18 300 2000 filial piety
300 SPSS 1 1950 22.3 1995 39.7 1995 125.6 2005 127.7 2050 104.9 15-64 1995 87.2 2050 57.1 65 1995 18.3 14.62045 34.0 2050 33.3 31.8UN Population Division, 2000 : 49-54 1 1995 44.9 2035 53.0 2050 51.5 1950-1955 5.401955-1960 6.33 1990-1995 1.70 1950-1955 47.5 1990-1995 70.9 1950-1995 18.4 12.6 UN Population Division, 2000 : 55-60 1955 1965 1975 1985 1995 1 21,422 28,530 35,281 40,806 44,949 100 96.1 100.1 101.5 101.7 101.5 0-4 15.6 16.5 12.7 9.1 7.7 60 5.6 5.1 5.8 6.8 8.9 65 3.7 3.3 3.6 4.3 5.6 19.8 18.7 19.9 24.5 29.2 216 288 356 412 454 1955 1965 1975 1985 1995 89,815 98,881 111,524 120,837 125,472 100 96.5 96.4 96.9 96.7 96.2 0-4 10.6 8.3 8.9 6.2 4.8 60 8.1 9.6 11.7 14.8 20.5 65 5.3 6.2 7.9 10.3 14.6 23.6 27.3 30.4 35.2 39.7 238 262 295 320 332 United Nations Population Division, World Population Projects, The 1998 Revision
2 10 20 65-69 85 36 77 85 65-84 2 nursing home 11 16 Morginstin, 1989 : 123 60 60 70 46No.1900, 1996, p.46 2000 111,997 1 75.8 303,583 1 23.9 2002 409 1985-1998 5,830 9.7 16.6 280 1 4,910 53 1995 4.72000 17.42000b 402004224 Replacement Migration 3 2050 1 1 1995 4.8 2025 2.2 2050 1.7 1995 12.6 2020 5.7 2050 2.4 2 10 20 10 1984 2010 1951 1947 1971 20 2007 2032 2012 2011 2028 UN Population Division, 1999. 3 10 20 23 22 61 64 57 2050 1 65 70 75 80 2.40 1.71 3.55 2.40 5.61 3.64 UN Population Division, Replacement Migration, 2000 10.44 6.48
4.8 1995 77 1995 2020 82 UN Population Division, 2000 : 49-60 1 4 1998 1,111,778 1,065,391 495,631 (169,081) 53,716 2,726,565 40.8 39.1 18.2 (6.2) 1.97 100.00 5 1998 750,417 100.0(%) 378,061 109,443 15,101 954 503,559 67.1(%) http//www.ipss.go.jp/japanese/kyuhuhi-h11/2/no2.html 61 GDP 1 1995 1984 1978 1987 GDP 5.7 10.42 13.62 20.53 OECD, 1999, Social Expenditure Database 1980-1996 1977 24.49
4 67.1 5 GDP 1 GDP1 GDP 6 2 1973 5 2001 1 319.5 1 203.6 212.1 1975 30.1 2000 209.8 7 26.2 65.7200439 1988 2008 2000 32.5 3 formal sectorinformal sector
7OECD 0 64 100 1987 1993 1990 1993 1994 65 74 314 254 230 309 160 OECD1997200051 65 417 388 283 479 162 75 533 559 343 573 168 1993 602000 45199613 1/3 7 0 64 100 65 479 162 75 573168 18
300 16 / 7 multistage cluster sampling / / / / 312 500 500 3 94 50 10 500 30 270 1 8 2 8 147 (47.3%) 131 (48.7%) 278 (47.9%) 164 (52.7%) 138 (51.3%) 302 (52.1%) 311 (100.0%) 269 (100.0%) 580 (100.0%) 45 (14.6%) 35 (14.8%) 80 (14.7%) 204 (66.2%) 157 (66.5%) 361 (66.4%) 59 (19.2%) 44 (18.6%) 103 (18.9%) 308 (100.0%) 236 (100.0%) 544 (100.0%) 46 (14.7%) 39 (14.8%) 85 (14.8%) 134 (42.9%) 106 (40.3%) 240 (41.7%) 132 (42.3%) 118 (44.9%) 250 (43.5%) 312 (100.0%) 263 (100.0%) 575 (100.0%) 20 85 (27.2%) 32 (11.9%) 117 (20.1%) 30 81 (26.0%) 49 (18.1%) 130 (22.3%) 40 78 (25.0%) 61 (22.6%) 139 (23.9%) 50 45 (14.4%) 48 (17.8%) 93 (16.0%) 60 23 (7.4%) 80 (29.6%) 103 (17.7%) 312 (100.0%) 270 (100.0%) 582 (100.0%)
24.224.9 2.3 9 93.3 25.8 10 blame the victim 59.0 38.3 11 * 9 42 59 31 27 49 11 49 4 7 19 (14.1%) (19.8%)* (10.4%) ( 9.1%) (16.4%) ( 3.7%) (16.4%) ( 1.3%) ( 2.3%) ( 6.4%) 298 (100.0%) * 19.8% IMF 3 21 39 39 24 1 67 1 65 9 ( 1.1%) ( 7.8%) (14.5%) (14.5%) ( 8.9%) ( 0.4%) (24.9%) ( 0.4%) (24.2%) ( 3.3%) 269 (100.0%) 45 80 70 66 73 12 116 5 72 28 ( 7.9%) (14.1%) (12.3%) (11.6%) (12.9%) ( 2.1%) (20.5%) ( 0.9%) (12.7%) ( 4.9%) 567 (100.0%) 10 71 (22.9%) 82 (30.6%) 153 (26.5%) 158 (51.0%) 168 (62.7%) 326 (56.4%) 48 (15.5%) 9 ( 3.4%) 57 ( 9.9%) 32 (10.3%) 7 ( 2.6%) 39 ( 6.7%) 1 ( 0.3%) 2 ( 0.7%) 3 ( 0.5%) 310 (100.0%) 268 (100.0%) 578 (100.0%)
12 13 84.9 11 79 (23.3%) 115 (43.6%) 194 (33.7%) 34 (10.9%) 21 ( 8.0%) 55 ( 9.5%) 11 (3.5%) 6 ( 2.3%) 17 ( 3.0%) 116 (37.2%) 71 (26.9%) 187 (32.5%) 68 (21.8%) 30 (11.4%) 98 (17.0%) 4 ( 1.3%) 21 ( 8.0%) 25 ( 4.3%) 312 (100.0%) 264 (100.0%) 576 (100.0%) 12 43 (55.8%) 44 (61.1%) 41 (57.7%) 128 (58.2%) 34 (44.2%) 28 (38.9%) 30 (42.3%) 92 (41.8%) 77 (100.0%) 23 (69.7%) 72 (100.0%) 9 (37.5%) 71 (100.0%) 14 (40.0%) 220 (100.0%) 46 (50.0%) 10 (30.3%) 15 (62.5%) 21 (60.0%) 46 (50.0%) 33 (100.0%) 24 (100.0%) 35 (100.0%) 92 (100.0%) chi-square=.432df 2p.806 chi-square=8.021df 2p.018 33%
11.3 56 1 Decommodification Esping-Andersen, 1990 14 13 5 ( 1.9%) 5 ( 0.9%) 6 ( 1.9%) 25 ( 9.4%) 31 ( 5.4%) 41 (13.1%) 87 (32.7%) 128 (22.1%) 151 (48.4%) 117 (44.0%) 268 (46.4%) 114 (36.5%) 32 (12.0%) 146 (25.3%) 312 (100.0%) 266 (100.0%) 578 (100.0%) 14 19 (43.2%) 137 (67.8%) 44 (74.6%) 200 (65.6%) 25 (56.8%) 65 (32.2%) 15 (25.4%) 105 (34.4%) 44 (100.0%) 202 (100.0%) 59 (100.0%) 305 (100.0%) 17 (48.6%) 122 (77.7%) 36 (81.8%) 175 (74.2%) 18 (51.4%) 35 (22.3%) 8 (18.2%) 61 (25.8%) 35 (100.0%) 157 (100.0%) 44 (100.0%) 236 (100.0%) 15 29 (14.5%) 48 (25.7%) 77 (19.9%) 152 (76.0%) 127 (67.9%) 297 (72.1%) * 19 ( 9.5%) 12 ( 6.4%) 31 ( 8.0%) 200 (100.0%) 187 (100.0%) 387 (100.0%) *
65.6 74.2 74.667.8 43.2 81.8 77.7 48.6 15 14.5 25.7 10 76 67.9 3 16 40.1 47.3NPO 50 17 18 16 146 (46.8%) 104 (38.8%) 250 (43.1%) 128 (41.0%) 121 (45.1%) 249 (42.9%) 14 ( 4.5%) 24 ( 9.0%) 38 ( 6.6%) 24 ( 7.7%) 19 ( 7.1%) 43 ( 7.4%) 312 (100.0%) 268 (100.0%) 580 (100.0%) 17 124 (40.1%) 123 (47.3%) 247 (43.4%) NPO 81 (26.2%) 37 (14.2%) 118 (20.7%) 15 ( 4.9%) 24 ( 9.2%) 39 ( 6.9%) 79 (25.6%) 67 (25.8%) 146 (25.7%) 10 ( 3.2%) 9 ( 3.5%) 19 ( 3.3%) 309 (100.0%) 260 (100.0%) 569 (100.0%)
18 Constant R 2.133[.170]a(.057)b.0489[.086](.045).0164[.008](.150)*.224[.081](.211)**.200[.082](.214)* 6.571.064.002288[.279](.001).134[.150](.098).00320[.009](.040).112[.096](.124).251[.180](.156) 3.898.070 a=std.error, b=beta.05<p<.10, *p<.05, **p<.01, ***p<.001 4 9.0 32.3 67.7 57.8 90 66.8 19 20 21 13.5 9.9 30.3 16.0
12.6 1 13 2.9 52.6 48.5 22 p<.05 19 100 (32.3%) 24 (9.0%) 124 (21.5%) 1 ( 0.3%) 5 ( 1.9%) 6 ( 1.0%) 179 (57.7%) 155 (57.8%) 334 (57.8%) 23 ( 7.4%) 76 (28.4%) 99 (17.1%) 7 ( 2.3%) 8 ( 3.0%) 15 ( 2.6%) 310 (100.0%) 268 (100.0%) 578 (100.0%) 20 44.3% 25.4% 53.1% 65.5% 1.7% 3.8% 0.9% 5.3% 1998 21 42 (13.5%) 26 (9.9%) 68 (11.9%) 93 (30.3%) 42 (16.0%) 135 (23.6%) 3 ( 1.0%) 33 (12.6%) 36 ( 6.3%) 163 (52.6%) 127 (48.5%) 290 (50.7%) 9 ( 2.9%) 34 (13.0%) 43 ( 7.5%) 310 (100.0%) 262 (100.0%) 572 (100.0%)
23 22 Constant R 2.09773[.084]a(.083)b.00408[.004](.073).08498[.042](.154)*.0382[.040](.069).0690[.040](.144) 3.189.046.286[.109](.261).00426[.003](.155).104[.060](.174).02471[.038](.064).0704[.073](.099) 2.467 a=std.error, b=beta.05<p<.10, *p<.05, **p<.01, ***p<.001 = 22.107 23 Constant R 2.517[.156]a(.228)b***.01979[.008](.186)**.02865[.079](.027)*.0145[.074](.014).0859[.074](.094) 6.000.100.801[.244](.326)***.0163[.008](.212)*.04389[.139](.032).009515[.088](.011).236[.162](.148) 6.785.135 a=std.error, b=beta.05<p<.10, *p<.05, **p<.01, ***p<.001
90 3 2004,
1999, Vol. 35, No. 1. 1996, 66 1999, 5 2 2000, 2004, 1992, 2003, 1998, Esping Andersen, G.,1990, The Three World of Welfare Capitalism, Polity Press. Zeng Yi and and Linda George, 1999, Extreamly Rapid Ageing and the Living Arrangements of Older Persons ; The Case of China, UN Population Division. UN Population Division, 2000. 3. Replacement Migration : Is It a Solution to Declining and Ageing Populations? Makoto Atoh, 2000, The Coming of a Hyper-aged and Depopulating Society and Population Policies : The Case of Japan, Expert Group Meeting on Policy Responses to Population Ageing and Population Decline, UN Population Division. Yukiko Katsumata, 2000, The Impact of Population Decline and Population Aging in Japan from the Perspectives of Social and Labor Policy, UN Population division. Namhoon Cho, 2000, Policy Responses to Population Ageing and Population Ageingin Korea, UN Population division. Ik Ki Kim, 2000, Policy Responses to low Fertility and Population Ageing in Korea, UN Population division. Sung-Jae Choi et al., 2000, A Comparative Study on Long-Term Care Policy for the Elderly in Korea and Japan, Journal of the Korea Gerontological Society, Vol. 20, No. 3. OECD, 1997, Ageing in OECD Countries : A Critical Policy Challenges. 2004 10 15