Create variable that calculates difference in matched observation and "normal observation" of a variable

[Cristina Demmers]

Hi all,

For my thesis I need to extract the difference in Issue Yield between green bonds and conventional bonds. First, I have identified matches (based on different characteristics and Mahalonobis Distance) using mahapick:

mahapick Maturity Coupon AmountIssuedUSD, idvar(id) treated(GreenBond) genfile(MatchedGreenBonds) prime_id(prime_id_var) matchnum(matchnum_var) nummatches(1) full matchon(BondGrade)

I am stuck however on how to create a new variable that indicates the difference in Issue Yields between the green bond and the matched conventional bond, can anyone help me?

Thank you very much!

[Andrew Musau]

Present a data example using dataex, clearly identifying what is a green bond, what is a conventional bond and what variable represents the match id. See

help dataex

[Cristina Demmers]

Sorry for my late response, I did not see your reply. I must say I am quite new with stata and have been trying to figure it out over the course of the last two weeks, so sorry if I did not understand your question correctly.
Below you can find a data example, the variable GreenBond is a dummy, where 1=Green Bond and 0= conventional bond. The dataex only shows green bonds.

Through the command mahapick I have been able to match green bonds with a similar conventional bond. This resulted in a dataset I will also show below. Now, I want to find the difference in YTM between the green bond and matched conventional bond, but I do not know how to create this extra variable. Essentially, I want to augment the green bond dataset with a variable that shows YTM matched conventional bond - YTM green bond.

input float id byte GreenBond double YTM int IssueDate long Maturity double(Coupon AmountIssuedUSD)
108 1 15.25 20080 93 15.25 281
141 1 8 19386 94 8 443
437 1 13.77 19374 96 13.77 276
465 1 19.62 22027 96 19.62 200
511 1 7 20633 97 7 300
542 1 9 20017 97 9 1000
656 1 13.7 22047 97 13.7 685
685 1 15.68 22049 97 15.68 315
743 1 5.6 20016 98 5.6 1000
746 1 6.45 20016 98 6.45 400
757 1 9.36 20152 98 9.36 200
782 1 9.76 20174 102 9.76 1000
785 1 11.89 22117 104 11.89 500
975 1 16.37 22021 158 16.37 100
986 1 5.19 20185 164 5.19 1391
987 1 7.18 20185 164 7.18 1001
997 1 9.58 20369 174 9.58 1000
1072 1 7 19415 183 7 153
1076 1 8.25 19387 183 8.25 190
1078 1 8.75 19374 183 8.75 599
1163 1 7.5 19402 184 7.5 132
1187 1 9.82 19387 184 9.82 600
1196 1 10.29 20359 184 10.29 1300
1414 1 7.75 21084 186 7.75 100
1426 1 8.5 19568 186 8.5 380
1434 1 9 19375 186 9 325
1484 1 12.09 21983 186 12.09 1000
1725 1 3.25 20192 188 3.25 100
1727 1 3.65 20972 188 3.65 100
1728 1 3.75 19380 188 3.75 29874
1771 1 8.75 19522 188 8.75 130
1810 1 10 19535 188 10 125
1817 1 10.25 19472 188 10.25 1013
1862 1 12.57 22068 188 12.57 100
1896 1 18.28 22084 188 18.28 100
1905 1 20.57 22007 188 20.57 250
1911 1 22.83 22006 188 22.83 250
2013 1 6.37 22062 189 6.37 100
2029 1 7.2 20629 189 7.2 100
2122 1 11.5 19555 189 11.5 75
2143 1 13.96 22054 189 13.96 100
2180 1 22.55 21997 189 22.55 250
2258 1 7.53 21979 190 7.53 1000
2265 1 8.94 21978 190 8.94 500
2447 1 7.4 19751 195 7.4 500
2534 1 10.56 20353 203 10.56 1100
2551 1 14.19 21986 207 14.19 355
2583 1 9.21 20377 217 9.21 1100
2643 1 6.11 20236 242 6.11 600
2826 1 5.51 21516 279 5.51 610
2875 1 4.77 21783 280 4.77 675
2884 1 9.07 21978 280 9.07 500
3084 1 9.18 19730 322 9.18 16049
3439 1 7.25 19415 366 7.25 1000
3456 1 8.5 19374 366 8.5 120
3465 1 9 19387 366 9 90
3726 1 6.75 19443 367 6.75 140
3754 1 7.5 19442 367 7.5 185
3764 1 7.75 19555 367 7.75 163
3769 1 8 19415 367 8 98
3777 1 8.2 20086 367 8.2 3469
3788 1 9 19555 367 9 63
3802 1 9.5 19415 367 9.5 115
3947 1 4.27 19834 368 4.27 100
3952 1 4.7 20541 368 4.7 625
3954 1 4.78 19386 368 4.78 150
3976 1 6.02 20527 368 6.02 135
3986 1 6.32 21493 368 6.32 110
3987 1 6.35 19953 368 6.35 1400
3991 1 6.5 20681 368 6.5 572
4040 1 7.8 19372 368 7.8 100
4050 1 7.97 19372 368 7.97 139
4052 1 7.99 22158 368 7.99 100
4077 1 8.3 19722 368 8.3 1865
4087 1 8.5 19474 368 8.5 327
4089 1 8.5 19974 368 8.5 1277
4152 1 10.06 22018 368 10.06 300
4200 1 12.48 22025 368 12.48 300
4361 1 3.99 20145 369 3.99 150
4371 1 5.8 19992 369 5.8 87
4374 1 6.05 20935 369 6.05 2644
4380 1 6.59 19423 369 6.59 100
4382 1 6.6 20762 369 6.6 1199
4419 1 8.15 19472 369 8.15 950
4428 1 8.5 19460 369 8.5 149
4465 1 11 19368 369 11 488
4471 1 11 22090 369 11 5000
4472 1 11.3 22120 369 11.3 5000
4713 1 4.66 19662 370 4.66 170
4716 1 4.71 19955 370 4.71 125
4719 1 4.78 20188 370 4.78 259
4744 1 5.07 19614 370 5.07 200
4749 1 5.15 19744 370 5.15 100
4757 1 5.22 19381 370 5.22 810
4760 1 5.22 19800 370 5.22 350
4771 1 5.33 19534 370 5.33 115
4793 1 5.6 20115 370 5.6 400
4794 1 5.6 20115 370 5.6 190
4817 1 5.87 19494 370 5.87 100
4822 1 6 20111 370 6 5617

Dataset with matched bonds:
input float prime_id_var int matchnum_var float id
108 0 108
108 1 1647
141 0 141
141 1 1074
437 0 437
437 1 55
465 0 465
465 1 1902
511 0 511
511 1 61603
542 0 542
542 1 749
656 0 656
656 1 9489
685 0 685
685 1 686
743 0 743
743 1 64632
746 0 746
746 1 4886
757 0 757
757 1 8078
782 0 782
782 1 7860
785 0 785
785 1 62522
975 0 975
975 1 6238
986 0 986
986 1 64595
987 0 987
987 1 6623
997 0 997
997 1 8444
1072 0 1072
1072 1 1558
1076 0 1076
1076 1 5352
1078 0 1078
1078 1 1080
1163 0 1163
1163 1 5126
1187 0 1187
1187 1 1605
1196 0 1196
1196 1 7218
1414 0 1414
1414 1 10406
1426 0 1426
1426 1 523
1434 0 1434
1434 1 276
1484 0 1484
1484 1 6108
1725 0 1725
1725 1 64259
1727 0 1727
1727 1 64178
1728 0 1728
1728 1 64759
1771 0 1771
1771 1 1772
1810 0 1810
1810 1 406
1817 0 1817
1817 1 5899
1862 0 1862
1862 1 6138
1896 0 1896
1896 1 6258
1905 0 1905
1905 1 61476
1911 0 1911
1911 1 61477
2013 0 2013
2013 1 70639
2029 0 2029
2029 1 64376
2122 0 2122
2122 1 2123
2143 0 2143
2143 1 2280
2180 0 2180
2180 1 263
2258 0 2258
2258 1 8945
2265 0 2265
2265 1 2056
2447 0 2447
2447 1 5101
2534 0 2534
2534 1 8667
2551 0 2551
2551 1 6182
2583 0 2583
2583 1 4443
2643 0 2643
2643 1 10916
2826 0 2826
2826 1 68006

Thank you for your help!