1. Analysis Findings of the Depth of Social and Economic Problems Across the Regions of the Russian Federation
Volkova Maria Igorevna, Candidate of Economic Sciences, Associate Professor
The Central Economic Mathematical Institute of the Russian Academy of Sciences

2. Social and Economic Problems
Decrease in Quality of Life and Quality of Living Conditions
Increase in Stratification and Differentiation
Search for Alternative Sources of Income
Potential Involvement in Criminal Organizations

3. Examples of Simulation Models Where the Population Acts as One of the Main Agents
Genkin M., Gutfraind A. (2008): How Do Terrorist Cells Self-Assemble? Insights from an Agent-Based Model. Annual Meeting of the American Sociological Association, Sheraton Boston and the Boston Marriott Copley Place, Boston, MA, Jul 31, 2008.
S.Ya. Sushchy, G.A. Ugolnitsky, V.K. Dyachenko. Simulation Modeling of Struggle Against Extremism in the Northern Caucasus. Sociology: 4М No. 37. P
Steve Kiser. Financing Terror. An Analysis and Simulation for Affecting Al Qaeda's Financial Infrastructure. – р.

4. Groups of the Most Acute Social and Economic Problems
Labor
Unemployment
Long-term unemployment
Arrears in wages
Work-related injuries
Unemployed people per vacancy
And other criteria
Health
Infant mortality
Mortality caused by certain diseases
Incidence of certain diseases
Rate of natural increase
Security
Crime rate
Social security level
Income and Welfare
Personal and household incomes (relative parameters)
Poverty headcount
Material security
Infrastructure development level

5. Key Focuses of National Projects
Quality of life
Demography, education, healthcare
Social sphere
Ecology
Employment support
Small and medium-sized entrepreneurship
Science, digital economy, culture
Income, housing, roads

6. Composite Indicator Calculation Methodology as Part of the Principal Component Analysis. Flowchart
Transformation of initial variables
Block partitioning (correlation relationships)
Calculation of information content criteria (using eigenvalues of the covariance matrix)
Estimation of eigenvalues, eigenvectors and weighting factors
Calculation of principal components and indicators of certain categories
Estimation of the weighted Euclidean distance to the reference point and the composite indicator value

7. List of Variables (by Russian Region)
Demography
Rate of natural increase (per 1,000 people)
Infant mortality rate (Infant deaths per 1,000 live births)
Mortality from malignant neoplasms (per 100,000 people)
Cardiovascular mortality rate (per 100,000 people)
Number of invalids (per 1,000 people)
Social sphere
Percent of the population with money incomes below the minimum subsistence level (%)
Long-term unemployment level (people seeking employment for more than 12 months, % of all unemployed)
Labor market tension (number of unemployed people per one vacancy)
Total number of grave crimes (per 10,000 people)
Welfare
Number of cars in private hands (per 1,000 people)
Housing commissioning (square meters per 1,000 people)
Ratio of per capita income to the minimum subsistence level (%)
Cumulative volume of retail turnover and chargeable services (per capita)
Investments in fixed capital (per capita)
Length of paved motor roads (per 1,000 square meters of the regional area)

8. Criterion Weights Within Categories (2018)
Demography
Rate of natural increase (0,31)
Number of invalids (0,08)
Infant mortality rate (0,1)
Mortality from malignant neoplasms (0,25)
Cardiovascular mortality rate (0,26)
Social pathology
1(0,69):
Poverty headcount (0,41); long-term unemployment (0,28); unemployed people per vacancy (0,31)
2 (0,31):
Number of grave crimes
Welfare
1 (0,27):
Turnover and chargeable services (0,41); housing commissioning (0,4); roads (0,19)
2 (0,46): Income (0,45) and investments (0,55)
3 (0,27): Cars

9. “Demography” Indicator Values, 2018

10. Ranks of the Leading and Low-Performing Regions (Demography), 2015-2018

11. “Social Pathology” Indicator Values, 2018

12. Ranks of the Leading and Low-Performing Regions (Social Sphere), 2015-2018

13. “Welfare” Indicator Values, 2018

14. Ranks of the Leading and Low-Performing Regions (Welfare), 2015-2018

15. Weights of Group Indicators in the Composite Indicator, 2018 J=1 (Demography), J=2 (Welfare), J=3 (Social Sphere)

16. Chart of Normalized Weights of Synthetic Categories of the Quality of Life of the Population of the Russian Federation, 2018

17. Composite Indicator Values, 2018

18. Summarized Principal Component Flowchart (for Three-Dimensional Data)

19. Eigenvalues of the compromise matrix

20. Object Projection (Altai Krai) (Onto the First Axis of Compromise Space)

21. Object Projection (Republic of Khakassia) (Onto the First Axis of Compromise Space)

22. THANK YOU
for your attention