THE POSSIBILITIES OF MULTIDIMENSIONAL STATISTICAL ANALYSIS METHODS FOR ASSESSING THE QUALITY OF LIFE OF THE POPULATION IN THE REGIONS (USING THE EXAMPLE OF THE BORDER REGIONS OF THE CENTRAL FEDERAL DISTRICT)
The quality of life in the regions plays a significant role in assessing the effectiveness of regional policies, the growth of citizens' well-being, and the opportunities for improving the efficiency of decision-making. Economic and social challenges, as well as dynamic changes in the geopolitical environment, particularly in border regions, require the use of modern analysis methods to comprehensively assess the quality of life. One of these methods is multidimensional statistical analysis, which covers a wide range of indicators and takes into account both economic and social aspects of the population's life. The article is devoted to the study of the possibilities of multidimensional statistical analysis, including factor analysis, clustering, discriminant analysis and other methods. These tools provide researchers with powerful capabilities for processing and interpreting large amounts of data, allowing them to identify hidden dependencies, form groups based on similar characteristics, and identify key factors affecting quality of life.
Vladyka M.V., Burdinskaya D.M., Sivakova Y.A. “The possibilities of multidimensional statistical analysis methods for assessing the quality of life of the population in the regions (using the example of the border regions of the Central Federal District)”, Research Result. Economic Research, 12(1), 13-23, DOI: 10.18413/2409-1634-2026-12-1-0-2
While nobody left any comments to this publication.
You can be first.
1. Breuer W., Brueser D. (2012) “Determining Indicators of Quality of Life Differences in European Cities”, EIBURS RWTH Aachen Working Paper No. 1/2012, August 6, 2012, 43 p.
2. Easterlin R.A., Angelescu L. (2007), “Modern Economic Growth and Quality of Life: Cross-Sectional and Time Series Evidence”, IEPR Working Paper No. 07.4 : IZA Discussion Paper No. 2755 : USC CLEO Research Paper No. C07-7, April 12, 2007, 59 p.
3. Rubanov I.N., Tikunov V.S. (2007) “On the Methodology for Assessing the Human Development Index and Its Use in Russian Conditions”, Geographical Bulletin, 1-2 (5-6),
pp. 57-72, EDN NDARFV.
4. Erikson R. (1993) “Descriptions of Inequality: The Swedish Approach to Welfare Research”, In: M. Nussbaum, A. Sen. Eds. The Quality of Life (Oxford: Clarendon Press), Pp. 67-87, https://doi.org/10.1093/0198287976.003.0006.
5. Kozlova O.A. et al. (2015) “A Methodological Approach to Measure the Quality of Life of the Region’s Population”, R-Economy,
1, 2, 280-290.
6. Okrepilov V.V. et al. (2015) “Application of supercomputer technologies for modeling socio-economic systems”, Economics of the region, 2(42), 301-312, DOI 10.17059/2015-2-24, EDN VHRTMX.
7. Quality of life indicators – measuring quality of life, available at: https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Quality_of_life_indicators_-_measuring_quality_of_life
8. Richardson J. et al. (2004) “Measurement of the Quality of Life for Economic Evaluation and the Assessment of Quality of Life (Aqol) Mark 2 Instrument”, Australian Economic Review, 37, 62-88.
9. Satorra A., Bentler P.M. (2021) “A Scaled Difference Chi-Square Test Statistic for Moment Structure Analysis”, Psychometrika, 66(4), 507-514.
10. Shanygin S.I., Rizvanova E.R. (2020) “Standardization of indicators in multivariate studies of economic processes”, Economy. Law. Innovations, 3, 4-13, EDN AKEEYO.
11. Sanyasorn S. et al. (2019) “Problems, Needs, Quality of Life and the Development Model of Production Efficiency and Value Creation of Agricultural Products of Community Enterprises”, Journal of Interdisciplinary Research: Graduate Studies, 8, 2, 230-240.
12. Woo B.F.Y. et al. (2017) “The impact of the advanced practice nursing role on quality of care, clinical outcomes, patient satisfaction, and cost in the emergency and critical care settings: a systematic review”, Human resources for health, 15(1), DOI: https://doi.org/10.1186/s12960-017-0237-9
13. Ayvazyan S.A. (2000), Integral indicators of the quality of life of the population: their construction and use in socio-economic management and interregional comparisons, CEMI RAS, Moscow, 117 p.
14. Kolmakova I.D., Baykova E.I., Kolmakova E.M. (2017) “Economic and mathematical methods in assessing and planning the standard of living of the population of the region”, Regional Economy: Theory and Practice, 15, 5, 928-936.
15. Mazelis L.S., Krasova E.V., Boyko A.A. (2022) “Comprehensive Assessment of the Quality of Life of the Population in the Regions of the Russian Federation”, Economy and Management, 8, 753-766.
16. Methodological Provisions on Statistics of the Standard of Living of the Population of the Russian Federation, available at: https://adept.srcc.msu.ru/adept/urov_blag/method/
17. Migranova L.A., Ulyanov V.V. (2017) “Methodological Approaches to Assessing the Quality of Life of the Population in the Region”, Population, 116-129.
18. Mukhacheva A. V., Pastukhova E. Ya., Kiryukhina A. N. (2020) “Mathematical modeling of the quality of life of the regional population”, Bulletin of Omsk State University. Series: Economics, 18, 1, 149-161.
19. Ponomareva V.N. (2019) “Application of econometric methods to assessing the level of quality of life”, Forum of young scientists, 2(30), 1181-1188, EDN VOYYGM.
20. Regions of Russia. Socio-economic indicators, available at: https://ssl.rosstat.gov.ru/
21. Ranking of regions by quality of life – 2023, available at: https://riarating.ru/infografika/20240212/630257500.html