J., 2014, Siniavskaya O., 2010) is also widely discussed. T otal savings will decrease with the growth of the senior citizens rate (Searching for a new silver age in Russia, 2015). T hat’s why we need special methods of developing and regulating the funded pensionsystem (Developing a funded pension system in Russia, 2013) as a part of social safety net. Pension Fund is a basic source of material wellbeing of the retirees, the budget of which is deficit due to different reasons. T.
he conducted assessment allows us to assume that the reasons for this are not only economic and demographic, but also organizational, including: Goals contradiction: the Pension Fund performs the functions of a «social state', which leads to the fact that there are more obligations than rights (those, who contribute nothing at all or less than they will receive when retire, also get pension);Implementation of the pension co-financing program: it doesn’t encourage retirees to take part in it, but results in high cost for the participants — current retirees. The following actions can be taken to overcome the budget deficit: only the salary loss and not the loss of income or reaching retirement age can be considered as the insurance case. I t means pension should be paid for «salary loss» and not for «retirement age»;all other pensions (disability, loss of breadwinner, maternity capital and so on) should be paid from general taxes;there should be a direct connection of the pension with the system payments. T he pension should not be calculated from the «minimum of subsistence in a region» or from the salary;the part of the funded pension in income should be increased, as it is effective for both the retirees and the investment market, despite the fact that the activity of companies managing the funded pension is limited by the social component of the source and they can’t function as investment companies;the combination of three components (state compulsory, compulsory funded and voluntary funded) in the pension system allows to the wellbeing of the retirees, as diversification reduces the risks. BibliographyAndreev E. M. K onechnyj ehffekt mer demograficheskoj politiki 1980;h v Rossii // Mir Rossii: Sociologiya, ehtnologiya. 2016.
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k XII Mezhdunar. nauch. konf. po problemam razvitiya ekonomiki i obshchestva.
NIU VShE. Appendix 120 152 014 201 320 128 905 2160FemaleMaleFemaleMaleFemaleMaleFemaleMaleFemaleMaleFemaleMalenqx — probability of dying between ages x and x+n<1 year0.
0070.
0090.
0080.
010.
0080.
010.
0080.
010.
0090.
0110.
0090.
0121−4 years0.
0010.
0020.
0010.
0020.
0010.
0020.
0010.
0020.
0010.
0020.
0010.
0025−9 years0.
0010.
0010.
0010.
0010.
0010.
0010.
0010.
0020.
0010.
0020.
0010.
210−14 years0.
0010.
0020.
0010.
0020.
0010.
0020.
0010.
0020.
0010.
0020.
0010.
215−19 years0.
0020.
0050.
0020.
0050.
0020.
0050.
0030.
0060.
0030.
0060.
0030.
620−24 years0.
0030.
0110.
0030.
0110.
0030.
0110.
0040.
0120.
0040.
0120.
0040.
1 325−29 years0.
0060.
0190.
0060.
020.
0060.
020.
0060.
0210.
0060.
020.
0060.
2 330−34 years0.
0090.
0310.
0090.
0310.
0090.
0320.
0090.
0330.
0090.
0330.
010.
3 535−39 years0.
0110.
0350.
0110.
0360.
0110.
0360.
0120.
0380.
0120.
0390.
0120.
0440−44 years0.
0140.
0420.
0140.
0420.
0140.
0440.
0150.
0450.
0160.
0490.
0160.
5 145−49 years0.
0170.
0530.
0170.
0530.
0180.
0550.
0180.
0570.
0190.
0590.
020.
6 450−54 years0.
0240.
0750.
0240.
0760.
0250.
0780.
0260.
0810.
0280.
0860.
0290.
9 155−59 years0.
0380.
1090.
0380.
110.
0390.
1130.
0410.
1160.
040.
1160.
0440.
12 460−64 years0.
0550.
1550.
0560.
1560.
0580.
1590.
0590.
1630.
0670.
180.
0690.
18 565−69 years0.
080.
2030.
0810.
2040.
0830.
2070.
0860.
2110.
0760.
1830.
0890.
21 570−74 years0.
1270.
2680.
1290.
2690.
1310.
2720.
1350.
2760.
1490.
2990.
150.
29 975−79 years0.
2290.
3880.
2310.
3890.
2360.
3920.
2410.
3960.
2260.
3640.
2580.
40 880−84 years0.
3720.
4950.
3750.
4960.
3790.
4990.
3850.
5020.
3930.
5170.
4030.
52 385−89 years0.
5490.
6710.
5530.
6710.
5570.
6750.
5610.
6810.
5510.
640.
6020.
7390−94 years0.
7440.
80.
7470.
7990.
750.
7990.
7520.
8030.
7390.
7550.
7820.
84 995−99 years0.
8770.
9050.
880.
9030.
8820.
9020.
8830.
9020.
8710.
8510.
9060.
938 100+ years111111111111lx — number of people left alive at age x<1 year1000001000001000001000001000001000001000001000001000001000001000001000001−4 years9928099090992509905099220990109918098960991409891099090988505−9 years99160989409912098890990909884099050987909900098730989509866010−14 years99057.
669 880 199 016.
998 747.
8 298 982.
8 298 692.
2 698 937.
798 634.
898 884.
7 898 571.
8 398 831.
2 898 480.4615−19 years98947.
9 598 635.
898 905.
698 579.
698 868.
798 516.
9 898 818.
8 698 449.
5 298 765.
5 298 379.
298 703.
2 398 282.
7320−24 years98715.
7 798 139.
7 498 670.
3 398 072.
8 898 628.
2 797 992.
2 898 569.
7 797 899.
998 513.
9 697 813.
9 598 449.
697 703.
9425−29 years98389.
4 997 109.
2 398 340.
697 022.
3 998 291.
696 903.
8 698 221.
1 396 756.
8 598 157.
7 696 628.
6 698 074.
7 796 458.
2130−34 years97811.
2 795 232.
2 697 757.
795 118.
897 698.
4 294 949.
4 897 613.
2 994 726.
5 597 556.
1 394 650.
6 197 438.
8 794 272.
3235−39 years96927.
9 892 305.
7 596 867.
4 592 153.
696 796.
6 391 921.
3 896 695.
9 791 613.
4 896 630.
991 559.
2 396 493.
790 990.
6440−44 years95838.
3 889 066.
1 495 769.
4 988 870.
695 684.
5 588 571.
4 795 564.
3 388 176.
295 493.
1 388 022.
995 324.
7 487 322.
2645−49 years94511.
7 685 338.
4 294 428.
585 094.
7 494 317.
7 984 705.
8 494 160.
3 884 176.
3 994 010.
3 683 745.
9 193 794.
782 854.
8150−54 years92916.
180 851.
892 812.
3 780 553.
2 592 662.
3 880 052.
4 192 445.
6 479 346.
7 892 252.
7 778 783.
7 791 931.
5 877 538.
6255−59 years90673.
9 574 772.
7 490 539.
6 374 419.
2 290 332.
2 373 802.
2 390 029.
2 872 908.
9 889 686.
7 572 043.
6 289 251.
3 870 471.
0760−64 years87236.
9 566 615.
6 387 059.
766 214.
186 773.
6 265 493.
3 486 354.
564 434.
286 067.
8 463 676.
6 385 291.
4 461 698.
2665−69 years82396.
5 556 281.
3 782 160.
7 755 856.
4 581 778.
1 255 084.
581 225.
253 947.
980 341.
4 152 222.
1 179 418.
2 950 269.
2370−74 years75780.
3 844 881.
8 675 469.
3 944 464.
874 962.
6 643 692.
1 374 239.
3 542 547.
2 374 203.
8 242 643.
4 872 330.
4 939 449.
7375−79 years66143.
6 832 863.
5 865 758.
3 532 506.
6 365 120.
1 931 828.
4 864 209.
930 814.
5 163 173.
8 929 890.
161 465.
7 527 649.
7380−84 years51006.
5 920 101.
4 450 537.
2 919 846.
5 249 778.
4 319 350.
6 148 721.
8 418 602.
5 948 901.
1 619 024.
545 579.
1 616 373.
5785−89 years32023.
2 910 145.
131 587.
229 993.
46 730 894.
789 699.
43 429 951.
439 259.
4 529 682.
789 189.
19 627 226.
487 808.
51 490−94 years14455.
833 341.
92 214 126.
513 284.
85 213 691.
483 156.
41 913 142.
362 954.
55 313 325.
653 312.
20 810 834.
542 104.
84 495−99 years3707.
296 668.
1 363 570.
94 661.
6 323 423.
86 633.
2 653 256.
931 583.
1 613 472.
953 810.
4 562 363.
507 317.
5100+ years456.
4 163.
225 427.
1 364.
134 403.
2162.
9 381.
74 857.
18 447.
558 120.
409 221.
91 219.
531nLx — person-years lived between ages x and x+n<1 year99330.
2 399 151.
8 199 302.
6 699 115.
699 275.
1 999 078.
4 699 238.
5 999 032.
7 899 202.
398 987.
4 899 157.
898 933.
341−4 years396821.
6 396 004 396 676.
7 395 820.
1 396 556.
7 395 636.
3 396 396.
6 395 436.
1 396 211.
7 395 212.
2 396 011.
6 394 948.15−9 years495544.
2 494 352.
5 495 340.
3 494 094.
5 495 182.
1 493 830.
6 494 969.
3 493 560.
2 494 712 493 254.
6 494 453.
2 492 851.210−14 years495014493592494802.
9 493 317.
2 494 628.
8 493 023.
1 494 391.
4 492 709 494 125.
8 492 377.
6 493 836.
349 190 815−19 years494216.
4 492 124.
4 493 996 491 819.
1 493 801.
2 491 469.
2 493 532.
5 491 077.
6 493 260.
8 490 697.
8 492 944.
4 490 191.920−24 years492823.
9 488 386.
2 492 588.
5 488 006.
6 492 360.
7 487 518.
2 492 041.
5 486 932.
2 491 744.
8 486 415.
4 491 378.
3 485 738.
825−29 years490619.
7 481 217 490 364.
3 480 720.
4 490 093.
9 480 009.
1 489 708.
6 479 096.
3 489 402.
8 478 568.
8 488 903.
5 477 223.330−34 years486972.
5 469 209.
8 486 688.
2 468 548.
5 486 364.
4 467 549.
5 485 901.
3 466 225.
3 485 590.
3 465 868.
9 484 951.
6 463 480.
235−39 years482018.
4 453 623.
7 481 695.
7 452 753.
9 481 307.
6 451 427.
5 480 757.
5 449 675.
3 480 417 449 167.
2 479 661.
3 446 016.540−44 years476008.
1 436 309.
5 475 629.
2 435 211.
2 475 142.
7 433 495.
6 474 452.
9 431 195.
9 473 911.
2 429 770.
647 296 242 583 345−49 years468758.
3 415 959.
8 468 293.
3 414 605.
4 467 646.
3 412 388.
2 466 718.
4 409 314.
3 465 869.
6 406 839.
5 464 546.
1 401 530.
450−54 years459300.
6 389 729.
3 458 709.
8 388 099.
5 457 824.
7 385 309.
9 456 538 381 320.
5 455 221.
4 377 755.
1 453 346.
9 370 706.855−59 years445289.
7 354 312.
3 444 516.
9 352 422.
9 443 294.
7 349 080.
2 441 503.
6 344 195.
8 439 912.
1 340 066.
7 436 912.
9 331 135.
460−64 years424748.
8 307 848.
8 423 723.
6 305 777.
1 422 063.
9 302 039.
6 419 647.
3 296 539.
8 416 786.
9 290 351.
3 412 532.928047565−69 years396455.
5 253 352.
4 395 097.
9 251 239.
8 392 890.
8 247 372.
2 389 722.
4 241 654.
4 387 290.
8 237 484 380 436.
9 224 609.570−74 years356345.
5 194 519.
5 354 610.
2 192 576.
7 351 760.
8 188 942.
8 347 695.
1 183 529.
5 345 154.
3 181 424.
7 336 150.
9 167 769.
975−79 years294830.
1 131 910.
4 292 687.
5 130 379.
4 289 188.
1 127 443.
8 284 254 123 028.
5 281 894.
3 121 754.
8 269 409.
6 109 391.880−84 years20870074375.
5 920 643 373 367.
88 202 798.
171 412.
18 197 759.
768 468.
16 197 365.
469 251.
9 182 585.
559 293.
1785−89 years114291.
932 085.
45 112 368.
231 583.
34 109 548.
430 562.
43 105 812.
528 999.
32 105 550.
229 760.
2 993 038.
423 241.
4390−94 years41289.
228 994.
7 440 176.
778 853.
10 538 817.
688 497.
7 137 184.
87 916.
65 838 250.
189 272.
46 829 845.
815 256.
28 195−99 years8039.
6 441 485.
8 987 712.
9 331 475.
7 197 384.
2 011 414.
1 087 038.
9 531 299.
2 757 703.
2 031 909.
6 775 044.
926 647.
919 100+ years812.
222 118.
349 755.
632 120.
616 711.
572 117.
15 674.
609 107.
524 822.
567 253.
671 378.
84 732.
466Appendix 2Age dependency ratioYearUnder workingWorkingOver workingOld dependency ratio19963876269836187260,82 318 619 973 812 770 450 702 336,80078719983714572752199870,78 529 819 993 197 475 054 747 648,65586620003599583746271960,75 455 520 013 156 786 798 329 856,70600720022632788942297780,63 080 420 032 513 689 197 215 744,60635320042434990099293530,59 603 320 052 367 193 075 089 408,5887420062307390058297320,58 634 420 072 284 289 083 899 904,59059620082285489342305410,59 764 720 092 312 688 633 315 328,62330220102320987847318090,62 629 320 112 356 884 654 063 616,64328320122411086137331000,66 417 520 132 471 784 472 576 000,68698520142568985415351630,71 242 820 152 636 084 179 697 664,74046Appendix 3YearGdp_GrowthGdpCLab_RateExpImpPub_Spend_EdHelth_ExpCRes_ExpGov_ConOld_DepP65RLife_ExpPop_GrPop_Den199696,39 261 068,2523,5438,72,61,90,2116,260,26 816,8065,80−0,110,131 997 101,38265068,1579,3527,72,51,70,2316,870,26 857,1066,73−0,180,13 199 894,66213067,4821,0645,62,71,70,2517,280,27 477,4067,07−0,150,131 999 106,35175066,12 084,61262,42,61,80,2317,110,27 047,6965,92−0,180,122 000 110,05171065,53 218,91755,82,91,80,2418,230,32 479,9665,34−0,440,122 001 105,09178064,23 299,62165,93,11,90,2618,120,33 759,6365,23−0,400,122 002 104,74210064,93 813,72646,23,72,10,2917,950,334 812,9664,95−0,450,122 003 107,30258064,74 655,93153,93,62,20,3117,920,326 613,4264,86−0,470,122 004 107,18341065,45 860,43773,93,73,10,2816,970,325 813,7865,31−0,430,122 005 106,38445066,7 607,34648,33,83,40,3616,870,326 214,0065,37−0,370,122 006 108,15580066,39 079,35653,43,83,60,3617,390,330 114,1266,69−0,390,122 007 108,54756067,110 028,87162,24,14,20,417,30,336 113,8767,61−0,260,122 008 105,25959067,412 923,69111,043,70,3917,830,341 813,3967,99−0,080,12 200 992,18923067,610 842,07954,34,64,20,5620,790,360 512,7568,78−0,010,122 010 104,50998067,713 529,39789,64,23,80,5118,730,362 112,6968,940,070,122 011 104,261104068,316 940,912164,44,13,50,5318,050,372 612,7869,830,020,122 012 103,521331068,716 865,212010,84,23,60,5318,780,384 312,9470,240,130,122 013 101,281481068,518 324,813786,94,43,50,6019,670,396 713,1270,760,200,122 014 100,721435068,918 909,314920,94,33,50,5619,510,411 713,5470,930,220,12 201 597,161145069,123 860,517149,14,33,40,5419,440,427 413,8970,981,810,12Appendix 4NRangeMeanStd. D eviationVarianceSkewnessKurtosisStatisticStatisticStatisticStd. E rrorStatisticStatisticStatisticStd.
E rrorStatisticStd. E rrorYear2019,2 005,5001,32 295,916135,000,000,512−1,200,992Gdp_Growth2017,86 654 224 503 533 104,2534564587384301,953 600 785 797 734,89859919108776623,996-, 890,512,021,992GdpC2013100,6 614,5001048,74 004 690,107721997110,263,472,512−1,346,992Lab_Rate204,967,007,33 831,51292,289-, 388,512−1,096,992Exp2023337,9 188,3951582,40 017 076,708350079799,985,488,512-, 880,992Imp2016710,46 536,0501184,40 065 296,800328056093,554,571,512-, 929,992Pub_Spend_Ed202,13,660,1521,6801,463-, 586,512−1,077,992Helth_ExpC202,52,930,2042,9131,834-, 244,512−1,690,992Res_Exp20,39,3820,3 034,13567,018,301,512−1,578,992Gov_Con204,5318,0535,256 151,145551,312,730,512,190,992Old_Dep20,2 368 413 936 106 302,670957104895008,17 059 041 455 911,076290352652806,006,685,512-, 772,992P65R207,32 332 094 384 130 212,791736520047070,5 837 693 107 140 432,6106957238695926,816−1,073,512-, 532,992Life_Exp206,1 200 000 000 000 067,466574742354330,4 889 088 906 217 512,1864670284684904,781,436,512−1,330,992Pop_Gr202,2 808 086 559 130 770-, 73 199 928 626 022,111341443421329,497 934 072 406 078,2483,043,51 211,390,992Pop_Den20,179 247 929 139 254,121048122372788,1 201 995 476 093,005375487186380,0001,754,5121,883,992Valid N (listwise)20Appendix 5Appendix 6CorrelationsGdp_GrowthGdpCLab_RateExpImpPub_Spend_EdHelth_ExpCRes_ExpGov_ConOld_DepP65RLife_ExpPop_GrPop_DenGdp_GrowthPearson Correlation1-, 236-, 572**-, 143-, 182-, 060-, 015-, 271-, 388-, 080,298-, 416-, 486*-, 449*Sig. (2-tailed), 317,008,549,442,801,949,248,091,738,203,068,030,047N2020202020202020202020202020GdpCPearson Correlation-, 2361,746**, 940**, 953**, 819**, 777**, 953**, 690**, 844**, 566**, 944**, 588**-, 387Sig. (.
2-tailed), 317,000,000,000,000,000,000,001,000,009,000,006,092N2020202020202020202020202020Lab_RatePearson Correlation-, 572**, 746**1,637**, 664**, 347,433,634**, 361,409,019,861**, 682**, 253Sig. (2-tailed), 008,000,003,001,134,057,003,118,074,935,000,001,282N2020202020202020202020202020ExpPearson Correlation-, 143,940**, 637**1,997**, 850**, 766**, 930**, 682**, 932**, 680**, 893**, 720**-, 552*Sig. (2-tailed), 549,000,003,000,000,000,000,001,000,001,000,000,012N2020202020202020202020202020ImpPearson Correlation-, 182,953**, 664**, 997**1,840**, 748**, 937**, 700**, 931**, 650**, 914**, 724**-, 524*Sig. (2-tailed), 442,000,001,000,000,000,000,001,000,002,000,000,018N2020202020202020202020202020Pub_Spend_EdPearson Correlation-, 060,819**, 347,850**, 840**1,906**, 902**, 708**, 870**, 887**, 665**, 393-, 682**Sig.
(2-tailed), 801,000,134,000,000,000,000,000,000,000,001,087,001N2020202020202020202020202020Helth_ExpCPearson Correlation-, 015,777**, 433,766**, 748**, 906**1,816**, 497*, 681**, 794**, 631**, 311-, 492*Sig. (2-tailed), 949,000,057,000,000,000,000,026,001,000,003,182,028N2020202020202020202020202020Res_ExpPearson Correlation-, 271,953**, 634**, 930**, 937**, 902**, 816**1,802**, 885**, 647**, 895**, 573**-, 493*Sig.
(2-tailed), 248,000,003,000,000,000,000,000,000,002,000,008,027N2020202020202020202020202020Gov_ConPearson Correlation-, 388,690**, 361,682**, 700**, 708**, 497*, 802**1,789**, 429,686**, 496*-, 547*Sig. (2-tailed), 091,001,118,001,001,000,026,000,000,059,001,026,013N2020202020202020202020202020Old_DepPearson Correlation-, 080,844**, 409,932**, 931**, 870**, 681**, 885**, 789**1,741**, 764**, 615**-, 741**Sig. (2-tailed), 738,000,074,000,000,000,001,000,000,000,000,004,000N2020202020202020202020202020P65RPearson Correlation, 298,566**, 019,680**, 650**, 887**, 794**, 647**, 429,741**1,348,186-, 796**Sig. (.
2-tailed), 203,009,935,001,002,000,000,002,059,000,133,432,000N2020202020202020202020202020Life_ExpPearson Correlation-, 416,944**, 861**, 893**, 914**, 665**, 631**, 895**, 686**, 764**, 3481,729**-, 209Sig. (2-tailed), 068,000,000,000,000,001,003,000,001,000,133,000,377N2020202020202020202020202020Pop_GrPearson Correlation-, 486*, 588**, 682**, 720**, 724**, 393,311,573**, 496*, 615**, 186,729**1-, 129Sig. (2-tailed), 030,006,001,000,000,087,182,008,026,004,432,000,589N2020202020202020202020202020Pop_DenPearson Correlation-, 449*-, 387,253-, 552*-, 524*-, 682**-, 492*-, 493*-, 547*-, 741**-, 796**-, 209-, 1291Sig.
(2-tailed), 047,092,282,012,018,001,028,027,013,000,000,377,589N2020202020202020202020202020**. Correlation is significant at the 0.01 level (2-tailed).*. Correlation is significant at the 0.05 level (2-tailed).Appendix 7The annual GDP growth rate (%)GDP per capita ($)The share of economically active population in the age group 15−64The share of exports of goods and services in GDP (%)The share of imports of goods and services in GDP (%)The share of public expenditure on education in GDP (%)Total expenditure on health (US$)Life expectancy at birth (years)Central Federal district108,53 451 517,259,3 256 145,5192955,64,4 402 245,871,93The North-Western Federal district109,66 383 339,459,952 294,157122,54,3 131 845,771,25Southern Federal district114,67 229 214,558,419 216,9122724,388 815,471,76The North Caucasian Federal district113,38 127 042,159,81 279,82187,93,851 145,173,95Volga Federal district111,54 263 976,258,76 883 918 950,64,4 197 216,870,06Urals Federal district112,42 583 243,959,76 395 910 417,54,2 143 598,370,06Siberian Federal district107,9 926 917 159,236051,29 274,24,1 152 787,768,63The far Eastern Federal district106,70 431 768,16128187,5 121 054,283177,167,81Central Federal district109,92 494 482,758,5 255 352,6173818,14,3 402 245,872,1The North-Western Federal district105,83 403 612,95955750,3 545 314,2131845,771,42Southern Federal district112,20 256 444,657,620 215,511047,64,488 815,471,74The North Caucasian Federal district115,60 146 117,259,31 286,42077,83,751 145,174,11Volga Federal district107,76 284 810,457,863 727,5176404,5 205 720,870,2Urals Federal district106,62 619 540,958,737 735,58684,14,3 144 855,170,2Siberian Federal district106,82 287 293,858,234 970,48072,94,3 157 112,268,85The far Eastern Federal district104,85 454 144,160,128 681,310653,14,286 876,168,21Central Federal district108,66 535 430,557,6 168 875,9108797,54,4 402 245,872,72The North-Western Federal district106,51 427 922,957,939 697,734008,84,3 131 845,771,7Southern Federal district109,69 280 342,356,713 582,37479,24,288 815,472,13The North Caucasian Federal district113,56 164 905,958,71 108,41072,83,951 145,174,63Volga Federal district108,22 308 508,556,84 204 411 397,94,2 214 104,970,71Urals Federal district105,73 652 935,457,727 282,27086,54,3 148 053,370,38Siberian Federal district110,22 316 380,157,230 221,46855,14,3 167 320,669,31The far Eastern Federal district113,73 518 185,559,220 633,45882,84,290 849,468,68.
