% % * ~ 14 % 15~ 64 % 65 %

2018 4 * 210095 DOI:10.13246/j.cnki.jae.2018.04.002 2000 65 7. 5%2010 65 10. 06% 2. 56 2009 20032006 2011 19782009 2008 2013 2013 20032010 2010 * 71473123 14ZDA037 15

2018 4 2014 1 2000 2005 2010 3 65 8. 9%2000 1. 9 65 7% * 2000 2000 2005 2010 1 0~ 14 % 15~ 64 % 65 % 2000 22. 90 18. 42 25. 52 70. 2 75. 16 66. 98 7. 00 6. 42 7. 5 2005 19. 55 16. 60 21. 95 71. 37 74. 19 68. 50 9. 07 8. 49 9. 55 2010 16. 60 14. 08 19. 16 74. 50 78. 12 70. 78 8. 90 7. 8 10. 06 2000 2005 1% 2010 2012 2015 2009 1 * 1956 65 4% 4% ~ 7% 7% 16

2 1 2013 2015 2015 2016 Y i = α + βl i + γl i D i + θx i + ε i 1 Y i L i 2015 X i ε i 17

2018 4 2013 1 7 7 2010 31 346 20100 8 1 2 3 2016 2016 11799 4360 3920 3519 2016 2013 2013 2015 2016 2 3 60 0. 694 0. 687 0. 724 0. 760 18

2 0. 73 0. 32 / 59. 92 53. 76 7. 43 16. 41 / 49. 74 10. 75 6. 25 2. 32 4. 05 1. 56 1 = 0 = 0. 15 0. 36 0. 15 0. 23 10. 03 15. 95 5. 69 6. 15 0. 99 23664. 63 596. 99 740. 63 2. 54 3. 71 3 / / <60 10. 037 0. 687 57. 829 5. 840 60 5. 642 0. 694 58. 741 5. 801 <60 11. 704 0. 760 60. 541 8. 841 60 5. 450 0. 724 62. 989 6. 107 <60 60 1 4 1 2-0. 001 1% 19

2018 4 1 0. 1% 3 4 1% 5 6 1% 5% 4 1 1-0. 001-0. 001 *** -1. 049-2. 928-0. 024 *** -0. 003 ** -10. 510-2. 186 0. 012*** 3. 418 0. 004 0. 327-0. 005*** -8. 496 0. 005*** 6. 536-0. 005 * -1. 953 2 3 0. 001 0. 626 0. 010 1. 064-0. 002 *** -6. 774 0. 000 0. 147-0. 002-1. 318 0. 126 *** -0. 001 5. 437-0. 053 0. 000 *** 15. 686 0. 000 *** 15. 664-0. 004 ** 0. 001-2. 356 0. 988 _cons 0. 807 *** 19. 871 0. 759 *** 26. 169 0. 267 *** 3. 005 0. 239 0. 602 0. 833 1. 364-1. 298-0. 547-0. 602 *** -5. 779-0. 759 *** -6. 139-0. 136-0. 330 10. 820 *** 2. 735 0. 013 *** 6. 883 4 5 0. 196 *** 2. 917 2. 064 *** 6. 980-0. 645-1. 472-1. 135-0. 634-0. 471 *** -9. 881-0. 927 *** -7. 877-0. 546 ** -2. 116-0. 743-0. 256 0. 018 *** 14. 877 24. 026 *** 3. 439 34. 413 *** 6. 418 0. 048 *** 3. 946 0. 169 *** 3. 084 0. 077 0. 913-0. 796 ** -2. 417 0. 013 0. 776-0. 113 *** -6. 670 0. 194 *** 3. 437 2. 832 *** 5. 161 0. 002 *** 9. 031-0. 033-0. 034 6 0. 052 ** 2. 142 0. 350 *** 3. 252-0. 269 * -1. 706 0. 168 0. 256 0. 085 *** 4. 953-0. 254 *** -6. 101-0. 050-0. 530-0. 918-0. 864 0. 007 *** 18. 556 0. 357 0. 194 4328 7422 3913 6955 3669 6452 * ** *** 10% 5% 1% 20

2011 2012 Li 2013 5 1% 10% 3 5 2 7 Dum_ Dum_ 0. 017 1. 362 0. 045 *** 3. 583 0. 010*** 2. 936-0. 014-1. 028-0. 005*** -7. 850 0. 006*** 7. 494-0. 005 ** -2. 207 8 9 0. 011 1. 360-0. 015 * -1. 840-0. 002-0. 677-0. 001-0. 126-0. 001 *** -4. 770-0. 001 * -1. 836-0. 002-1. 621 0. 133 *** -0. 004 5. 632-0. 251 0. 000 *** 15. 689 0. 000 *** 22. 171-0. 004 ** -0. 000-2. 499-0. 246 _cons 0. 608 *** 30. 572 0. 702 *** 59. 925-4. 851 ** -2. 333 4. 003 * 1. 872 0. 965 1. 588-1. 301-0. 554-0. 598 *** -5. 770-0. 765 *** -6. 221-0. 125-0. 305 10. 382 *** 2. 618 0. 013 *** 6. 870 10 11-5. 661 *** -3. 606-0. 194-0. 124 0. 179 0. 412 1. 743 0. 970-0. 561 *** -11. 742-0. 777 *** -6. 649-0. 687 *** -2. 631 0. 408 0. 139 0. 014 *** 12. 506 38. 724 *** 11. 332 63. 924 *** 29. 374-0. 322-1. 117 1. 035 *** 3. 492 0. 114 1. 348-0. 696 ** -2. 135 0. 010 0. 620-0. 118 *** -6. 976 0. 202 *** 3. 591 2. 855 *** 5. 188 0. 002 *** 9. 065 12-1. 096 * -1. 914-0. 561-0. 981-0. 338 ** -2. 107 0. 365 0. 557 0. 093 *** 5. 282-0. 283 *** -6. 620-0. 056-0. 590-1. 159-1. 076 0. 008 *** 18. 024 3. 099 *** 6. 487 6. 238 *** 6. 323 4328 7422 3913 6955 3669 6452 * ** *** 10% 5% 1% 9 21

2018 4 10 5 4 2010 65 10. 88% 65 9. 34% 7 70% 14. 3% 23. 2% 70. 4% 2013 6 20002011 0. 67 0. 694 0. 65 0. 509 65 8. 76% 10. 88% 2. 21 65 8. 84% 9. 34% 0. 5 2012 2012 2012 2000 2000 52. 29 / 51. 09 / 2015 155. 53 / 140. 14 / 2. 97 2. 74 22

6 / / 2000 7944. 87 5304. 31 0. 668 52. 29 3554. 33 2300. 26 0. 647 51. 09 2001 7777. 42 4886. 66 0. 628 53. 42 3245. 93 1939. 1 0. 597 61. 14 2002 7797. 85 4882. 58 0. 626 56. 06 3064. 53 1659. 1 0. 541 63. 18 2003 7681. 49 4659. 47 0. 607 63. 22 2834. 39 1427. 77 0. 504 71. 14 2004 7668. 98 4774. 59 0. 623 71. 00 2778. 41 1454. 53 0. 524 82. 34 2005 7641. 2 4909. 48 0. 643 88. 31 2837. 94 1510. 79 0. 532 95. 16 2006 7385. 15 5110. 8 0. 692 97. 03 2511. 37 1253. 16 0. 499 100. 24 2007 7407. 73 5215. 59 0. 704 108. 12 2462. 82 1219. 57 0. 495 110. 62 2008 7510. 27 5267. 1 0. 701 106. 30 2482. 43 1271. 63 0. 512 106. 57 2009 7558. 15 5272. 04 0. 698 110. 12 2504. 79 1290. 09 0. 515 103. 68 2010 7619. 58 5282. 36 0. 693 119. 56 2484. 65 1275. 83 0. 513 106. 78 2011 7663. 25 5319. 2 0. 694 126. 20 2462. 71 1254. 13 0. 509 109. 09 2012 7651. 56 5336. 56 0. 697 132. 53 2324. 16 1251. 55 0. 538 119. 99 2013 7683. 63 5360. 77 0. 698 140. 19 2311. 94 1253. 74 0. 542 129. 43 2014 7678. 62 5376. 07 0. 700 152. 41 2274. 00 1266. 81 0. 557 134. 43 2015 7745. 04 5424. 64 0. 700 155. 53 2290. 55 1277. 85 0. 558 140. 14 2016 N i = α 0 + α 1 l i + α 2 d i + ε i 2 N i l i d i GDP 20002011 2012 2012 65 60 2 OLS 2009 2 Hausman 7 Hausman 23

2018 4 0. 016 5% 1 0. 016 5% 1 0. 011 7 FE RE FE RE 0. 016 ** 2. 015 0. 020 *** 2. 805-0. 011 ** -2. 237-0. 003-0. 550 ln_ 0. 032 1. 314 0. 021 0. 859 0. 009 ** 2. 412 0. 008 ** 2. 229 0. 239 1. 159-0. 089-0. 462-0. 227-1. 244-0. 525 ** -2. 378 ln_ 0. 063 * 1. 959 0. 098 *** 3. 099-0. 015-0. 891 0. 004 0. 225 ln_ -0. 077-1. 507-0. 102 ** -2. 136 0. 003 1. 256 0. 002 0. 833 _cons 0. 401 1. 376 0. 617 ** 2. 278 0. 966 *** 7. 580 1. 034 *** 6. 785 156 156 132 132 Hausman Test 34. 79 0. 0000 22. 22 0. 0005 * ** *** 10% 5% 1% 24

1. Li M Sicular T. Aging of the labor force and technical efficiency in crop production Evidence from Liaoning province China. China Agricultural Economic Review 2013 5 3 342~ 359 2... http / /www. stats. gov. cn /tjsj /pcsj / 3... http / /www. stats. gov. cn /tjsj /pcsj / 4... 2009 10 12 ~ 18 110 5... 2011 2 39~ 46 6... 2008 10 20 ~ 20 7... 2013 2 69 ~ 77 8... 2013 2 9... 2010 5 58~ 65 10... 2014 3 53 ~ 65 11... 2012 4 15 ~ 25 12... 2015 29 10 35~ 41 13... 2009 5 52~ 60 14... 2013 9 63~ 77 15... 2017 1 45 ~ 66 16... 2015 6 15~ 21 17... 2013 2 31~ 39 18... 2016 1 78~ 87 19... 2017 1 45 ~ 66 20... 2013 35 4 95~ 103 21... 2013 25 6 1397 ~ 1403 22... 2011 33 9 1691 ~ 1698 23... 2013 34 12 15 ~ 24 24. Holly Wang. 15. 2009 2 22 ~ 33 25

2018 4 The Influence of Rural Labor Force Aging on Agricultural Production An empirical analysis of cultivated land terrain WANG Shangao TIAN Xu Abstract In this paper we identified the direct and indirect effects of rural labor force aging on agricultural production.then using the data of rural farmers' fixed observation points to test the ecological structure of rural laborers under different terrains.provincial macro data of Jiangsu and Zhejiang provinces are then used to carry out a robustness test.the results showed that the impact of rural labor aging on agricultural production significantly differs by terrain.specifically plain areas the elderly households will increase the proportion of grain crops which are suitable for machinery while in hilly areas cash crops are more welcomed.the results also found that with the aging of the rural labor force significant replacement of labor with agricultural machinery can be found in both types of terrains. Keywords Agricultural labor Aging Agricultural production Production structure Agricultural machinery 26