y2020i2p149-165.html
   My bibliography  Save this article

Modeling of the Main Determinants of the Poverty Level in Russian Regions

Author

Listed:
  • D.V. Shimanovsky
  • T.S. Zagrebina

Abstract

In the paper the dependence of the proportion of the population with the income below the subsistence minimum on other socio-economic indicators in a regional context has been considered. According to the UN concept, poverty reduction is one of the main goals of sustainable development, which enhances the relevance of the selected theme. This study aims at identifying the determinants of the proportion of poor population and developing potential practical recommendations on government policy related to the reduction of the proportion of low-income citizens. The determinants are the unemployment rate, the birth rate, and some other indicators. The paper contains an overview of the works of national and foreign authors on modeling the proportion of the poor population. As part of the study, two alternative econometric models based on panel data have been formed: the pooled data model and the model with fixed effects. The results of the work based on the formed models clearly show that the proportion of the poor population depends on other characteristics of citizens’ well-being (life duration, unemployment rate) and the migration of highly productive and promising personnel to high-income regions. At the same time, these two models deliver similar results. As a result of the study, the authors have concluded that investment in the human capital (education, health status, culture, strive for self-discipline and self-development) is an important factor in reducing the poverty rate. As practical recommendations, the authors make three final conclusions. First, the involvement of high-paid vacancies in employment services can lead to a reduction in unemployment and, as a result, to a reduction in the level of poverty. Second, investment in education can reduce crime by increasing the overall level of culture and responsibility. Third, investment in health care can increase life expectancy. And this can lead to an increase in the employment rate of pensioners and people with chronic diseases, which reduces the level of poverty.

Suggested Citation

  • D.V. Shimanovsky & T.S. Zagrebina, 2020. "Modeling of the Main Determinants of the Poverty Level in Russian Regions," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 19(2), pages 149-165.
    • Handle: RePEc:aiy:jnjaer:v:19:y:2020:i:2:p:149-165
    DOI: http://dx.doi.org/10.15826/vestnik.2020.19.2.008
    as

    Download full text from publisher

    File URL: https://journalaer.ru//fileadmin/user_upload/site_15934/2020/02_SHimanovskii_Zagrebina.pdf
    Download Restriction: no
    File URL: https://libkey.io/http://dx.doi.org/10.15826/vestnik.2020.19.2.008?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. Meng, Xin & Gregory, Robert & Wang, Youjuan, 2005. "Poverty, inequality, and growth in urban China, 1986-2000," Journal of Comparative Economics, Elsevier, vol. 33(4), pages 710-729, December.
    2. Akihiko Yanase, 2005. "Pollution Control in Open Economies: Implications of Within-period Interactions for Dynamic Game Equilibrium," Journal of Economics, Springer, vol. 84(3), pages 277-311, May.
    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. Bin, Peng & Chen, Xiaolan & Fracasso, Andrea & Tomasi, Chiara, 2018. "Resource allocation and productivity across provinces in China," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 103-113.
    2. Fields, Gary S. & Meng, Xin & Song, Yang, 2022. "Earnings mobility during labor market reforms in urban China," China Economic Review, Elsevier, vol. 75(C).
    3. Shuai Shi & Kathy Pain, 2020. "Investigating China’s Mid-Yangtze River economic growth region using a spatial network growth model," Urban Studies, Urban Studies Journal Limited, vol. 57(14), pages 2973-2993, November.
    4. Song, Yang & Zhou, Guangsu, 2019. "Inequality of opportunity and household education expenditures: Evidence from panel data in China," China Economic Review, Elsevier, vol. 55(C), pages 85-98.
    5. Bjorn A Gustafsson & Deng Quheng, 2011. "Di Bao Receipt and Its Importance for Combating Poverty in Urban China," Poverty & Public Policy, John Wiley & Sons, vol. 3(1), pages 1-32, March.
    6. Christopher Candelaria & Mary C. Daly & Galina Hale, 2009. "Beyond Kuznets: persistent regional inequality in China," Working Paper Series 2009-07, Federal Reserve Bank of San Francisco.
    7. Gustafsson, Björn Anders & Sai, Ding, 2019. "Growing into Relative Income Poverty: Urban China 1988 to 2013," IZA Discussion Papers 12422, Institute of Labor Economics (IZA).
    8. Bin Dong & Benno Torgler, 2010. "The Causes of Corruption: Evidence from China," Working Papers 2010.72, Fondazione Eni Enrico Mattei.
    9. Chen, Shaohua & Ravallion, Martin, 2021. "Reconciling the conflicting narratives on poverty in China," Journal of Development Economics, Elsevier, vol. 153(C).
    10. Xin Meng & Kailing Shen & Sen Xue, 2010. "Economic Reform, Education Expansion, and Earnings Inequality for Urban Males in China, 1988-2007," CEPR Discussion Papers 639, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    11. Hering, Laura & Poncet, Sandra, 2009. "The impact of economic geography on wages: Disentangling the channels of influence," China Economic Review, Elsevier, vol. 20(1), pages 1-14, March.
    12. Calvo, Emilio & Rubio, Santiago J., 2013. "Dynamic Models of International Environmental Agreements: A Differential Game Approach," International Review of Environmental and Resource Economics, now publishers, vol. 6(4), pages 289-339, April.
    13. Zhicheng Liang, 2006. "Financial Development And Income Distribution: A System Gmm Panel Analysis With Application To Urban China," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 31(2), pages 1-21, December.
    14. Ming Lu & Shiqing Jiang, 2008. "Labor Market Reform, Income Inequality and Economic Growth in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 16(6), pages 63-80, November.
    15. GOH, Chor-ching & LUO, Xubei & ZHU, Nong, 2009. "Income growth, inequality and poverty reduction: A case study of eight provinces in China," China Economic Review, Elsevier, vol. 20(3), pages 485-496, September.
    16. Zhang, Chunni & Xu, Qi & Zhou, Xiang & Zhang, Xiaobo & Xie, Yu, 2014. "Are poverty rates underestimated in China? New evidence from four recent surveys," China Economic Review, Elsevier, vol. 31(C), pages 410-425.
    17. Marco Bee & Maria Michela Dickson & Flavio Santi, 2018. "Likelihood-based risk estimation for variance-gamma models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(1), pages 69-89, March.
    18. Meng, Xin & Shen, Kailing & Xue, Sen, 2013. "Economic reform, education expansion, and earnings inequality for urban males in China, 1988–2009," Journal of Comparative Economics, Elsevier, vol. 41(1), pages 227-244.
    19. Shuai Zhao, 2023. "Family Size and Intergenerational Inequality: Evidence from China's One-child Policy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 165(1), pages 283-307, January.
    20. Roberts, Mark & Deichmann, Uwe & Fingleton, Bernard & Shi, Tuo, 2010. "On the road to prosperity ? The economic geography of China's national expressway network," Policy Research Working Paper Series 5479, The World Bank.

    More about this item

    Keywords

    poverty level; goals of the sustainable development; model with fixed effects;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

    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:19:y:2020:i:2:p:149-165. 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.