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{com}.
. egen id=group(Province)
{txt}
{com}. xtset id year
{res}
{col 1}{txt:Panel variable: }{res:id}{txt: (strongly balanced)}
{p 1 16 2}{txt:Time variable: }{res:year}{txt:, }{res:{bind:2013}}{txt: to }{res:{bind:2015}}{p_end}
{txt}{col 10}Delta: {res}1 unit
{txt}
{com}. gtfpch K L= Y: CO2, dmu( Province ) global sav(ex3result,replace)
{res}
The directional vector is (0 0 Y -CO2)
Total Factor Productivity Change:Malmquist-Luenberger Productivity Index
(Row: Row # in the original data; Pdwise: periodwise)
{txt}
{c TLC}{hline 5}{c -}{hline 14}{c -}{hline 4}{c -}{hline 11}{c -}{hline 8}{c -}{hline 8}{c -}{hline 8}{c TRC}
{c |} {res}Row Province id Pdwise TFPCH TECH TECCH {txt}{c |}
{c LT}{hline 5}{c -}{hline 14}{c -}{hline 4}{c -}{hline 11}{c -}{hline 8}{c -}{hline 8}{c -}{hline 8}{c RT}
1. {c |} {res} 2 Anhui 1 2013~2014 0.9943 0.9662 1.0290 {txt}{c |}
2. {c |} {res} 3 Anhui 1 2014~2015 0.9951 0.9645 1.0317 {txt}{c |}
3. {c |} {res} 5 Beijing 2 2013~2014 1.0328 1.0000 1.0328 {txt}{c |}
4. {c |} {res} 6 Beijing 2 2014~2015 1.0583 1.0000 1.0583 {txt}{c |}
5. {c |} {res} 8 Chongqing 3 2013~2014 1.0013 0.9883 1.0132 {txt}{c |}
6. {c |} {res} 9 Chongqing 3 2014~2015 1.0222 0.9659 1.0582 {txt}{c |}
7. {c |} {res} 11 Fujian 4 2013~2014 0.9813 0.9438 1.0397 {txt}{c |}
8. {c |} {res} 12 Fujian 4 2014~2015 1.0207 0.9774 1.0443 {txt}{c |}
9. {c |} {res} 14 Gansu 5 2013~2014 0.9942 0.9748 1.0200 {txt}{c |}
10. {c |} {res} 15 Gansu 5 2014~2015 0.9958 0.9725 1.0240 {txt}{c |}
11. {c |} {res} 17 Guangdong 6 2013~2014 1.0185 0.9575 1.0637 {txt}{c |}
12. {c |} {res} 18 Guangdong 6 2014~2015 1.0152 0.9841 1.0316 {txt}{c |}
13. {c |} {res} 20 Guangxi 7 2013~2014 1.0031 0.9856 1.0177 {txt}{c |}
14. {c |} {res} 21 Guangxi 7 2014~2015 1.0317 0.9830 1.0495 {txt}{c |}
15. {c |} {res} 23 Guizhou 8 2013~2014 1.0014 0.9889 1.0127 {txt}{c |}
16. {c |} {res} 24 Guizhou 8 2014~2015 1.0080 0.9879 1.0204 {txt}{c |}
17. {c |} {res} 26 Hainan 9 2013~2014 0.9729 0.9497 1.0244 {txt}{c |}
18. {c |} {res} 27 Hainan 9 2014~2015 0.9773 0.9321 1.0485 {txt}{c |}
19. {c |} {res} 29 Hebei 10 2013~2014 1.0052 0.9796 1.0261 {txt}{c |}
20. {c |} {res} 30 Hebei 10 2014~2015 1.0002 0.9784 1.0223 {txt}{c |}
21. {c |} {res} 32 Heilongjiang 11 2013~2014 1.0007 0.9546 1.0482 {txt}{c |}
22. {c |} {res} 33 Heilongjiang 11 2014~2015 1.0071 0.9854 1.0220 {txt}{c |}
23. {c |} {res} 35 Henan 12 2013~2014 0.9955 0.9689 1.0274 {txt}{c |}
24. {c |} {res} 36 Henan 12 2014~2015 0.9963 0.9632 1.0343 {txt}{c |}
25. {c |} {res} 38 Hubei 13 2013~2014 1.0019 0.9618 1.0418 {txt}{c |}
26. {c |} {res} 39 Hubei 13 2014~2015 1.0015 0.9656 1.0372 {txt}{c |}
27. {c |} {res} 41 Hunan 14 2013~2014 1.0090 0.9714 1.0388 {txt}{c |}
28. {c |} {res} 42 Hunan 14 2014~2015 0.9820 0.9453 1.0388 {txt}{c |}
29. {c |} {res} 44 Jiangsu 15 2013~2014 1.0275 0.9894 1.0385 {txt}{c |}
30. {c |} {res} 45 Jiangsu 15 2014~2015 1.0390 0.9975 1.0417 {txt}{c |}
31. {c |} {res} 47 Jiangxi 16 2013~2014 0.9932 0.9731 1.0206 {txt}{c |}
32. {c |} {res} 48 Jiangxi 16 2014~2015 0.9970 0.9515 1.0478 {txt}{c |}
33. {c |} {res} 50 Jilin 17 2013~2014 1.0064 0.9858 1.0209 {txt}{c |}
34. {c |} {res} 51 Jilin 17 2014~2015 1.0312 0.9922 1.0393 {txt}{c |}
35. {c |} {res} 53 Liaoning 18 2013~2014 1.0179 0.9712 1.0481 {txt}{c |}
36. {c |} {res} 54 Liaoning 18 2014~2015 1.0289 0.9997 1.0292 {txt}{c |}
37. {c |} {res} 56 Neimenggu 19 2013~2014 1.0074 0.9830 1.0249 {txt}{c |}
38. {c |} {res} 57 Neimenggu 19 2014~2015 1.0157 1.0019 1.0138 {txt}{c |}
39. {c |} {res} 59 Ningxia 20 2013~2014 1.0024 0.9966 1.0058 {txt}{c |}
40. {c |} {res} 60 Ningxia 20 2014~2015 1.0021 0.9914 1.0108 {txt}{c |}
41. {c |} {res} 62 Qinghai 21 2013~2014 1.0127 0.9928 1.0200 {txt}{c |}
42. {c |} {res} 63 Qinghai 21 2014~2015 1.0038 0.9657 1.0395 {txt}{c |}
43. {c |} {res} 65 Shaanxi 22 2013~2014 0.9983 0.9908 1.0076 {txt}{c |}
44. {c |} {res} 66 Shaanxi 22 2014~2015 1.0120 0.9772 1.0357 {txt}{c |}
45. {c |} {res} 68 Shandong 23 2013~2014 1.0032 0.9588 1.0463 {txt}{c |}
46. {c |} {res} 69 Shandong 23 2014~2015 0.9919 0.9685 1.0241 {txt}{c |}
47. {c |} {res} 71 Shanghai 24 2013~2014 0.9955 1.0000 0.9955 {txt}{c |}
48. {c |} {res} 72 Shanghai 24 2014~2015 1.0152 1.0000 1.0152 {txt}{c |}
49. {c |} {res} 74 Shanxi 25 2013~2014 0.9932 0.9788 1.0147 {txt}{c |}
50. {c |} {res} 75 Shanxi 25 2014~2015 0.9967 0.9855 1.0114 {txt}{c |}
51. {c |} {res} 77 Sichuan 26 2013~2014 1.0027 0.9699 1.0338 {txt}{c |}
52. {c |} {res} 78 Sichuan 26 2014~2015 1.0187 0.9774 1.0423 {txt}{c |}
53. {c |} {res} 80 Tianjin 27 2013~2014 1.0686 1.0000 1.0686 {txt}{c |}
54. {c |} {res} 81 Tianjin 27 2014~2015 1.0697 0.9701 1.1027 {txt}{c |}
55. {c |} {res} 83 Xinjiang 28 2013~2014 0.9897 0.9746 1.0154 {txt}{c |}
56. {c |} {res} 84 Xinjiang 28 2014~2015 0.9881 0.9727 1.0159 {txt}{c |}
57. {c |} {res} 86 Yunnan 29 2013~2014 1.0161 0.9889 1.0275 {txt}{c |}
58. {c |} {res} 87 Yunnan 29 2014~2015 1.0155 0.9849 1.0310 {txt}{c |}
59. {c |} {res} 89 Zhejiang 30 2013~2014 1.0143 0.9677 1.0481 {txt}{c |}
60. {c |} {res} 90 Zhejiang 30 2014~2015 1.0028 0.9695 1.0343 {txt}{c |}
{c BLC}{hline 5}{c -}{hline 14}{c -}{hline 4}{c -}{hline 11}{c -}{hline 8}{c -}{hline 8}{c -}{hline 8}{c BRC}
Note: missing value indicates infeasible problem.
{p 0 4 2}
(file {bf}
ex3result.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
ex3result.dta{rm}
saved
{p_end}
Estimated Results are saved in ex3result.dta.
{com}.
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