I am new to the forum and to stata as well. I know this topic has been covered multiple times but I am not getting the desired output. I am looking to create the HHI (Herfindahl-Hirschman Index) for US firms per year. The dataex below shows part of the dataset intend to use, based on the forum search the data below should be sufficient to create the HHI (please inform me if I am incorrect in the matter)
The id variables for the firms are GVKEY, lpermno and cusip_6 (A shortened version of CUSIP). sale is the net sales of the firm, mkvalt is the market value of the firm, sic2d is the 2 digit SIC code.
I have tried the following: Using HHI and HHI5 program I tried:
Code:
hhi sale, by (year sic2d)
I then tried what Nick Cox stated in the same post linked above and tested this:
Code:
entropyetc sale, by(sic2d year)
I understand this is not a unique case and is answered multiple times, answer is probably simple but I can't seem to figure it out. I do apologies for the repeat of this topic but I I'd appreciate the help! Thanks!
Code:
input str6(gvkey cusip_6) double(lpermno year sale mkvalt) str2 sic2d "178698" "000307" 14945 2014 132.968 660.8841 "80" "178698" "000307" 14945 2015 212.261 434.8348 "80" "178698" "000307" 14945 2016 279.77 171.3998 "80" "178698" "000307" 14945 2017 317.641 214.848 "80" "021542" "000360" 76868 2009 245.282 335.5204 "35" "021542" "000360" 76868 2010 244.552 465.6343 "35" "021542" "000360" 76868 2011 266.22 504.4228 "35" "021542" "000360" 76868 2012 303.114 511.6907 "35" "021542" "000360" 76868 2013 321.14 1172.9165 "35" "021542" "000360" 76868 2014 356.322 1210.0004 "35" "021542" "000360" 76868 2015 358.632 1230.9386 "35" "021542" "000360" 76868 2016 383.977 1740.1156 "35" "021542" "000360" 76868 2017 405.232 1923.9241 "35" "001004" "000361" 54594 2009 1352.151 777.8348 "50" "001004" "000361" 54594 2010 1775.782 1049.8206 "50" "001004" "000361" 54594 2011 2074.498 485.2897 "50" "001004" "000361" 54594 2012 2167.1 790.0029 "50" "001004" "000361" 54594 2013 2035 961.308 "50" "001004" "000361" 54594 2014 1594.3 1046.3954 "50" "001004" "000361" 54594 2015 1662.6 842.5112 "50" "001004" "000361" 54594 2016 1767.6 1200.3288 "50" "210418" "000375" 88953 2009 31795 . "36" "210418" "000375" 88953 2010 31589 . "36" "210418" "000375" 88953 2011 37990 . "36" "210418" "000375" 88953 2012 39336 . "36" "210418" "000375" 88953 2013 41848 . "36" "210418" "000375" 88953 2014 39830 . "36" "210418" "000375" 88953 2015 35481 . "36" "210418" "000375" 88953 2016 33828 . "36" "210418" "000375" 88953 2017 34312 . "36" "164506" "00081T" 90825 2009 1272.5 397.2842 "27" "164506" "00081T" 90825 2010 1330.5 467.944 "27" "164506" "00081T" 90825 2011 1318.4 535.3434 "27" "164506" "00081T" 90825 2012 1758.5 830.4696 "27" "164506" "00081T" 90825 2013 1765.1 763.8221 "27" "164506" "00081T" 90825 2014 1689.2 1008.3181 "27" "164506" "00081T" 90825 2015 1510.4 753.2132 "27" "164506" "00081T" 90825 2016 1557.1 1408.1864 "27" "164506" "00081T" 90825 2017 1948.8 1301.5448 "27" "017173" "000868" 12480 2010 56.734 93.0103 "60" "017173" "000868" 12480 2011 53.569 82.2332 "60" "017173" "000868" 12480 2012 52.243 96.5137 "60" "017173" "000868" 12480 2013 49.304 108.1975 "60" "017173" "000868" 12480 2014 49.43 130.848 "60" "017173" "000868" 12480 2015 51.87 128.652 "60" "017173" "000868" 12480 2016 53.259 189.5 "60" "017173" "000868" 12480 2017 65.934 207.5592 "60" "065569" "00086T" 85452 2009 468.889 73.0649 "59" "065569" "00086T" 85452 2010 448.058 63.6185 "59" "001013" "000886" 50906 2009 996.7 805.644 "36" "001013" "000886" 50906 2010 1156.6 1231.524 "36" "061523" "00088U" 82544 2009 28.161 41.601 "73" "017653" "000899" 15056 2014 5.916 103.7916 "28" "017653" "000899" 15056 2015 7.177 86.4539 "28" "017653" "000899" 15056 2016 10.661 65.9814 "28" "017653" "000899" 15056 2017 15.761 145.4676 "28" "001410" "000957" 47730 2009 3481.823 970.7006 "73" "001410" "000957" 47730 2010 3495.747 1186.9193 "73" "001410" "000957" 47730 2011 4246.842 1078.3933 "73" "001410" "000957" 47730 2012 4300.265 1033.486 "73" "001410" "000957" 47730 2013 4809.281 1526.1998 "73" "001410" "000957" 47730 2014 5032.8 1539.2992 "73" "001410" "000957" 47730 2015 4897.8 1593.4104 "73" "001410" "000957" 47730 2016 5144.7 2172.8089 "73" "001410" "000957" 47730 2017 5453.6 2749.1609 "73" "014438" "00101J" 13567 2013 3309 8497.1675 "73" "014438" "00101J" 13567 2014 3408 6173.9051 "73" "014438" "00101J" 13567 2015 3574 4958.915 "73" "011903" "001031" 10025 2009 744.819 238.9978 "30" "011903" "001031" 10025 2010 800.57 149.7049 "30" "011903" "001031" 10025 2011 974.792 148.3947 "30" "011903" "001031" 10025 2012 1152.535 353.5968 "30" "011903" "001031" 10025 2013 1143.852 332.8114 "30" "011903" "001031" 10025 2014 1192.99 233.6752 "30" "011903" "001031" 10025 2015 1141.391 408.24 "30" "011903" "001031" 10025 2016 1095.83 560.2387 "30" "001449" "001055" 57904 2009 18237 . "63" "001449" "001055" 57904 2010 20732 . "63" "001449" "001055" 57904 2011 22171 20172.5706 "63" "001449" "001055" 57904 2012 25364 . "63" "001449" "001055" 57904 2013 23939 . "63" "001449" "001055" 57904 2014 22728 . "63" "001449" "001055" 57904 2015 20904 25420.362 "63" "001449" "001055" 57904 2016 22374 . "63" "001449" "001055" 57904 2017 21700 . "63" "025180" "001084" 77520 2009 6630.4 2989.9624 "35" "025180" "001084" 77520 2010 6896.6 4718.675 "35" "025180" "001084" 77520 2011 8773.2 4176.4692 "35" "025180" "001084" 77520 2012 9962.2 4755.6019 "35" "025180" "001084" 77520 2013 10786.9 5762.8568 "35" "025180" "001084" 77520 2014 9723.7 4029.3992 "35" "025180" "001084" 77520 2015 7467.3 3804.3629 "35" "025180" "001084" 77520 2016 7410.5 4597.8449 "35" "025180" "001084" 77520 2017 8306.5 5682.5422 "35" "032638" "00108J" 17045 2017 36.506 80.5613 "35" "011361" "00108M" 63829 2009 52.526 23.6557 "50" "011361" "00108M" 63829 2010 45.704 24.3934 "50" "011361" "00108M" 63829 2011 42.894 23.4219 "50" "011361" "00108M" 63829 2012 51.117 20.7673 "50" "011361" "00108M" 63829 2013 57.916 20.8248 "50" end
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