我有一个面板数据集(标识符是cc
和year
的变量)。
我有Y
变量的所有值,但我只有X_{1996}
变量的初始值(X
)。
我想用这种模式替换X
的缺失值:
X_{1997} = Y_{1996} + 0.95*X_{1996}
X_{1998} = Y_{1997} + 0.95*X_{1997}
.
.
.
X_{2015} = Y_{2014} + 0.95*X_{2014}
我想从X
开始迭代地替换1997
,即使用最后生成的值。
是否可以为此目的编写循环?
示例数据:
clear
input str3 cc year X Y
"ABW" 1996 467.5953 28.46004
"ABW" 1997 . 30.23142
"ABW" 1998 . 31.70577
"ABW" 1999 . 30.870903
"ABW" 2000 . 25.495903
"ABW" 2001 . 23.71254
"ABW" 2002 . 26.906475
"ABW" 2003 . 29.215036
"ABW" 2004 . 28.77914
"ABW" 2005 . 33.581017
"ABW" 2006 . 35.16129
"ABW" 2007 . 32.51442
"ABW" 2008 . 33.251934
"ABW" 2009 . 30.29287
"ABW" 2010 . 28.931993
"ABW" 2011 . 28.5057
"ABW" 2012 . 26.647564
"ABW" 2013 . 23.999134
"ABW" 2014 . 22.917984
"ABW" 2015 . 21.481943
"AFG" 1996 362.353 11.51442
"AFG" 1997 . 11.557285
"AFG" 1998 . 12.19376
"AFG" 1999 . 14.557285
"AFG" 2000 . 12.906254
"AFG" 2001 . 13.156855
"AFG" 2002 . 11.557285
"AFG" 2003 . 15.758896
"AFG" 2004 . 19.005346
"AFG" 2005 . 23.193766
"AFG" 2006 . 26.407976
"AFG" 2007 . 20.068926
"AFG" 2008 . 19.021326
"AFG" 2009 . 17.991436
"AFG" 2010 . 17.959072
"AFG" 2011 . 16.674591
"AFG" 2012 . 16.906254
"AFG" 2013 . 17.343513
"AFG" 2014 . 18.156855
"AFG" 2015 . 19.454687
如果要通过使用上次生成的观察计算X
的缺失值,则可以按如下方式进行:
bysort cc (year): replace X = Y[_n-1] + 0.95 * X[_n-1] if _n > 1
list, sepby(cc)
+----------------------------------+
| cc year X Y |
|----------------------------------|
1. | ABW 1996 467.5953 28.46004 |
2. | ABW 1997 472.6756 30.23142 |
3. | ABW 1998 479.2732 31.70577 |
4. | ABW 1999 487.0153 30.8709 |
5. | ABW 2000 493.5355 25.4959 |
6. | ABW 2001 494.3546 23.71254 |
7. | ABW 2002 493.3494 26.90648 |
8. | ABW 2003 495.5884 29.21504 |
9. | ABW 2004 500.024 28.77914 |
10. | ABW 2005 503.802 33.58102 |
11. | ABW 2006 512.1929 35.16129 |
12. | ABW 2007 521.7445 32.51442 |
13. | ABW 2008 528.1717 33.25193 |
14. | ABW 2009 535.015 30.29287 |
15. | ABW 2010 538.5571 28.93199 |
16. | ABW 2011 540.5613 28.5057 |
17. | ABW 2012 542.0389 26.64756 |
18. | ABW 2013 541.5845 23.99913 |
19. | ABW 2014 538.5045 22.91798 |
20. | ABW 2015 534.4972 21.48194 |
|----------------------------------|
21. | AFG 1996 362.353 11.51442 |
22. | AFG 1997 355.7498 11.55729 |
23. | AFG 1998 349.5196 12.19376 |
24. | AFG 1999 344.2373 14.55729 |
25. | AFG 2000 341.5828 12.90625 |
26. | AFG 2001 337.4099 13.15685 |
27. | AFG 2002 333.6962 11.55729 |
28. | AFG 2003 328.5687 15.7589 |
29. | AFG 2004 327.8992 19.00535 |
30. | AFG 2005 330.5096 23.19377 |
31. | AFG 2006 337.1778 26.40798 |
32. | AFG 2007 346.7269 20.06893 |
33. | AFG 2008 349.4595 19.02133 |
34. | AFG 2009 351.0078 17.99144 |
35. | AFG 2010 351.4489 17.95907 |
36. | AFG 2011 351.8355 16.67459 |
37. | AFG 2012 350.9183 16.90625 |
38. | AFG 2013 350.2787 17.34351 |
39. | AFG 2014 350.1082 18.15685 |
40. | AFG 2015 350.7597 19.45469 |
+----------------------------------+