I know that there are a lot of topics on this matter, but unfortunately I cant figure out how to do it in my particular case. This is my last resort, I really hope somebody can help me out.
I have a dataset of 105 firms that issued a green bond, the treated firms. Furthermore, I constructed a dataset of firms which did not issue a green bond, but which are in the same country and same industry, the control firms( I did this manually, so for each treated firm I gathered every firm which is in the same country & industry).
Now I want to match these 105 treated firms to the nearest neighbor in this control firm dataset, and drop the treated firms of which I cant find a match. For this I want to use several variables:
treated and control must be in same country and industry, and be the nearest neighbor based on: ESG score, environmental pillar score, env innovation score, total assets, net income, market value, total debt and Return on Assets.
Now I read a lot about psmatch2, teffects nnmatch, teffects psmatch and joinby/joinrange, but I still cant figure it out. My problem is with identifiying the matches, I want to know specifically which treated firm is matched with which control firm, to do further analysis on these pairs.
My initial dataset from excel is in wide format, thus variables are arranged as follows: ESG2012 ESG 2013 ESG2014.... But I guess I need it in long format thus;
ID ESG
2012 ... ...
2013 ... ...
2014 ... ...
I used the following code so far:
Code:
clear all cd "..." sysdir set PLUS "...." import excel "....." qui destring ESGscore* envpillarscore* envinnovation* CO2* totalassets* netincome* Marketvalue* totaldebt* ROA*, force replace gen ID= _n order ID, first save temp_fileALL.dta, replace use temp_fileALL.dta, clear reshape long ESGscore envpillarscore envinnovation CO2 totalassets netincome Marketvalue totaldebt ROA, i(ID) j(year) drop in 329/672 logit treated IndustryCode countrycode predict pscore teffects psmatch (pscore) (treated ESGscore envpillarscore envinnovation CO2 totalassets netincome Marketvalue totaldebt ROA), osample(Unobserved) vce(robust) drop if Unobserved == 1 teffects psmatch (pscore) (treated ESGscore envpillarscore envinnovation CO2 totalassets netincome Marketvalue totaldebt ROA), vce(robust) gen(match) atet nn(1)
the problem with the last row is that I get matches, but they are not in the same country/industry, so not correct.
Does somebody has a solution/ better idea how to solve for this? I will be forever thankful.
Here a small sample of my dataset of both the control and treated combined:
I have also separate datasets of the treated and control firms, in the case that is more easy.
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float ID int year byte treated int(issuedate matchyear) byte(countrycode IndustryCode) double(ESGscore totalassets ROA) 1 2012 0 . . 1 27 66.2457824760244 4.1758e+10 .5911 1 2013 0 . . 1 27 62.9380001633186 4.25283e+10 .7055 1 2014 0 . . 1 27 61.4641120634756 4.6905e+10 .7876 1 2015 0 . . 1 27 67.4532742537313 4.8018e+10 .83656 1 2016 0 . . 1 27 66.8599233529028 5.0853e+10 .7486 1 2017 0 . . 1 27 67.9544809247538 5.1658e+10 .7957 1 2018 0 . . 1 27 68.622678475577 5.298e+10 .73638 1 2019 0 . . 1 27 65.8091548459849 . . 2 2012 0 . . 1 27 67.6176384045335 5.72378e+10 .60256 2 2013 0 . . 1 27 76.3366252245631 6.02725e+10 .6244 2 2014 0 . . 1 27 75.4096938951136 6.50629e+10 .6644 2 2015 0 . . 1 27 73.7283675373134 6.60288e+10 .67444 2 2016 0 . . 1 27 75.7162997390737 6.85727e+10 .64889 2 2017 0 . . 1 27 76.7183939873417 7.14155e+10 .70089 2 2018 0 . . 1 27 76.3741814278046 7.14398e+10 .64675 2 2019 0 . . 1 27 73.9373118088116 . . 3 2012 0 . . 21 27 70.9345094086021 2.449591e+12 .57636 3 2013 0 . . 21 27 66.0918692317691 2.383951e+12 .59542 3 2014 0 . . 21 27 68.1731720725673 2.484721e+12 .58689 3 2015 0 . . 21 27 62.2513681592039 2.816676e+12 .54409 3 2016 0 . . 21 27 65.2514313312258 2.522133e+12 .6347 3 2017 0 . . 21 27 73.5190324419568 2.62758e+12 .60322 3 2018 0 . . 21 27 69.8513486312399 2.766977e+12 .61433 3 2019 0 . . 21 27 74.7859366447728 . . 4 2012 0 . . 21 27 77.8569220430107 7.01131e+11 .42839 4 2013 0 . . 21 27 76.6504127128558 6.68178e+11 .49477 4 2014 0 . . 21 27 72.3085486531061 6.30434e+11 .531 4 2015 0 . . 21 27 73.9584577114427 6.69342e+11 .56946 4 2016 0 . . 21 27 81.4865823674042 6.46868e+11 .51708 4 2017 0 . . 21 27 82.8377772595356 6.15659e+11 .51911 4 2018 0 . . 21 27 79.4671900161031 5.81612e+11 .574 4 2019 0 . . 21 27 79.4671900161031 . . 5 2012 0 . . 21 27 72.8064180107526 1.857065e+12 .7325 5 2013 0 . . 21 27 77.3264493695567 1.84686e+12 .79046 5 2014 0 . . 21 27 76.1074308227964 1.824102e+12 .89767 5 2015 0 . . 21 27 79.5152294085129 2.121297e+12 .75654 5 2016 0 . . 21 27 79.6658236740428 2.148855e+12 .84533 5 2017 0 . . 21 27 83.2784579705638 2.154203e+12 .8593 5 2018 0 . . 21 27 84.3029388083735 2.212636e+12 .9338 5 2019 0 . . 21 27 79.7103345648604 . . 6 2012 0 . . 22 27 33.8208280416561 1594613438000 .5575 6 2013 0 . . 22 27 41.3013908240445 1613823532000 .55867 6 2014 0 . . 22 27 41.3013908240445 1700055541000 .641 6 2015 0 . . 22 27 39.1983644859813 1815872967000 .63733 6 2016 0 . . 22 27 55.1990507089641 1906257219000 .682 6 2017 0 . . 22 27 55.1990507089641 2005151504000 .6235 6 2018 0 . . 22 27 59.6559716921119 2.0362584e+12 .59 6 2019 0 . . 22 27 64.9517876817647 . . 7 2012 0 . . 22 27 41.3559869685964 333947379000 . 7 2013 0 . . 22 27 37.755397510795 521698790000 1.51 7 2014 0 . . 22 27 39.5017291998407 647943022000 3.255 7 2015 0 . . 22 27 61.4538965477953 919701218000 1.3065 7 2016 0 . . 22 27 75.4347426786143 866719175000 .7 7 2017 0 . . 22 27 63.5285861959287 892197509000 . 7 2018 0 . . 22 27 63.5285861959287 2392524390000 . 7 2019 0 . . 22 27 73.4050797283062 . . 8 2012 0 . . 22 27 35.6617442854091 1979259175000 .446 8 2013 0 . . 22 27 37.1076209195859 2062013289000 .48667 8 2014 0 . . 22 27 35.7937395159357 2164729432000 .57 8 2015 0 . . 22 27 35.7937395159357 2259951646000 .639 8 2016 0 . . 22 27 38.4938931297709 2350288574000 .6205 8 2017 0 . . 22 27 65.2002889100933 2545941962000 .50667 8 2018 0 . . 22 27 64.9154649909798 2573419750000 .636 8 2019 0 . . 22 27 64.9154649909798 . . 9 2012 0 . . 22 27 34.7293878587757 2087837113000 .50462 9 2013 0 . . 22 27 49.7325213972929 2124278888000 .58133 9 2014 0 . . 22 27 41.614312245387 2263385352000 .58491 9 2015 0 . . 22 27 59.7961091489119 2355708683000 .65433 9 2016 0 . . 22 27 65.324368283723 2500095812000 .6944 9 2017 0 . . 22 27 65.324368283723 2541156335000 .6376 9 2018 0 . . 22 27 69.4354259435962 2634058605000 .7015 9 2019 0 . . 22 27 76.1333436247623 . . 10 2012 0 . . 22 27 40.682626575518 2629122262000 .60409 10 2013 0 . . 22 27 34.2325120650241 2727365846000 1.79688 10 2014 0 . . 22 27 56.4053019410496 2870986686000 .626 10 2015 0 . . 22 27 56.7156374615472 1382953378000 .9968 10 2016 0 . . 22 27 73.7465238438562 1520230642000 .8734 10 2017 0 . . 22 27 71.0063049989397 1576985727000 .8114 10 2018 0 . . 22 27 74.3978696741854 1677520316000 .8298 10 2019 0 . . 22 27 74.3978696741854 . . 11 2012 0 . . 22 27 69.3539624079248 2025068494000 .88108 11 2013 0 . . 22 27 65.5116689888535 2113515574000 .94967 11 2014 0 . . 22 27 68.8810148574167 2424720079000 1.39575 11 2015 0 . . 22 27 68.8810148574167 3654680064000 .93727 11 2016 0 . . 22 27 73.5106471459496 4596226754000 .68257 11 2017 0 . . 22 27 76.0836852404985 4839251254000 .70283 11 2018 0 . . 22 27 76.2589505163875 5340733544000 .74263 11 2019 0 . . 22 27 76.2589505163875 . . 12 2012 0 . . 22 27 68.9373634747269 1156814176000 .5859 12 2013 0 . . 22 27 66.8674114251592 1245954037000 1.39846 12 2014 0 . . 22 27 64.8836867960699 1381036599000 .74008 12 2015 0 . . 22 27 64.8836867960699 1566419858000 .806 12 2016 0 . . 22 27 63.4519824541415 1775283931000 .79778 12 2017 0 . . 22 27 77.1522675466497 1884300190000 .78925 12 2018 0 . . 22 27 77.1522675466497 2074388287000 .94017 12 2019 0 . . 22 27 81.2228185197292 . . 13 2012 0 . . 1 38 65.0827815315315 9.6062e+10 1.17786 13 2013 0 . . 1 38 54.1462128879892 9.5928e+10 1.38657 13 2014 0 . . 1 38 60.5439569623816 9.4429e+10 1.452 13 2015 0 . . 1 38 62.8988888888888 9.5651e+10 1.21263 13 2016 0 . . 1 38 65.3443783068783 9.5748e+10 1.34063 13 2017 0 . . 1 38 71.1719052712901 9.7109e+10 1.26075 13 2018 0 . . 1 38 67.1157407407407 9.9333e+10 1.2366 13 2019 0 . . 1 38 73.3401056481105 . . 14 2012 0 . . 1 38 85.1108333333333 2.5132e+10 3.069 14 2013 0 . . 1 38 78.3646676788124 2.4859e+10 3.8815 14 2014 0 . . 1 38 82.8485281697575 2.9748e+10 3.774 14 2015 0 . . 1 38 87.6689891975308 3.1402e+10 3.3208 14 2016 0 . . 1 38 86.8681216931216 3.003e+10 3.06722 14 2017 0 . . 1 38 86.059018244488 2.9597e+10 3.37656 14 2018 0 . . 1 38 83.2547067901234 2.9766e+10 3.46714 14 2019 0 . . 1 38 81.0143968124971 . . 15 2012 0 . . 1 44 54.2064072116671 3.7138e+09 6.51067 15 2013 0 . . 1 44 49.3855580693816 3.7732e+09 6.377 15 2014 0 . . 1 44 58.0994475138121 3.7732e+09 . 15 2015 0 . . 1 44 58.0994475138121 3.7732e+09 . 15 2016 0 . . 1 44 58.0994475138121 3.7732e+09 . 15 2017 0 . . 1 44 58.0994475138121 3.7732e+09 . 15 2018 0 . . 1 44 58.0994475138121 3.7732e+09 . 15 2019 0 . . 1 44 58.0994475138121 . . 16 2012 1 20242 2014 1 27 90.6414232781168 6.42127e+11 .9764 16 2013 1 20242 2014 1 27 90.3483331291851 7.02995e+11 .9761 16 2014 1 20242 2014 1 27 92.4878143233335 7.72092e+11 .9422 16 2015 1 20242 2014 1 27 92.9414272388059 8.899e+11 .8555 16 2016 1 20242 2014 1 27 92.1333577951728 9.14869e+11 .7717 16 2017 1 20242 2014 1 27 93.3905436884669 8.97326e+11 .81556 16 2018 1 20242 2014 1 27 92.7779656468062 9.43156e+11 .78613 16 2019 1 20242 2014 1 27 92.398009328669 . . 17 2012 1 20909 2016 1 27 80.8471392763731 7.18859e+11 1.037 17 2013 1 20909 2016 1 27 82.1811560917851 7.53857e+11 1.83822 17 2014 1 20909 2016 1 27 82.3430878986592 7.91451e+11 1.76333 17 2015 1 20909 2016 1 27 79.4056063432835 8.73446e+11 1.1044 17 2016 1 20909 2016 1 27 85.172203196347 9.33001e+11 1.08522 17 2017 1 20909 2016 1 27 87.0337827443741 9.76318e+11 1.1044 17 2018 1 20909 2016 1 27 85.2217391304347 9.75165e+11 1.07567 17 2019 1 20909 2016 1 27 81.5128953380452 . . 18 2012 1 20914 2016 1 43 29.4409110915493 2.5026e+09 6.42717 18 2013 1 20914 2016 1 43 53.1428167420814 2.7238e+09 5.87029 18 2014 1 20914 2016 1 43 62.3312531391261 3.1425e+09 5.79714 18 2015 1 20914 2016 1 43 62.3312531391261 3.3212e+09 5.2196 18 2016 1 20914 2016 1 43 56.2171855105678 3.7834e+09 4.8382 18 2017 1 20914 2016 1 43 56.2171855105678 3.923e+09 4.90767 18 2018 1 20914 2016 1 43 55.9665859005422 4.4519e+09 . 18 2019 1 20914 2016 1 43 55.9665859005422 . . 19 2012 1 20073 2013 1 27 89.243820836966 7.6309e+11 .7802 19 2013 1 20073 2013 1 27 84.8257747427731 8.0987e+11 1.6307 19 2014 1 20073 2013 1 27 88.2014380131151 8.83301e+11 .7572 19 2015 1 20073 2013 1 27 86.0320615671641 9.55052e+11 .84 19 2016 1 20073 2013 1 27 90.2010600130463 7.7671e+11 .8387 19 2017 1 20073 2013 1 27 91.378210706751 7.88325e+11 .8622 19 2018 1 20073 2013 1 27 90.4247450348899 8.0651e+11 .83144 19 2019 1 20073 2013 1 27 88.5423746460103 . . 20 2012 1 20885 2016 1 27 89.243820836966 7.6309e+11 .7802 20 2013 1 20885 2016 1 27 84.8257747427731 8.0987e+11 1.6307 20 2014 1 20885 2016 1 27 88.2014380131151 8.83301e+11 .7572 20 2015 1 20885 2016 1 27 86.0320615671641 9.55052e+11 .84 20 2016 1 20885 2016 1 27 90.2010600130463 7.7671e+11 .8387 20 2017 1 20885 2016 1 27 91.378210706751 7.88325e+11 .8622 20 2018 1 20885 2016 1 27 90.4247450348899 8.0651e+11 .83144 20 2019 1 20885 2016 1 27 88.5423746460103 . . 21 2012 1 21426 2017 1 27 89.243820836966 7.6309e+11 .7802 21 2013 1 21426 2017 1 27 84.8257747427731 8.0987e+11 1.6307 21 2014 1 21426 2017 1 27 88.2014380131151 8.83301e+11 .7572 21 2015 1 21426 2017 1 27 86.0320615671641 9.55052e+11 .84 21 2016 1 21426 2017 1 27 90.2010600130463 7.7671e+11 .8387 21 2017 1 21426 2017 1 27 91.378210706751 7.88325e+11 .8622 21 2018 1 21426 2017 1 27 90.4247450348899 8.0651e+11 .83144 21 2019 1 21426 2017 1 27 88.5423746460103 . . 22 2012 1 20933 2016 1 38 62.9688400900901 4.6737e+10 2.02463 22 2013 1 20933 2016 1 38 64.5759531039136 5.0748e+10 .31689 22 2014 1 20933 2016 1 38 61.6874274202062 4.7271e+10 1.97967 22 2015 1 20933 2016 1 38 61.6874274202062 4.500e+10 2.0514 22 2016 1 20933 2016 1 38 65.0246031746031 4.2176e+10 1.79733 22 2017 1 20933 2016 1 38 65.0246031746031 4.1583e+10 .54478 22 2018 1 20933 2016 1 38 64.1606495513163 4.3862e+10 1.75843 22 2019 1 20933 2016 1 38 68.4523148148148 . . 23 2012 1 20608 2015 1 27 82.4275174367916 6.74965e+11 1.0355 23 2013 1 20608 2015 1 27 85.6581689939572 7.01097e+11 1.0775 23 2014 1 20608 2015 1 27 84.9926421231992 7.70842e+11 1.0088 23 2015 1 20608 2015 1 27 85.7501958955224 8.12156e+11 1.04536 23 2016 1 20608 2015 1 27 86.2237361382909 8.39202e+11 .9855 23 2017 1 20608 2015 1 27 86.0688620780591 8.51875e+11 1.0105 23 2018 1 20608 2015 1 27 85.8255233494364 8.79592e+11 .97422 23 2019 1 20608 2015 1 27 86.4759703481592 . . 24 2012 1 21145 2016 1 27 82.4275174367916 6.74965e+11 1.0355 24 2013 1 21145 2016 1 27 85.6581689939572 7.01097e+11 1.0775 24 2014 1 21145 2016 1 27 84.9926421231992 7.70842e+11 1.0088 24 2015 1 21145 2016 1 27 85.7501958955224 8.12156e+11 1.04536 24 2016 1 21145 2016 1 27 86.2237361382909 8.39202e+11 .9855 24 2017 1 21145 2016 1 27 86.0688620780591 8.51875e+11 1.0105 24 2018 1 21145 2016 1 27 85.8255233494364 8.79592e+11 .97422 24 2019 1 21145 2016 1 27 86.4759703481592 . . 25 2012 0 . . 22 37 46.8552386030391 95794131000 12.36467 25 2013 0 . . 22 37 59.8285481083157 99215640000 12.45313 25 2014 0 . . 22 37 53.3679208472686 120223776000 9.907 25 2015 0 . . 22 37 61.2587468193384 123708187000 9.60882 25 2016 0 . . 22 37 60.0940331598226 136881171000 9.37675 25 2017 0 . . 22 37 60.0940331598226 132807322000 9.00338 25 2018 0 . . 22 37 74.2151160108861 132706355000 8.26614 25 2019 0 . . 22 37 74.2151160108861 . . 26 2012 0 . . 22 37 68.4003424876768 97631316000 17.25538 26 2013 0 . . 22 37 68.4003424876768 100390225000 17.29271 26 2014 0 . . 22 37 66.8963935319767 138352379000 11.175 26 2015 0 . . 22 37 69.6903095843935 153539693000 10.56227 26 2016 0 . . 22 37 69.6903095843935 156085673000 10.67275 26 2017 0 . . 22 37 76.7180692114902 151377405000 10.46186 26 2018 0 . . 22 37 79.9576166779399 154522754000 9.50771 26 2019 0 . . 22 37 80.8380690991282 . . 27 2012 0 . . 21 45 59.2591359289617 2.09107e+10 6.26667 27 2013 0 . . 21 45 71.6796875 2.08997e+10 4.36667 27 2014 0 . . 21 45 63.0687169972884 2.2968e+10 1.93333 27 2015 0 . . 21 45 43.0974400871459 2.304e+10 4.325 27 2016 0 . . 21 45 49.3100761217948 2.8213e+10 5.725 27 2017 0 . . 21 45 59.8665582976208 2.9854e+10 4.53333 27 2018 0 . . 21 45 59.8665582976208 3.1546e+10 7.1 27 2019 0 . . 21 45 59.9508477633477 . . 28 2012 0 . . 21 45 61.3660348360655 1.8583e+10 4.7 28 2013 0 . . 21 45 64.7093620665049 2.0449e+10 5.53333 28 2014 0 . . 21 45 64.7093620665049 2.319e+10 6.15 28 2015 0 . . 21 45 67.0509259259259 2.4678e+10 5.85 28 2016 0 . . 21 45 67.0509259259259 2.9033e+10 3.85 28 2017 0 . . 21 45 75.4799078525641 3.3414e+10 4.33333 28 2018 0 . . 21 45 67.4998196248196 3.9217e+10 4.6 28 2019 0 . . 21 45 67.4998196248196 . . 29 2012 0 . . 21 45 . 2.2695e+10 3.525 29 2013 0 . . 21 45 . 2.36531e+10 4.9 29 2014 0 . . 21 45 70.2362994148708 2.64757e+10 4.63333 29 2015 0 . . 21 45 67.6771786492374 2.84153e+10 5.725 29 2016 0 . . 21 45 67.6771786492374 3.23226e+10 7.4 29 2017 0 . . 21 45 67.356109775641 3.77088e+10 4.6 29 2018 0 . . 21 45 68.5662036352889 4.02949e+10 8.7 29 2019 0 . . 21 45 64.2382756132756 . . 30 2012 0 . . 21 45 74.3295765027322 3.0711e+10 .03333 30 2013 0 . . 21 45 72.7096354166666 3.3709e+10 3.9 30 2014 0 . . 21 45 74.6013071895424 3.5431e+10 3.96667 30 2015 0 . . 21 45 72.9674836601307 3.6018e+10 4.9 30 2016 0 . . 21 45 72.9674836601307 4.1751e+10 4.25 30 2017 0 . . 21 45 77.6842548076923 5.0223e+10 4.4 30 2018 0 . . 21 45 77.2033951529481 5.9384e+10 12 30 2019 0 . . 21 45 72.7929292929292 . . 31 2012 0 . . 21 45 . 1.8978e+10 6.05 31 2013 0 . . 21 45 . 2.3843e+10 4.6 31 2014 0 . . 21 45 . 3.0041e+10 5.66667 31 2015 0 . . 21 45 . 4.0185e+10 5.775 31 2016 0 . . 21 45 . 7.3376e+10 2.16667 31 2017 0 . . 21 45 29.45078125 9.2623e+10 4.05 31 2018 0 . . 21 45 31.8309073444657 1.0626e+11 9.3 31 2019 0 . . 21 45 30.1359126984127 . . 32 2012 1 21192 2017 22 37 61.4911864710093 330361707000 5.95 32 2013 1 21192 2017 22 37 63.6958451704545 420341223000 3.75875 32 2014 1 21192 2017 22 37 66.6200320512821 472999472000 2.1 32 2015 1 21192 2017 22 37 63.4216793893129 496604290000 2.03767 32 2016 1 21192 2017 22 37 67.4659304511278 518765122000 2.3475 32 2017 1 21192 2017 22 37 76.6623754690128 513460158000 3.188 32 2018 1 21192 2017 22 37 77.1474458204334 516766280000 3.2872 32 2019 1 21192 2017 22 37 77.1474458204334 . . 33 2012 1 21189 2017 22 27 . 1267851991000 . 33 2013 1 21189 2017 22 27 19.0450224311044 1291268290000 . 33 2014 1 21189 2017 22 27 25.2912832494608 1326368076000 . 33 2015 1 21189 2017 22 27 27.9748319471345 1392390567000 . 33 2016 1 21189 2017 22 27 27.9748319471345 1475891595000 . 33 2017 1 21189 2017 22 27 27.9748319471345 1498728982000 . 33 2018 1 21189 2017 22 27 40.9380471727263 1584093971000 . 33 2019 1 21189 2017 22 27 44.3002544529262 . . 34 2012 1 20731 2015 21 45 61.8535156249999 3.4171e+10 4.76667 34 2013 1 20731 2015 21 45 69.8253532182103 3.6631e+10 5.43333 34 2014 1 20731 2015 21 45 73.7369281045751 3.8113e+10 5.16667 34 2015 1 20731 2015 21 45 66.7726034858387 3.8088e+10 5.73333 34 2016 1 20731 2015 21 45 78.8646033653846 4.2652e+10 5 34 2017 1 20731 2015 21 45 86.1205482488547 7.8313e+10 3.85 34 2018 1 20731 2015 21 45 82.5423881673881 8.3712e+10 5.1 34 2019 1 20731 2015 21 45 81.1087211399711 . . 35 2012 1 20866 2016 21 45 74.3295765027322 3.0711e+10 .03333 35 2013 1 20866 2016 21 45 72.7096354166666 3.3709e+10 3.9 35 2014 1 20866 2016 21 45 74.6013071895424 3.5431e+10 3.96667 35 2015 1 20866 2016 21 45 72.9674836601307 3.6018e+10 4.9 35 2016 1 20866 2016 21 45 77.6842548076923 4.1751e+10 4.25 35 2017 1 20866 2016 21 45 77.6842548076923 5.0223e+10 4.4 35 2018 1 20866 2016 21 45 72.7929292929292 5.9384e+10 12 35 2019 1 20866 2016 21 45 72.7929292929292 . . 36 2012 1 21243 2017 21 45 74.3295765027322 3.0711e+10 .03333 36 2013 1 21243 2017 21 45 72.7096354166666 3.3709e+10 3.9 36 2014 1 21243 2017 21 45 74.6013071895424 3.5431e+10 3.96667 36 2015 1 21243 2017 21 45 72.9674836601307 3.6018e+10 4.9 36 2016 1 21243 2017 21 45 77.6842548076923 4.1751e+10 4.25 36 2017 1 21243 2017 21 45 77.6842548076923 5.0223e+10 4.4 36 2018 1 21243 2017 21 45 72.7929292929292 5.9384e+10 12 36 2019 1 21243 2017 21 45 72.7929292929292 . . 37 2012 1 21264 2017 21 45 71.6796875 2.09107e+10 6.26667 37 2013 1 21264 2017 21 45 63.0687169972884 2.08997e+10 4.36667 37 2014 1 21264 2017 21 45 59.5702614379085 2.2968e+10 1.93333 37 2015 1 21264 2017 21 45 43.0974400871459 2.304e+10 4.325 37 2016 1 21264 2017 21 45 49.3100761217948 2.8213e+10 5.725 37 2017 1 21264 2017 21 45 59.8665582976208 2.9854e+10 4.53333 37 2018 1 21264 2017 21 45 59.8665582976208 3.1546e+10 7.1 37 2019 1 21264 2017 21 45 59.9508477633477 . . 38 2012 1 20867 2016 21 27 70.3916330645161 2.359381e+12 .49723 38 2013 1 20867 2016 21 27 73.7615852073313 2.453456e+12 .58592 38 2014 1 20867 2016 21 27 68.8428165658787 2.484834e+12 .693 38 2015 1 20867 2016 21 27 73.7299613045881 2.641246e+12 .63855 38 2016 1 20867 2016 21 27 75.0277397260274 2.495964e+12 .49815 38 2017 1 20867 2016 21 27 73.0229969941956 2.620646e+12 .67744 38 2018 1 20867 2016 21 27 70.5724637681159 2.556908e+12 .82375 38 2019 1 20867 2016 21 27 71.9122365900383 . . 39 2012 1 21368 2017 21 27 70.9345094086021 2.449591e+12 .57636 39 2013 1 21368 2017 21 27 66.0918692317691 2.383951e+12 .59542 39 2014 1 21368 2017 21 27 68.1731720725673 2.484721e+12 .58689 39 2015 1 21368 2017 21 27 62.2513681592039 2.816676e+12 .54409 39 2016 1 21368 2017 21 27 65.2514313312258 2.522133e+12 .6347 39 2017 1 21368 2017 21 27 73.5190324419568 2.62758e+12 .60322 39 2018 1 21368 2017 21 27 69.8513486312399 2.766977e+12 .61433 39 2019 1 21368 2017 21 27 74.7859366447728 . . 40 2012 1 21130 2016 21 27 72.8064180107526 1.857065e+12 .7325 40 2013 1 21130 2016 21 27 77.3264493695567 1.84686e+12 .79046 40 2014 1 21130 2016 21 27 76.1074308227964 1.824102e+12 .89767 40 2015 1 21130 2016 21 27 79.5152294085129 2.121297e+12 .75654 40 2016 1 21130 2016 21 27 79.6658236740428 2.148855e+12 .84533 40 2017 1 21130 2016 21 27 83.2784579705638 2.154203e+12 .8593 40 2018 1 21130 2016 21 27 84.3029388083735 2.212636e+12 .9338 40 2019 1 21130 2016 21 27 79.7103345648604 . . 41 2012 1 21272 2017 21 27 72.8064180107526 1.857065e+12 .7325 41 2013 1 21272 2017 21 27 77.3264493695567 1.84686e+12 .79046 41 2014 1 21272 2017 21 27 76.1074308227964 1.824102e+12 .89767 41 2015 1 21272 2017 21 27 79.5152294085129 2.121297e+12 .75654 41 2016 1 21272 2017 21 27 79.6658236740428 2.148855e+12 .84533 41 2017 1 21272 2017 21 27 83.2784579705638 2.154203e+12 .8593 41 2018 1 21272 2017 21 27 84.3029388083735 2.212636e+12 .9338 41 2019 1 21272 2017 21 27 79.7103345648604 . . end format %tdnn/dd/CCYY issuedate
0 Response to nearest neighbor matching
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