Dear Statalists,
I am posting to ask for your help with entropy balance matching. I am trying to apply entropy balance technique to match a group of treatment firms to a group of control firms. Firms in each pair should be from the same country and industry, then the covariates to be matched are market capitalisation and price-to-book ratio. I have attached a part of the sample. I understand the principles of entropy balance but I can't manage to get the list of the matched firm pairs. Could anyone knowing this technique well please help me with the codes?
Thank you very much in advance.
I am posting to ask for your help with entropy balance matching. I am trying to apply entropy balance technique to match a group of treatment firms to a group of control firms. Firms in each pair should be from the same country and industry, then the covariates to be matched are market capitalisation and price-to-book ratio. I have attached a part of the sample. I understand the principles of entropy balance but I can't manage to get the list of the matched firm pairs. Could anyone knowing this technique well please help me with the codes?
Thank you very much in advance.
Code:
input byte id str12 isin byte treatment str2 country byte industry float(market_cap price_to_book) 1 "DE0007664005" 1 "DE" 29 43540.5 .244 2 "DE000UNSE018" 1 "DE" 35 951.496 .215 3 "DE0007100000" 1 "DE" 29 65805.7 .76 4 "IT0003128367" 1 "IT" 35 51138.4 1.215 5 "IT0003132476" 1 "IT" 6 47903.93 .867 6 "DE0005557508" 1 "DE" 61 93236.8 1.068 7 "DE000ENAG999" 1 "DE" 35 24664.637 1.128 8 "DE0005552004" 1 "DE" 53 43794.55 1.848 9 "DE0008404005" 1 "DE" 65 81287.94 1.579 10 "DE000BASF111" 1 "DE" 20 41541.91 1.015 12 "FR0010208488" 1 "FR" 35 32603.596 .83 14 "FR0010208488" 1 "FR" 35 32603.596 .83 16 "FR0014003U94" 1 "FR" 45 354.671 1.683 18 "FR0000073272" 1 "FR" 30 49953.41 4.597 20 "FR0000035164" 1 "FR" 30 1135.5 1.8 22 "IT0005037210" 1 "IT" 70 1076.322 2.677 24 "DE0005810055" 1 "DE" 66 31027 3.424 26 "DE000A0ETBQ4" 1 "DE" 66 541.202 .703 28 "DE0005493365" 1 "DE" 66 639.922 2.346 30 "DE000FTG1111" 1 "DE" 66 703.092 1.156 32 "IT0003097257" 1 "IT" 28 347.5 1.3 34 "GB00BYM8GJ06" 1 "GB" 73 1004.122 1.18 36 "GB00BGDT3G23" 1 "GB" 73 4774.876 61.913 38 "GB00B5NR1S72" 1 "GB" 74 511.243 1.654 40 "GB00B61TVQ02" 1 "GB" 45 3474.502 1.96 42 "IT0005452658" 0 "IT" 70 572.2 5.5 44 "NL0015000N33" 0 "IT" 70 1003.061 .991 46 "FR0010220475" 0 "FR" 30 9541.772 1.048 48 "FR0000032278" 0 "FR" 30 196.5 1.7 50 "FR0014007LQ2" 0 "FR" 45 44.93958 1.969 52 "FR0013030152" 0 "FR" 35 264.84802 4.198 54 "FR0012532810" 0 "FR" 35 643 5.2 56 "DE0006095003" 0 "DE" 66 2997.577 3.133 58 "DE000A161077" 0 "DE" 66 142.38539 .686 60 "DE000A0B9N37" 0 "DE" 66 228.9467 6.193 62 "DE000A2GSU42" 0 "DE" 66 239.75325 .76 64 "DE0005408686" 0 "DE" 66 377.9 2 66 "DE0008148206" 0 "DE" 66 103.45737 .395 68 "IT0001237053" 0 "IT" 28 191.14803 .69 70 "IT0005107492" 0 "IT" 28 223.59818 1.057 72 "JE00B8KF9B49" 0 "GB" 73 9938.426 2.111 74 "IM00BQ8NYV14" 0 "GB" 73 1316.8152 1.197 76 "GB00B01F7T14" 0 "GB" 73 208.87483 4.834 78 "GB00BDVZYZ77" 0 "GB" 74 2108.1 .4 80 "GB00B19NLV48" 0 "GB" 74 27868.4 8.8 82 "GB0009697037" 0 "GB" 74 1601.4 2.1 84 "GB00BLGXWY71" 0 "GB" 74 618.8959 1.955 86 "GB00BYQB9V88" 0 "GB" 45 786.445 1.162 88 "GB00BD0SFR60" 0 "GB" 45 183.5 3.2 90 "GB00BVYVFW23" 0 "GB" 45 5523.5 9.3
