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Econometric Model for Identifying Factors of Income Differentiation of the Population

https://doi.org/10.21686/2500-3925-2021-4-48-60

Abstract

Purpose of the study. On the basis of the construction of a multifactorial econometric model, it is necessary to identify the factors of income differentiation of the population. In accordance with the goal, the following tasks are set: 1) to propose a typology of factors of household income differentiation; 2) on the basis of correlation analysis, to assess the closeness of the relationship between the average income of the population and those statistical indicators that maximally reflect the level of formation, the content and nature of the factors’ influence of household income differentiation; 3) using a step-by-step regression analysis algorithm to construct an econometric model to quantify the relationship between the factors of income differentiation and the income of the population.

Materials and methods. In the process of preparing the article, the authors used information from the website of the Federal State Statistics Service, analytical statistical materials, scientific works of Russian and foreign scientists. The following methods were used in the paper: system analysis method (to develop a typology of factors for differentiating household income); the method of economic and mathematical modeling (when building an econometric model to quantify the relationship between the factors of income differentiation and the income of the population).

Results. The classification of the factors of differentiation of household incomes was carried out according to three criteria: the level of formation, the content and nature of the influence of the factors. Four groups of statistical indicators have been formed, which, to the maximum extent, are the essence of the factors of income differentiation. An analysis of the correlation coefficients indicates a close relationship between the average income of the population of the Russian Federation regions and the overwhelming majority of statistical indicators. Assessment of the statistical significance of the regression coefficients made it possible to identify those indicators with which the indicator of the average income of the population has a significant quantitative dependence, namely: retail trade turnover per capita; the volume of personal services per capita; average monthly nominal accrued wages; the value of the subsistence minimum. This made it possible to build a four-factor econometric model.

Conclusion. A typology of factors of household incomes’ differentiation is proposed, which combines such classification features as: the level of formation, the content and nature of the influence of factors. Those statistical indicators that reflect to the maximum extent the level of formation, content and nature of the influence of the previously considered factors of income differentiation on the level of income of the population are selected and grouped according to the corresponding criterion. Based on the correlation analysis, an assessment of the closeness of the relationship between the average income of the population and statistical indicators reflecting the factors of income differentiation was carried out. Using the algorithm of stepby-step regression analysis, a multivariate econometric model was built, which made it possible to identify a quantitative relationship between the factors of income differentiation and the average income of the population.

About the Authors

Irina A. Karpuhno
Donetsk National University
Russian Federation

Irina А. Karpukhno – Cand. Sci. (Economics), Associate Professor.

Donetsk



Dania A. Guchmazova
Donetsk National University
Russian Federation

Daniia А. Huchmazova – Postgraduate student.

Donetsk



References

1. Kakiye vidy neravenstv vidyatsya naiboleye ser’yoznymi = What types of inequalities are seen as the most serious [Internet]. Ipsos official website. Available from: https://www.ipsos.com/ru-ru/kakievidy-neravenstv-vidyatsya-naibolee-seryoznymi. (cited 01.05.2021). (In Russ.)

2. Time to care: Unpaid and underpaid care work and the global inequality crisis [Internet]. Official Oxfam website. Available from: https://oxfamilibrary.openrepository.com/bitstream/handle/10546/620928/bp-time-to-care-inequality-200120-en.pdf. (cited 01.05.2021).

3. Preobrazovaniye nashego mira: Povestka dnya v oblasti ustoychivogo razvitiya na period do 2030 goda = Transforming Our World: The 2030 Agenda for Sustainable Development [Internet]. United Nations. Available from: https://www.un.org/ga/search/view_doc.asp?symbol=A/RES/70/1&Lang=R. (cited 05.05.2021). (In Russ.)

4. Shevyakov A.YU., Kiruta A.YA. Neravenstvo, ekonomicheskiy rost i demografiya: neissledovannyye vzaimosvyazi = Inequality, economic growth and demography: unexplored relationships. Moscow: M-Studio, 2009. 192 s. (In Russ.)

5. Kiruta A.YA. The influence of inequality on the quality of human potential in Russia. Vestnik Instituta sotsiologii = Bulletin of the Institute of Sociology. 2011; 3: 67-87. (In Russ.)

6. Malkina M.YU. The relationship between the types of inequality with indicators of the standard of living and well-being of the population of the regions of Russia. Terra Economicus = Terra Economicus. 2017; 4: 46-63. (In Russ.)

7. Ovcharova L.N., Popova D.O., Rudberg A.M. Decomposition of the factors of income inequality in modern Russia. Zhurnal Novoy ekonomicheskoy assotsiatsii = Journal of the New Economic Association. 2016; 3(31): 170-186. (In Russ.)

8. Kadyrov D.B. Formirovaniye i mekhanizm regulirovaniya dokhodov naseleniya v sisteme faktorov rosta blagosostoyaniya: diss. d-ra ekon. nauk. = Formation and mechanism of regulation of the population’s income in the system of welfare growth factors: diss. Dr. econ. sciences. (08.00.01). Voronezh, 2003. 301 p. (In Russ.)

9. Bulavinets’ V.M., Zaklekta A.I. Income inequality of the population: factors and current state. Effektivnaya ekonomika = Effective Economics. 2017; 11: 23-31. (In Russ.)

10. Zagidullina I.F. Faktory, tendentsii i osobennosti differentsiatsii dokhodov v sovremennoy Rossii: avtoref. dis. kand. ekon. Nauk = Factors, tendencies and features of income differentiation in modern Russia: author. dis. Cand. econom. Sciences: (08.00.01). Moscow, 2011. 30 p. (In Russ.)

11. Goncharova K.S. Chislennaya otsenka vliyaniya sotsial’no-demograficheskikh faktorov na regional’nuyu differentsiatsiyu naseleniya po urovnyu dokhodov: diss. kand. ekon. Nauk = Numerical assessment of the influence of sociodemographic factors on the regional differentiation of the population by income level: diss. Cand. econom. Sciences. Yekaterinburg, 2020. 226 p. (In Russ.)

12. Stukalenko Ye.A. Differentiation of population income: causes and consequences. Vestnik OmGU. Seriya: Ekonomika = Bulletin of OmSU. Series: Economics. 2014; 1: 183-187. (In Russ.)

13. Malkina M.YU. Institutional Foundations of Income Inequality in the Modern Economy. Journal of Institutional Studies (Zhurnal institutsional’nykh issledovaniy) = Journal of Institutional Studies. 2016; 1(8): 100-120. (In Russ.)

14. Makkonell K.R. Ekonomiks: printsipy, problemy i politika = Economics: principles, problems and politics. Moscow: INFRA-M; 2009. 916 p. (In Russ.)

15. Tokhtarova V.S. Differentiation of population income: problems and factors. Vestnik Khmel’nitskogo natsional’nogo universiteta = Bulletin of Khmelnitsky National University. 2011; 6: 216-220. (In Russ.)

16. Surinov A.Ye. Nenablyudayemaya ekonomika: popytka kolichestvennykh izmereniy: monografiya = The Unobserved Economy: An Attempt at Quantitative Measurement: A Monograph. Moscow: OOO Finstatinform; 2003. 256 p. (In Russ.)

17. Duesenberry J.S. Income, Saving and the Theory of Consumer Behavior. Cambridge. Harvard University Press; 1949. 142 p.

18. Panskov V.G. Progressive versus proportional taxation scale: which is fairer and more efficient? Ekonomika. Nalogi. Pravo = Economy. Taxes. Right. 2017; 2: 105-112. (In Russ.)

19. The Global wealth report 2020 [Internet]. Credit Suisse. Available from: https://www.creditsuisse.com/about-us/en/reports-research/globalwealth-report.html (cited 01.05.2021).

20. Regiony Rossii. Sotsial’no-ekonomicheskiye pokazateli – 2020 g. = Regions of Russia. Socioeconomic indicators - 2020 [Internet]. Available from: https://gks.ru/bgd/regl/b20_14p/Main.htm (cited 01.05.2021). (In Russ.)

21. Prognoz dolgosrochnogo sotsial’noekonomicheskogo razvitiya Rossiyskoy Federatsii na period do 2030 goda (razrabotan Minekonomrazvitiya Rossii) = Forecast of longterm socio-economic development of the Russian Federation for the period up to 2030 (developed by the Ministry of Economic Development of Russia) [Internet]. Consultant Plus. Available from: http://www.consultant.ru/document/cons_doc_LAW_144190/797848062bfeb3711b889a3a539f05c86a98b4da/. (cited 01.05.2021). (In Russ.)

22. «Bezbednaya starost’»: pochemu na Severnom Kavkaze samyye nizkiye pensii v Rossii=»Comfortable old age»: why the North Caucasus has the lowest pensions in Russia [Internet]. NewsTracker. Available from: https://newstracker.ru/article/general/14-12-2019/bezbednaya-starostpochemu-na-severnom-kavkaze-samye-nizkiepensii-v-rossii. (cited 02.05.2021). (In Russ.)


Review

For citations:


Karpuhno I.A., Guchmazova D.A. Econometric Model for Identifying Factors of Income Differentiation of the Population. Statistics and Economics. 2021;18(4):48-60. (In Russ.) https://doi.org/10.21686/2500-3925-2021-4-48-60

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