2018 7 Jul. 2018 4 148 Journal of Chinese Women's Studies No. 4 Ser. No. 148 * 210023 CFPS 2010 C913. 68 A 1004-2563 2018 04-0019-14 Where does the Time Go Gender Differences in Time Use over the Life Course in China XU Qi School of Social and Behavioral Sciences Nanjing University Nanjing 210023 Jiangsu Province China Key Words time use gender differences life course modernization Abstract Based on the survey data of China Family Panel Study in 2010 this paper explores the gender differences in time use over the life course in China. The main findings are 1 in general men spend more time in work and leisure while women spend more time in housework and physiological activity but the difference is rather small when people are single and increase substantially with marriage and childbearing 2 marriage especially childbearing have significant impact on women's time use but the influence on men is negligible. The study points out that the rapid pace of modernization in China is not enough to eliminate the gender differences in time use. The strike of marriage and childbearing on women if expected can have significant influence on women's marriage and reproduction behavior. 1 PP3-12 2 PP285-303 3 PP1688-1698 1987- * 19
1 4 PP44-48 5 PP117-143 6 PP166-192 1 24 7 PP86-97 8 PP159-195 M. James M. Raymo economic /bargaining 9 PP471-492 theory S. Garys Becker 10 PP833-858 20
10 11 gender role theory 12 PP847-865 13 PP652-688 21
16 PP149-166 8 6 1 1 2 14 PP152-156 20 60 2 time use survey 15 PP1480-1523 22
17 PP149-164 7 21 4 20 60 2008 5 /7 2 /7 18 PP116-122 China Panel Family Study CFPS 2010 8 CFPS CFPS CFPS 2010 7 21 CFPS CFPS 6 CAPI 0-2 3-5 6-14 15 24 19 45 PP449-465 18-45 14251 13977 23
1 1 33. 06 7. 74 33. 05 7. 73 33. 05 7. 73 % 75. 06 72. 34 73. 79 24. 94 27. 66 26. 21 % 68. 80 68. 27 68. 55 31. 20 31. 73 31. 45 8. 03 4. 47 6. 96 4. 81 7. 46 4. 68 1. 49 0. 78 1. 62 0. 87 1. 56 0. 83 % 95. 20 94. 83 95. 03 4. 80 5. 17 4. 97 % 12. 66 22. 66 17. 35 6. 48 6. 53 6. 50 0-2 20. 26 18. 08 19. 24 3-5 12. 62 12. 18 12. 41 6-14 31. 20 28. 96 30. 15 15 16. 78 11. 59 14. 34 6588 7419 13977 multiple regression model β 1k β 4k 20 seemingly uncorrelated regression y 1 = β 1k X k + 1 y 2 = β 2k X k + 2 y 3 = β 3k X k + 3 k 1 4 1 y 4 = β 4k X k + 4 E i j = σ ij 0 y 1 y 4 X k k β 1k β 4k 24
1 2 2. 5 0. 9 4. 0 4. 1 0. 7 0. 4 2 2. 161 2 2 1 2. 088 0. 466 0. 364 25
2 = 0 0-2 3-5 6-14 1 2-0. 466 *** 2. 161 *** - 2. 088 *** 0. 364 *** - 0. 332 *** 0. 541 *** - 0. 457 *** 0. 298 ** 0. 028 0. 062 0. 037 0. 050 0. 062 0. 136 0. 079 0. 110-0. 048 * 0. 350 *** - 0. 004-0. 279 *** - 0. 045 * 0. 365 *** - 0. 028-0. 280 *** 0. 019 0. 043 0. 026 0. 035 0. 020 0. 043 0. 025 0. 035 0. 000-0. 005 *** 0. 000 0. 004 *** 0. 000-0. 005 *** 0. 001 0. 004 *** 0. 000 0. 001 0. 000 0. 001 0. 000 0. 001 0. 000 0. 001-0. 253 *** - 0. 160 0. 074 0. 433 *** - 0. 251 *** - 0. 173 0. 091 0. 425 *** 0. 043 0. 095 0. 057 0. 077 0. 043 0. 094 0. 054 0. 076-0. 176 *** 0. 133-0. 115 * 0. 237 *** - 0. 177 *** 0. 166 * - 0. 153 ** 0. 240 *** 0. 038 0. 084 0. 051 0. 068 0. 038 0. 083 0. 048 0. 068-0. 012 ** 0. 028 *** - 0. 044 *** 0. 055 *** - 0. 011 ** 0. 019 * - 0. 035 *** 0. 055 *** 0. 004 0. 008 0. 005 0. 007 0. 004 0. 008 0. 005 0. 007 0. 027-0. 217 *** 0. 064 ** 0. 082 * 0. 030-0. 219 *** 0. 061 ** 0. 081 * 0. 018 0. 040 0. 024 0. 032 0. 018 0. 039 0. 023 0. 032 0. 157 * - 0. 441 ** - 0. 139 0. 435 *** 0. 151 * - 0. 358 * - 0. 233 ** 0. 450 *** 0. 066 0. 147 0. 088 0. 118 0. 066 0. 145 0. 084 0. 118 0. 283 *** - 0. 126 0. 224 ** - 0. 381 *** 0. 564 *** - 1. 161 *** 0. 621 *** - 0. 060 0. 059 0. 130 0. 078 0. 105 0. 085 0. 187 0. 108 0. 152 0. 046-0. 935 *** 2. 823 *** - 1. 871 *** 0. 145* - 2. 811 *** 4. 869 *** - 2. 106 *** 0. 050 0. 112 0. 067 0. 090 0. 070 0. 153 0. 089 0. 125 0. 110 0. 183 1. 385 *** - 1. 535 *** 0. 245 ** - 0. 899 *** 2. 668 *** - 1. 741 *** 0. 063 0. 139 0. 083 0. 112 0. 085 0. 185 0. 107 0. 151 0. 075 0. 445 ** 0. 698 *** - 1. 237 *** 0. 152-0. 512 ** 1. 629 *** - 1. 203 *** 0. 062 0. 137 0. 082 0. 111 0. 080 0. 174 0. 101 0. 142 *** 0. 124 0. 654 0. 298 ** - 1. 055 *** 0. 088-0. 077 1. 111 *** - 0. 987 *** 15 0. 078 0. 174 0. 104 0. 140 0. 095 0. 208 0. 120 0. 169 * * = 0 * * 0-2 * 3-5 * 6-14 * 15-0. 533 *** 1. 653 *** - 0. 359 * - 0. 654 ** 0. 114 0. 250 0. 144 0. 203-0. 176 * 3. 437 *** - 3. 771 *** 0. 488 ** 0. 085 0. 187 0. 108 0. 152-0. 255 * 1. 765 *** - 2. 148 *** 0. 422 * 0. 101 0. 221 0. 128 0. 180-0. 139 1. 551 *** - 1. 470 *** - 0. 064 0. 082 0. 179 0. 104 0. 146 0. 126 1. 070 *** - 1. 251 *** - 0. 157 0. 102 0. 224 0. 129 0. 182 11. 973 *** - 1. 266 * 2. 808 *** 10. 067 *** 11. 837 *** - 0. 340 2. 021 *** 10. 124 *** 0. 280 0. 620 0. 371 0. 498 0. 282 0. 616 0. 356 0. 501 R-squared 0. 050 0. 125 0. 347 0. 126 0. 053 0. 146 0. 407 0. 129 13 977 13 977 13 977 13 977 13 977 13 977 13 977 13 977 * p < 0. 05 ** p < 0. 01 *** p < 0. 001 26
1 1 2 2 0. 5 6 0 1 2 2 2 1 1. 161 0. 621 0. 564 2. 811 2. 106 1 3 3 2 0 2 2 1 0 2 27
3 3 4 5 6 3 3 4-0. 470 *** 2. 304 *** - 2. 211 *** 0. 333 *** - 0. 322 *** 2. 574 *** - 2. 422 *** 0. 153 0. 034 0. 076 0. 045 0. 061 0. 056 0. 123 0. 074 0. 099-0. 048 * 0. 349 *** - 0. 003-0. 279 *** - 0. 047 * 0. 352 *** - 0. 005-0. 280 *** 0. 019 0. 043 0. 026 0. 035 0. 019 0. 043 0. 026 0. 035 0. 000-0. 005 *** 0. 000 0. 004 *** 0. 000-0. 005 *** 0. 000 0. 004 *** 0. 000 0. 001 0. 000 0. 001 0. 000 0. 001 0. 000 0. 001-0. 253 *** - 0. 151 0. 066 0. 431 *** - 0. 251 *** - 0. 154 0. 069 0. 430 *** 0. 043 0. 095 0. 057 0. 077 0. 043 0. 095 0. 057 0. 077-0. 183 *** 0. 342 ** - 0. 294 *** 0. 191 * - 0. 177 *** 0. 131-0. 114 * 0. 238 *** 0. 048 0. 106 0. 063 0. 085 0. 038 0. 084 0. 051 0. 068-0. 012 ** 0. 027 *** - 0. 043 *** 0. 055 *** - 0. 003 0. 052 *** - 0. 064 *** 0. 043 *** 0. 004 0. 008 0. 005 0. 007 0. 005 0. 010 0. 006 0. 008 0. 027-0. 216 *** 0. 063 ** 0. 081 * 0. 028-0. 213 *** 0. 061 * 0. 079 * 0. 018 0. 040 0. 024 0. 032 0. 018 0. 040 0. 024 0. 032 0. 157 * - 0. 437 ** - 0. 143 0. 434 *** 0. 157 * - 0. 441 ** - 0. 139 0. 435 *** 0. 066 0. 147 0. 088 0. 118 0. 066 0. 147 0. 088 0. 118 = 0 0. 283 *** - 0. 126 0. 224 ** - 0. 381 *** 0. 287 *** - 0. 116 0. 216 ** - 0. 386 *** 0. 059 0. 130 0. 078 0. 105 0. 059 0. 130 0. 078 0. 105 0-2 0. 046-0. 933 *** 2. 821 *** - 1. 871 *** 0. 051-0. 923 *** 2. 813 *** - 1. 877 *** 0. 050 0. 111 0. 067 0. 090 0. 050 0. 112 0. 067 0. 090 3-5 0. 110 0. 185 1. 382 *** - 1. 535 *** 0. 116 0. 200 1. 371 *** - 1. 543 *** 0. 063 0. 139 0. 083 0. 112 0. 063 0. 139 0. 083 0. 112 6-14 0. 075 0. 445 ** 0. 697 *** - 1. 237 *** 0. 082 0. 466 *** 0. 681 *** - 1. 248 *** 0. 062 0. 137 0. 082 0. 111 0. 062 0. 137 0. 082 0. 111 *** 0. 124 0. 646 0. 305 ** - 1. 053 *** 0. 134 0. 682 *** 0. 275 ** - 1. 070 *** 15 0. 078 0. 174 0. 104 0. 140 0. 078 0. 174 0. 104 0. 140 * 0. 013-0. 417*** 0. 356 *** 0. 092 0. 057 0. 127 0. 076 0. 102 * - 0. 018 ** - 0. 052 *** 0. 042 *** 0. 027 * 0. 006 0. 013 0. 008 0. 011 11. 975 *** - 1. 319 * 2. 853 *** 10. 079 *** 11. 894 *** - 1. 495 * 2. 992 *** 10. 184 *** 0. 280 0. 620 0. 371 0. 499 0. 281 0. 622 0. 373 0. 501 R-squared 0. 050 0. 125 0. 348 0. 126 0. 051 0. 126 0. 348 0. 127 13 977 13 977 13 977 13 977 13 977 13 977 13 977 13 977 * p < 0. 05 ** p < 0. 01 *** p < 0. 001 3 28
3 4 3 29
5 6 4 30
3 5 6 8 CFPS 2010 21 PP33-43 L. Larry L. Bumpass 22 PP215-235 23 24 PP48-53 31
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