Dear all,
I have the following dataset
And I would like to know how I can obtain a variable that describes the ratio between value added per worker by tech intensity in a particular year over the average value added per worker of all tech intensities in that year (and also over the median value added per worker)
For instance, I want to know the ratio of value added per worker in tech intensity==1 in year 1989 over average value added per worker in year 1989 (the same for all years, and also for the median)
Thank you very much,
I have the following dataset
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float(country year) str2 isic float(ValueAdded Employment val_per_worker tech_intensity) 8 1995 "15" . 4515 . 1 8 1996 "15" . 5836 . 1 8 1997 "15" . 8599 . 1 8 1998 "15" . 4316 . 1 8 1999 "15" . 4032 . 1 8 2000 "15" 13920062 3919 3551.9424 1 8 2001 "15" 14884939 3144 4734.3955 1 8 2002 "15" 17994426 3790 4747.8696 1 8 2003 "15" 27076334 3965 6828.836 1 8 2004 "15" 36551080 4599 7947.615 1 8 2005 "15" 50478552 5230 9651.731 1 8 2006 "15" 51174140 5503 9299.317 1 8 2007 "15" 65760408 6532 10067.423 1 8 2008 "15" 75889648 6243 12155.958 1 8 2009 "15" 69684768 6832 10199.76 1 8 2010 "15" 76790928 7208 10653.57 1 8 2011 "15" 72062648 7804 9234.065 1 8 2012 "15" 75477424 8202 9202.319 1 8 2013 "15" 86713528 8784 9871.759 1 8 2014 "15" 88902760 8970 9911.121 1 8 2015 "15" 86198296 11287 7636.954 1 8 2016 "15" 103714640 14582 7112.511 1 8 2017 "15" 113921072 15307 7442.417 1 8 2018 "15" 136004384 16373 8306.626 1 8 2019 "15" 159106672 17273 9211.293 1 8 2020 "15" 155971456 16480 9464.287 1 8 1995 "16" . 976 . 1 8 1996 "16" . 2148 . 1 8 1997 "16" . 1946 . 1 8 1998 "16" . 1399 . 1 8 1999 "16" . 1137 . 1 8 2000 "16" 2835555 899 3154.121 1 8 2001 "16" 2138344 546 3916.381 1 8 2002 "16" 1191542 418 2850.579 1 8 2003 "16" 1178961 374 3152.302 1 8 2004 "16" -127729 253 . 1 8 2005 "16" 1404002 240 5850.008 1 8 2006 "16" 876463 188 4662.037 1 8 2007 "16" 983944 174 5654.851 1 8 2008 "16" 520534 147 3541.0476 1 8 2009 "16" 620027 123 5040.87 1 8 2010 "16" 1208274 185 6531.211 1 8 2011 "16" 1432824 104 13777.154 1 8 2012 "16" 628974 92 6836.674 1 8 2013 "16" -312428 144 . 1 8 2014 "16" 1327702 273 4863.3774 1 8 2015 "16" . . . 1 8 2016 "16" . . . 1 8 2017 "16" . . . 1 8 2018 "16" . . . 1 8 2019 "16" . . . 1 8 2020 "16" . . . 1 8 1995 "17" . 172 . 1 8 1996 "17" . 106 . 1 8 1997 "17" . 960 . 1 8 1998 "17" . 10082 . 1 8 1999 "17" . 8223 . 1 8 2000 "17" 14949528 8717 1714.9855 1 8 2001 "17" 17252980 8562 2015.0642 1 8 2002 "17" 25635992 11638 2202.7832 1 8 2003 "17" 28142036 10479 2685.565 1 8 2004 "17" 29246026 10213 2863.608 1 8 2005 "17" 33258012 10018 3319.8254 1 8 2006 "17" 37106828 9807 3783.708 1 8 2007 "17" 56726600 12639 4488.219 1 8 2008 "17" 70314784 13162 5342.257 1 8 2009 "17" 60823208 11845 5134.927 1 8 2010 "17" 66085984 14105 4685.2876 1 8 2011 "17" 73213304 14172 5166.053 1 8 2012 "17" 78955832 15088 5233.022 1 8 2013 "17" 89212400 15873 5620.387 1 8 2014 "17" 107036280 18485 5790.44 1 8 2015 "17" 6424091 981 6548.513 1 8 2016 "17" 5398844 991 5447.875 1 8 2017 "17" 8043661 1449 5551.181 1 8 2018 "17" 11732658 1943 6038.424 1 8 2019 "17" 12080018 2274 5312.233 1 8 2020 "17" 11841980 2170 5457.134 1 8 1995 "18" . 1532 . 1 8 1996 "18" . 2243 . 1 8 1997 "18" . 1623 . 1 8 1998 "18" . . . 1 8 1999 "18" . . . 1 8 2000 "18" . . . 1 8 2001 "18" . . . 1 8 2002 "18" . . . 1 8 2003 "18" . . . 1 8 2004 "18" . . . 1 8 2005 "18" . . . 1 8 2006 "18" . . . 1 8 2007 "18" . . . 1 8 2008 "18" . . . 1 8 2009 "18" . . . 1 8 2010 "18" . . . 1 8 2011 "18" . . . 1 8 2012 "18" . . . 1 8 2013 "18" . . . 1 8 2014 "18" . . . 1 8 2015 "18" 78066320 19550 3993.162 1 8 2016 "18" 92327672 23083 3999.8125 1 end
For instance, I want to know the ratio of value added per worker in tech intensity==1 in year 1989 over average value added per worker in year 1989 (the same for all years, and also for the median)
Thank you very much,
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