Preview

Statistics and Economics

Advanced search

Income inequality, subjective perception and impact on psychosocial well-being of the population

https://doi.org/10.21686/2500-3925-2018-4-52-60

Abstract

Purpose of research. The work is devoted to the study of socio-economic differentiation in Russia and its impact on the financial situation of the population, its subjective perception, as well as on the psychosocial well-being of individuals. To achieve this goal, the following tasks are to be solved: clustering of regions of the Russian Federation, based on socio-economic indexes; studying the interrelation between the level of socio-economic development of the region and the financial situation of residents; studying the interrelation between the level of socio-economic development of the region and the subjective perception by individuals of their financial situation; studying the interrelation between the level of socio-economic development of the region and the psychosocial well-being of individuals.

Materials and methods. The information base of the study includes: regional data, published by the State Committee on Statistics in the digest “Russian Federation Regions”, household survey data “Russian monitoring of the economic situation and health of the population HSE” (RLMS-HSE). Russia Longitudinal Monitoring Survey of Higher School of Economics is a representative socio-economic survey of Russian households, in which the content structure of the used questionnaires meets the standard, adopted in the world practice.

The study uses the following methods: cluster analysis (k-means method), statistical groupings, Kruskal-Wallis and Mann-Whitney statistical tests.

Results. The study showed that:

– the Russian Federation regions are very heterogeneous in terms of socio-economic development – specific indicators for the regions may differ significantly. It should be taken into account in the study of any social and economic problems, including the problems of income inequality;

– Russian regions can be divided into four clusters. Analysis of the petal diagram of clusters made it possible to reveal their features and give them generalized characteristics. The first cluster includes regions with very high investment, fixed assets and GRP per capita. The second cluster includes regions with an average level of development. The third cluster includes regions with a high level of development. The fourth cluster includes depressive regions;

– There is a clear correlation between the level of socio-economic development of the region of residence and the objective financial situation of residents: the incomes of respondents, living in the leading regions are significantly higher than the incomes of respondents of other clusters; the incomes of respondents, living in depressed regions are lower than the incomes of respondents of other clusters;

– Individuals’ perception of their financial situation and their concerns are practically the same in all clusters and do not correlate with the level of socio-economic development of the region of residence;

– The level of economic development of the region of residence does not have a significant direct impact on psychosocial well-being – individuals from different clusters feel almost equally satisfied with life and almost equally happy.

About the Authors

Zulfiya F. Ibragimova
Bashkir State University, Ufa
Russian Federation

Cand. Sci. (Economics), Associate Professor of the Department of macroeconomic development and public administration, Institute of economics, finance and business



Marina V. Frants
Ufa State Aviation Technical University, Ufa
Russian Federation

Cand. Sci. (Engineering), Associate Professor of the Department of business Economics, Institute of Economics and management



References

1. Badertdinova Z.F. Problema bednosti i bogatstva v ucheniyakh sotsial-darvinizma i marksizma. Vestnik Bashkirskogo universiteta. 2008. Vol. 13. No. 1. P. 57-60. (In Russ.)

2. Raspredeleniye obshchego ob”yema denezhnykh dokhodov i kharakteristiki differentsiatsii denezhnykh dokhodov naseleniya: Federal’naya sluzhba gosudarstvennoy statistiki URL: http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/population/poverty/# (In Russ.)

3. Douthitt R.A., Macdonald M., Mullis R. The relationship between measures of subjective and economic well-being: A new look. Social Indicators Research. 1992. Vol. 26. Iss. 4. P. 407–422 https://doi.org/10.1007/BF00347898

4. Case A., Deaton A. Consumption, health, gender and poverty. Working Papers 261. Princeton University. Woodrow Wilson School of Public and International Affairs, Center for Health and Wellbeing. 2002.

5. Deutsch J., Silber J. Measuring multidimensional poverty: An empirical comparison of various approaches. Review of Income and Wealth. 2005. No. 51(1). P. 145–174.

6. Ball R., Chernova K. Absolute Income, Relative Income, and Happiness. Social Indicators Research. 2008. No. 88(3). P. 497–529.

7. Easterlin R. Will raising the incomes of all increase the happiness of all? Journal of Economic Behavior & Organization. 1995. No. 27. P. 35–47.

8. Blanchflower D., Oswald, A. Well-being over time in Britain and the USA. Journal of Public Economics. 2004. No. 88. P. 1359–1387.

9. Lelkes O. Tasting freedom Happiness, religion and economic transition. Journal of Economic Behavior and Organization. 2006. No. 59(2). P. 173–194.

10. Ravallion M., Lokshin M. Self-rated economic welfare in Russia. European–Economic Review. 2002. No. 46(8). P. 1453–1473.

11. Frijters P., Haisken-DeNew J., Shields M. Can the large swings in Russian life satisfaction be explained by ups and downs in real incomes. Scandinavian Journal of Economics. 2006. No. 108(3). P. 433–458.

12. Laaksonen S. A Research Note Happiness by Age is More Complex than U-Shaped. Journal of Happiness Studies. 2018. No. 19. P. 471–482. doi:10.1007/s10902-016-9830-1

13. Matthew D. A. Well-Being, Inequality and Time: The Time-Slice Problem and its Policy Implications. Public Law and Legal Theory University of Pennsylvania Law School Research Paper. No. 07-30. 64 p.

14. Romanova N.P. Sotsial’noye neravenstvo: metodologicheskiy aspekt. Vestnik Zabaykal’skogo gosudarstvennogo universiteta. 2008. No. 4. P. 140–152. (In Russ.)

15. Kalinina D.S. Problema sotsial’nogo neravenstva s pozitsii gendernogo podkhoda. Sovremennyye issledovaniya sotsial’nykh problem. 2017. Vol. 8. No. 2-2. 2017. P. 287-293. (In Russ.)

16. Hartigan J.A., Wong M.A. Algorithm AS 136: A K-Means Clustering Algorithm. Journal of the Royal Statistical Society. Series C (Applied Statistics). 1979. Vol. 28. No. 1. P. 100–108

17. Federal’naya sluzhba gosudarstvennoy statistiki. Regiony Rossii – 2017. URL: http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/publications/catalog/doc_1138623506156 (accessed: 17.04.2016). (In Russ.)

18. «Rossiyskiy monitoring ekonomicheskogo polozheniya i zdorov’ya naseleniya NIU-VSH•E (RLMS-HSE)», provodimyy Natsional’nym issledovatel’skim universitetom «Vysshaya shkola ekonomiki» i OOO «Demoskop» pri uchastii TSentra narodonaseleniya Universiteta Severnoy Karoliny v CHapel KHille i Instituta sotsiologii RAN. (URL: http://www.cpc.unc.edu/projects/rlms i http://www.hse.ru/rlms)» (In Russ.)

19. Nasledov A. SPSS 19: professional’nyy statisticheskiy analiz dannykh. Saint Petersburg: Piter, 2011. 400 p. (In Russ.)


Review

For citations:


Ibragimova Z.F., Frants M.V. Income inequality, subjective perception and impact on psychosocial well-being of the population. Statistics and Economics. 2018;15(4):52-60. (In Russ.) https://doi.org/10.21686/2500-3925-2018-4-52-60

Views: 963


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2500-3925 (Print)