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Socio-Economics of Russia

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Fig. 1. Population Pyramid of Russia


Abstract

Welcome to the repository! Here are collected plots for analysis of country's socio-economic status. It is aimed primarily for academia of Social Science, such as Economists, Sociologists and Political Scientists, but also can be applied in other places (for example, Marketing).


Bubble Plot of Income and Life Expectancy by Regions

Looking at this bubble plot, you may notice that there is no linear relationship between income and life expectancy in Russia. The reason is due to some regions: for example, Causasian regions show high life expectancy at lower incomes whereas Siberian, Ural and Far Eastern regions experience opposite situation with higher incomes and lower life expectancies. When reducing these regions from our data set, we will see ordinary linear relationship where the more regions earn the longer they live.


Population

Fig. 2. Bar Plot of Population by Regions


Fig. 3. Pie Plot of Population by Federal Districts


Fig. 4. Pie Plot of Portion of Regions in Total Population


Fig. 5. Bar Plot of Population by Federal Districts


Fig. 6. Histogram of Population by Regions


Income (GDP per Capita in $US)


Fig. 7. Bar Plot of Monthly Income by Regions


Fig. 8. Bar Plot of Monthly Median Income by Districts


Fig. 9. Histogram of Monthly Incomes by Regions


Fig. 10. Stacked Bar Plot of Age Group by Years


Fig. 11. Stacked Bar Plot of Age Group by Years in nominal values


Life Expectancy


Fig. 12. Bar Plot of Life Expectancy across Regions


Fig. 13. Bar Plot of Life Expectancy across Federal Districts


Fig. 14. Scatter Plot of Regions by Population and Life Expectancy

Call:
lm(formula = `Life Expectancy` ~ Population, data = df.new.rus)

Residuals:
    Min      1Q  Median      3Q     Max 
-4.1895 -1.0596 -0.4618  0.5349 11.3026 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 6.904e+01  3.426e-01 201.535   <2e-16 ***
Population  3.416e-07  1.349e-07   2.533   0.0135 *  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 2.223 on 73 degrees of freedom
Multiple R-squared:  0.0808,	Adjusted R-squared:  0.06821 
F-statistic: 6.417 on 1 and 73 DF,  p-value: 0.01345

Fig. 15. Pie Plot of Russia's Age Portions


Fig. 16. Histogram of Life Expectancy by Regions


Fig. 17. Bar Plot of Life Expectancy Difference between Females and Males


Fig. 18. Bar Plot of Life Expectancy Difference between Females and Males by Federal Districts


Fig. 19. Histogram of Life Expectancy Difference between Females and Males


Fig. 20. Scatter Plot of Population and Life Expectancy Difference between Females and Males

Call:
lm(formula = Difference ~ Population, data = df.new.rus)

Residuals:
    Min      1Q  Median      3Q     Max 
-4.4040 -0.5194  0.3089  0.6438  1.9079 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  9.368e+00  1.822e-01  51.419   <2e-16 ***
Population  -1.416e-07  7.172e-08  -1.974   0.0521 .  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.182 on 73 degrees of freedom
Multiple R-squared:  0.05069,	Adjusted R-squared:  0.03769 
F-statistic: 3.898 on 1 and 73 DF,  p-value: 0.05213

Fertility

Fig. 21. Bar Plot of Fertility Rate


Fig. 22. Bar Plot of Fertility Rate by Districts


Fig. 23. Bubble Plot of Regions by Income and Fertility Rate

Call:
lm(formula = `Fertility Rate` ~ Income, data = df.new.rus)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.57911 -0.16194 -0.02601  0.10487  1.36567 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept) 1.2707604  0.0759405  16.734   <2e-16 ***
Income      0.0002861  0.0001121   2.552   0.0128 *  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.275 on 73 degrees of freedom
Multiple R-squared:  0.0819,	Adjusted R-squared:  0.06932 
F-statistic: 6.512 on 1 and 73 DF,  p-value: 0.01281

Fig. 24. Histogram of Fertility Rate


Fig. 25. Scatter Plot of Life Expectnacy Difference between Females and Males and Fertility Rate

Call:
lm(formula = `Fertility Rate` ~ Difference, data = df.new.rus)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.54230 -0.18179 -0.01519  0.12357  0.97884 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  2.27520    0.23537   9.667 1.06e-14 ***
Difference  -0.09074    0.02556  -3.550 0.000679 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.265 on 73 degrees of freedom
Multiple R-squared:  0.1472,	Adjusted R-squared:  0.1355 
F-statistic:  12.6 on 1 and 73 DF,  p-value: 0.0006791

Fig. 26. 3D Bubble Plot of Life Expectnacy Difference between Females, Income and Males and Fertility Rate

Call:
lm(formula = `Fertility Rate` ~ Income + Difference, data = df.new.rus)

Residuals:
     Min       1Q   Median       3Q      Max 
-0.54541 -0.15263 -0.00404  0.13997  0.98702 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)  2.0857680  0.2377793   8.772 5.56e-13 ***
Income       0.0002722  0.0001041   2.616 0.010846 *  
Difference  -0.0883285  0.0246137  -3.589 0.000603 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.255 on 72 degrees of freedom
Multiple R-squared:  0.2212,	Adjusted R-squared:  0.1996 
F-statistic: 10.22 on 2 and 72 DF,  p-value: 0.0001234

Gender

Fig. 27. Stacked Bar Plot of Russia's Population by Gender


Fig. 28. Stacked Bar Plot of Russia's Population by Gender in Portions


Fig. 29. Bar Plot of Russia's Population by Gender and Age


Fig. 30. Pie Plot of Russia's Male Population by Gender in Portions


Fig. 31. Pie Plot of Russia's Female Population by Gender in Portions


Fig. 32. Nested Pie Plot of Russia's Population by Age and Gender in Portions


Fig. 33. Stacked Bar Plot of Population by Gender Portions


Fig. 34. Histogram of Russia's Population by Age and Gender


Comparison with Post Soviet Countries

Fig. 35. Bubble Plot of Post Soviet Union's Countries by Life Expectancy and Fertility Rate

Data

Region Federal District Fertility Rate Difference Income Life Expectancy Population
Adygea Southern 1.31 9.16 435.07 71.22 496934
Altai Krai Siberian 1.35 9.02 402.33 68.6 2163693
Amur Far Eastern 1.46 9.36 747.16 66.3 766912
Arkhangelsk Northwestern 1.49 10.75 760.29 69.6 978873
Astrakhan Southern 1.63 8.01 538.66 69.9 960142
Bashkortostan Volga 1.41 9.34 522.24 69.49 4091423
Belgorod Central 1.17 8.12 506.96 70.67 1540486
Bryansk Central 1.2 10.31 443.45 68.67 1169161
Buryatia Siberian 1.68 9.69 591.56 68.91 978588
Chechnya North Caucasian 2.74 4.75 361.99 73 1510824
Chelyabinsk Ural 1.47 9.43 549.82 69.16 3431224
Chukotka Far Eastern 1.66 8.7 1565.56 64.87 47490
Chuvashia Volga 1.42 10.51 439.56 69.99 1186909
Dagestan North Caucasian 1.73 4.89 380.96 76.59 3182054
Ingushetia North Caucasian 1.83 6.03 408.11 80.52 509541
Irkutsk Siberian 1.69 9.79 691.84 66.8 2370102
Ivanovo Central 1.37 9.83 387.16 69.02 927828
Jewish AO Far Eastern 1.62 8.85 616.3 66.12 150453
Kabardino-Balkaria North Caucasian 1.51 7.41 382.8 73.77 904200
Kaliningrad Northwestern 1.26 8.74 497.54 70.99 1029966
Kalmykia Southern 1.43 8.16 414.18 71.4 267133
Kaluga Central 1.34 9.81 565.12 69.16 1069904
Karachay-Cherkessia North Caucasian 1.3 8.07 381.6 73.47 469865
Karelia Northwestern 1.5 10.38 627.02 67.31 533121
Khakassia Siberian 1.54 9.43 588.49 68.49 534795
Khanty-Mansi AO Ural 1.67 7.22 1079.29 72.01 1711480
Kirov Volga 1.5 9.88 441.99 69.73 1153680
Komi Northwestern 1.53 9.6 774.88 68.32 737853
Kostroma Central 1.52 9.43 427.29 68.78 580976
Kurgan Ural 1.68 10.19 438.46 68.29 776661
Kursk Central 1.29 8.85 499.09 68.56 1082458
Leningrad Northwestern 0.87 9.51 623.34 70.17 2000997
Lipetsk Central 1.2 9.41 485.19 68.58 1143224
Magadan Far Eastern 1.43 10.03 1360.58 67.41 136085
Mari El Volga 1.41 11.18 430.09 69.46 677097
Mordovia Volga 1.03 8.11 436.91 70.24 783552
Moscow Central 1.33 9.07 737.57 70.35 8524665
Moscow City Central 1.42 6.94 1249.13 74.55 13010112
Murmansk Northwestern 1.47 9.13 1005.29 68.29 667744
Nenets AO Northwestern 1.84 10.83 1191.59 69.39 41434
Nizhny Novgorod Volga 1.31 10.16 483.85 68.93 3119115
North Ossetia North Caucasian 1.59 8.38 394.68 72.47 687357
Novgorod Northwestern 1.32 10.32 494.79 67.64 583387
Novosibirsk Siberian 1.49 9.61 553.34 69.19 2797176
Omsk Siberian 1.52 8.97 497.24 69.02 1858798
Orenburg Volga 1.46 8.57 485.87 68.21 1862767
Oryol Central 1.21 9.77 434.26 68.97 713374
Penza Volga 1.19 9.58 441.73 69.97 1266348
Primorsky Krai Far Eastern 1.43 9.47 678.8 68.61 1845165
Pskov Northwestern 1.33 9.82 420.9 67.69 599084
Rostov Southern 1.25 7.87 470.3 69.79 4200729
Ryazan Central 1.14 9.35 484.23 68.61 1102810
Saint Petersburg Northwestern 1.28 8.07 886.79 72.51 5601911
Sakha Far Eastern 1.62 8.82 1113.66 69.98 995686
Sakhalin Far Eastern 1.81 9.69 1160.59 68.42 466609
Samara Volga 1.33 9.24 507.43 69.33 3172925
Saratov Volga 1.11 8.34 465.51 69.08 2442575
Smolensk Central 1.08 9.55 438.74 68 888421
Sverdlovsk Ural 1.56 10.08 590.4 68.79 4268998
Tambov Central 1.22 8.92 411.67 69.88 982991
Tatarstan Volga 1.43 9.33 580.1 71.28 4004809
Tomsk Siberian 1.24 9.33 617.69 69.7 1062666
Tula Central 1.15 9.8 531.12 68.97 1501214
Tuva Siberian 2.51 8.2 593.44 66.88 336651
Tver Central 1.3 10.23 490.58 67.87 1230171
Tyumen Ural 1.72 9.45 1099.71 70.14 1601940
Udmurtia Volga 1.43 10.84 488.14 69.99 1452914
Ulyanovsk Volga 1.32 9.69 443.69 69.05 1196745
Vladimir Central 1.16 9.82 485.58 68.11 1348134
Volgograd Southern 1.14 8.44 453.44 69.96 2500781
Vologda Northwestern 1.41 10.53 577.55 69.08 1142827
Voronezh Central 1.23 9.52 496.07 69.49 2308792
Yamalo-Nenets AO Ural 1.92 7.32 1739.92 71.7 510490
Yaroslavl Central 1.31 10.47 499.99 69.07 1209811
Zabaykalsky Krai Siberian 1.69 9.26 646.57 66.82 1004125