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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
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    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.
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    Keywords

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    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

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