. 
. egen id=group(Province)

. xtset id year

Panel variable: id (strongly balanced)
 Time variable: year, 2013 to 2015
         Delta: 1 unit

. gtfpch K L= Y: CO2, dmu( Province ) global sav(ex3result,replace)

 The directional vector is (0 0 Y -CO2)


 Total Factor Productivity Change:Malmquist-Luenberger Productivity Index
    (Row: Row # in the original data; Pdwise: periodwise)

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

Estimated Results are saved in ex3result.dta.

.