Socio-Economics of Russia

Fig. 1. Population Pyramid of Russia

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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).

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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.

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Population

Fig. 2. Bar Plot of Population by Regions

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Fig. 3. Pie Plot of Population by Federal Districts

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

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Fig. 5. Bar Plot of Population by Federal Districts

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Fig. 6. Histogram of Population by Regions

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Income (GDP per Capita in $US)

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Fig. 7. Bar Plot of Monthly Income by Regions

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

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Fig. 9. Histogram of Monthly Incomes by Regions

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

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

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Life Expectancy

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Fig. 12. Bar Plot of Life Expectancy across Regions

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

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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 *  
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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

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

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Fig. 16. Histogram of Life Expectancy by Regions

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

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

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

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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 .  
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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

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Fertility

Fig. 21. Bar Plot of Fertility Rate

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Fig. 22. Bar Plot of Fertility Rate by Districts

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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 *  
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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

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Fig. 24. Histogram of Fertility Rate

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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 ***
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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

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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 ***
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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

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Gender

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

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

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

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

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

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

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

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

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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