Need Help: Matching Method for Green Bond Data

[Kelly Quigley]

Hi guys,

I am currently writing my dissertation/thesis on the existence of a greenium and I need to conduct a matching method similar to the paper "Zerbib (2019) The effect of pro-environmental preferences on bond prices: Evidence from green bonds". Unfortunately, I am new to Stata and have been offered little support from my supervisor so I was looking for someone to help me figure this out... I need to match one green bond to one non-green bond, with both bonds having the same rating, currency, issuer, coupon type, and similar maturity, issue amount, issue date and bid-ask spread.

I have tried to use psmatch2 for this but no such luck, can anyone recommend how to do this? I have 44 observations for green bonds and 2050 for non-green bonds but have merged both into one data sheet and imported it into stata as each data sheet has the same variable names.

Please help !!

[William Lisowski]

Very often a simple description really isn't clear without more detail, or at a minimum it is too difficult to guess at a good answer from what has been shared. When that happens other members will decide not to answer the question, or ask for an improved presentation that could have been provided to begin with.

So, if nobody leaps to answer this, please help us help you. Show example data. Show your psmatch2 code and show us what Stata told you. Tell us what precisely is wrong. The Statalist FAQ provides advice on effectively posing your questions, posting data, and sharing Stata output.

Without knowing what your data is like, we're left to write an answer abstractly rather than concretely in terms of your actual data. And without knowing how you applied psmatch2 to your data and why it didn't meet your expectations, we have to write an entire tutorial rather than tell you what to change in what you did.

You will find that the time spend preparing a well-formed question will often pay off in a quicker answer that requires less followup. Again, the Statalist FAQ provides advice on how to most effectively make use of the experience and expertise available here.

[Andres Salman]

Kelly Quigley ,
Can you show an example of your data using the dataex command? ( https://www.stata.com/help.cgi?dataex)

Have you tried the cem command (https://gking.harvard.edu/files/cem-stata.pdf)?

[Rens Eggink]

Hi Kelly, I am writing my thesis about the same topic. Could you please consider sharing your do-file with me?

[Jolee Lai]

Hi, I am having the same issue. My premise is the same as the OP's, essentially I would like to match a green bond with a similar conventional non-green bond using the following criteria: same issuer, same bond grade, same seniority, same currency, maturity neither two years longer or shorter than the green counterpart, issue date neither six years earlier or later than green counterpart, issue amount less than four times the green counterpart and greater than one-quarter of the green counterpart.

After the matching process, the unmatched bonds should be dropped. Then, I would use these matched pairs to conduct a regression to find out the effect of the Green label on YTM.

I am a complete newbie so any advice would be much appreciated. Many thanks.

* Example generated by -dataex-. For more info, type help dataex
clear
input str6 ticker byte(bondgrade seniority currency) long maturity int issuedate double amountissued byte greenbond double YTM
"REGEN"  2 3 1 23542 19859  196387500 1  6.463096
["HONDA"  2 3 1 24540 22714  785550000 1  4.742569
"MITBKA" 2 3 1 24540 22714  392775000 1  5.007377
"HONDA"  2 3 1 26367 22714  589162500 1  4.491943
"MFC"    2 3 1 26373 22720  589162500 1  4.708768
"UELMO"  2 2 1 33694 22736  412413750 1  5.066915
"WELLOP" 2 3 1 26464 22735  432052500 1  5.028282
"EQIX"   2 3 1 26403 22740  942660000 1  5.051932
"SHINBC" 2 4 1 26401 22748  392775000 1  5.608014
"FMGXN"  1 3 1 26403 22746  628440000 1  6.220701
"NXPIN"  2 3 1 25688 22784  785550000 1  5.076103
"NXPIN"  2 3 1 26063 22784  785550000 1  5.112294
"JBL"    2 3 1 24606 22769  392775000 1  5.304745
"XELPOW" 2 2 1 33755 22774  392775000 1  4.976797
"SOGEP"  2 3 1 33738 22769  628440000 1  5.160353
"ENNEG"  2 3 1 24608 22782  432052500 1   5.11259
"NXPIN"  2 3 1 26678 22781  785550000 1  5.182307
"SREPRL" 2 2 1 26450 22785  314220000 1  4.721938
"XELSWP" 2 2 1 33755 22796  157110000 1  5.766795
"AMBPAD" 1 2 1 24637 22804  471330000 1  6.283114
"NI"     2 3 1 33769 22806  274942500 1  5.406091
"LGCHE"  2 3 1 23936 22840  235665000 1  5.468886
"PEP"    2 3 1 26497 22844  981937500 1  4.311944
"LENVO"  2 3 1 24863 22853  490968750 1  5.348308
"LENVO"  2 3 1 26506 22853  490968750 1  5.573287
"GM"     2 3 1 25490 22859  785550000 1  5.290898
"GM"     2 3 1 26586 22859  981937500 1  5.425912
"INTC"   2 3 1 26515 22862  981937500 1  4.602878
"LNTWI"  2 3 1 26542 22872  471330000 1  4.791935
"F"      1 3 1 26529 22876 1374712500 1  6.144478
"ELC"    2 2 1 33861 22881  392775000 1  5.323611
"UNP"    2 3 1 33855 22897  471330000 1  4.841964
"HPPBD"  2 3 1 24882 22903  274942500 1   9.59325
"NGNMP"  2 3 1 33862 22904  392775000 1  5.491614
"PLDPR"  2 3 1 26678 22908  510607500 1    4.7103
"EDPPF"  2 3 1 24755 22929  392775000 1  4.925345
"BXPPI"  2 3 1 24806 22966  589162500 1  5.498002
"SOCGP"  2 2 1 33922 22963  471330000 1  5.330642
"YAR"    2 3 1 26616 22963  471330000 1  5.871942
"AILLP"  2 2 1 33938 22971  274942500 1  5.057787
"TA"     1 3 1 25521 22966  314220000 1  6.632219
"PPWLO"  2 2 1 34303 22980  864105000 1  5.660352
"SREPRL" 2 2 1 26450 23030  313175219 1   4.71667
"HXSCF"  2 3 1 26680 23027  589162500 1  5.761932
"ARE"    2 3 1 27498 23057  392775000 1  5.146352
"CMCSA"  2 3 1 26709 23050  785550000 1  4.705542
"EMN"    2 3 1 26730 23077  392775000 1  5.328899
"APD"    2 3 1 26725 23072  471330000 1  4.429043
"MITBKA" 2 3 1 24905 23078  392775000 1  5.109339
"CNPGYH" 2 2 1 34059 23092  235665000 1    4.9578
"LNTWI"  2 3 1 26754 23099  235665000 1  4.948254
"BXPPI"  2 3 1 27043 23145  589162500 1  5.896811
"LYNLF"  2 3 1 26798 23149  392775000 1  5.078998
"HYMTRN" 2 3 1 23918 23187  589162500 1   5.52522
"KEPCOH" 2 3 1 25036 23209  392775000 1  4.822592
"HANCHN" 2 3 1 25045 23218  314220000 1  4.898962
"AGRNW"  2 3 1 25064 23230  274942500 1  5.123682
"AGRNW"  2 3 1 26890 23230  314220000 1  5.287502
"SREDA"  2 2 1 25064 23233  471330000 1  4.583697
"SUZBSZ" 2 3 1 24488 23258  549885000 1  5.378913
"BRKMFC" 2 2 1 27043 23260  274942500 1  4.746813
"BRKMFC" 2 2 1 34591 23260  785550000 1  5.166355
"MAERS"  2 3 1 26920 23267  589162500 1  5.433688
"LGCHEN" 2 3 1 24374 23278  314220000 1  5.338899
"LGCHEN" 2 3 1 25105 23278  471330000 1   5.11258
"SNNVA"  1 3 1 25111 23279  314220000 1 15.616612
"SQM"    2 3 1 26974 23321  589162500 1  5.858649
"TD"     2 3 1 24451 23355  392775000 1  4.753922
"HASIH"  2 3 1 24637 23351  432052500 1  6.850954
"GS"     2 3 1 23365 22817   19638750 0  6.466516
"DBKGUK" 2 3 1 23365 21174     785550 0  6.728664
"GS"     2 3 1 23365 22270    4336236 0  6.480203
"CSGNLN" 2 3 1 23365 22909   10444673 0  7.448418
"EQNR"   2 3 1 23365 16470   78555000 0  6.087228
"JPM"    2 3 1 23366 22271   40451897 0  5.830638
"CM"     2 3 1 23373 22978    2356650 0  6.247167
"RY"     2 3 1 23373 22979   50775595 0  6.105486
"CM"     2 3 1 23373 22825    3927750 0  6.245628
"RY"     2 3 1 23373 23008   18670167 0  6.106287
"BMO"    2 3 1 23373 22826    3927750 0  6.429461
"BNS"    2 3 1 23374 22918   12884591 0  6.141958
"CSGNLN" 2 3 1 23374 22826    9831944 0  6.632762
"TD"     2 3 1 23375 22826    1571100 0  5.944876
"TD"     2 3 1 23375 22978   26708700 0  5.943636
"GS"     2 3 1 23381 22832    3927750 0  7.326636
"ATHFU"  2 2 1 23383 22288  589162500 0  6.662074
"GS"     2 3 1 23383 22832   47133000 0  6.712574
"HYMTRN" 2 3 1 23383 22288  942660000 0  6.193676
"FMCRT"  1 3 1 23384 20828  589162500 0  6.203373
"CATTP"  2 3 1 23385 22655  942660000 0  6.402507
"DEJCP"  2 3 1 23385 22655  392775000 0  5.693782
"SUMFGI" 2 3 1 23385 19733  392775000 0  5.593787
"DEJCP"  2 3 1 23385 21559  314220000 0  5.822767
"ISP"    2 3 1 23387 19737  785550000 0  6.195409
"HONDFA" 2 3 1 23387 21564  549885000 0   6.04263
"ISP"    2 3 1 23387 19737  785550000 0  6.195409
"ET"     2 3 1 23390 21633  885695056 0  5.702716
"CNHIH"  2 3 1 23390 21410  392775000 0  6.434981
"EQNR"   2 3 1 23390 19493  706995000 0  5.732657
"NBRIN"  1 3 1 23390 20832  451691250 0 72.728345
"AVGOBO" 2 3 1 23390 21229 1963843578 0  9.573296
"PSEC"   2 3 1 23390 22294     166537 0  7.855462
"NESNHO" 2 3 1 23390 22173  903382500 0  6.093237
"AVGOBO" 2 3 1 23390 20838 1963875000 0  9.573699
"TAMOJL" 1 3 2 23390 20836  557687476 0  7.105708
"AMT"    2 3 1 23390 22239  392775000 0  6.218595
"METMT"  2 4 1 23390 21301   84053850 0  7.483658
"KIMREK" 2 3 1 23390 19646  196387500 0  8.432565
"ALLY"   2 3 1 23390 22294     244306 0  7.822364
"GE"     2 3 1 23390 18647    7561704 0  7.394429
"NBRIN"  1 3 1 23390 20832  451691250 0 72.728345
"PSEC"   2 3 1 23390 21458   78555000 0   8.60428
"FRTFE"  2 3 1 23390 19701  471330000 0  6.683237
"EMN"    2 3 1 23390 12436  392775000 0  7.113917
"TTETL"  2 3 1 23390 19582  785550000 0  6.423067
"WELLOP" 2 3 1 23390 19638  314220000 0  6.482664
"PSEC"   2 3 1 23390 22302     353498 0  7.855462
"CPT"    2 3 1 23390 19694  196387500 0  6.313364
"WFC"    2 4 1 23391 19688  567979359 0  6.752279
"WBC"    2 2 1 23391 21565 1.5711e+09 0  5.793851
"VOD"    2 3 1 23391 21334 1.5711e+09 0  5.813293
"WFC"    2 4 1 23391 19758  567625861 0  6.752802
"RY"     2 3 1 23391 22993   39468389 0  6.105073
end
format %tdnn/dd/CCYY maturity
format %tdnn/dd/CCYY issuedate
label values bondgrade BondGrade
label def BondGrade 1 "High Yield", modify
label def BondGrade 2 "Investment Grade", modify
label values seniority Seniority
label def Seniority 1 "Senior Preferred", modify
label def Seniority 2 "Senior Secured", modify
label def Seniority 3 "Senior Unsecured", modify
label def Seniority 4 "Subordinated Unsecured", modify
label values currency Currency
label def Currency 1 "USD", modify
label def Currency 2 "EUR", modify
label def Currency 3 "GBP", modify
label values greenbond Green
label def Green 0 "No", modify
label def Green 1 "Yes", modify