Dear all,
I have a question regarding some estimations I want to make. I do have an industry level dataset (shown below). I want to see how the shares of employment in particular set of industries are affected by the level of human capital in the country (given that I do not have human capital at the industry level). Any recommendation or tip? Thank you!
Regressions ran
I have a question regarding some estimations I want to make. I do have an industry level dataset (shown below). I want to see how the shares of employment in particular set of industries are affected by the level of human capital in the country (given that I do not have human capital at the industry level). Any recommendation or tip? Thank you!
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float country1 int year str2 isic long Employment double Wages float(lval_worker share_emp tech_intensity hc) 246 1978 "16" 1400 12629858 10.524214 .002866503 1 2.660844 222 1965 "18" 3420 2028000 8.545497 .09492617 1 1.292488 44 1996 "21" 46 533900 10.060503 .0208901 1 . 124 1971 "21" 118000 1019002566 10.575851 .072392635 1 2.857602 100 2010 "20" 13577 42571640 8.357951 .02724516 1 3.0828595 246 1995 "21" 43831 1763566062 11.646667 .11346892 1 3.044641 108 1988 "16" 163 925959 10.30323 .029290207 1 1.1267314 554 1987 "15" . 975945982 . . 1 3.253287 392 2000 "17" 341049 5372777102 10.6837 .03752502 1 3.346039 203 2007 "18" 24799 165827066 8.891901 .02000331 1 3.623968 498 1992 "15" 80222 . . .25048164 1 2.616225 196 1966 "19" . . . . 1 1.8941683 608 1986 "16" 12300 15010535 10.11686 .01952102 1 2.1525567 222 1978 "17" 11010 24016000 9.165105 .18876335 1 1.3997713 204 1980 "15" 2923 7274722 9.587468 .490354 1 1.0910376 426 2001 "15" 1379 5779644 . .05865839 1 2.0724819 404 1984 "19" . . . . 1 1.560953 214 1968 "17" 2000 2643000 9.078338 .0207857 1 1.4700882 748 1981 "15" 5070 18407460 9.185945 .4319673 1 1.637325 554 1985 "16" 816 7413367 10.023375 .002929982 1 3.251434 158 2009 "16" . . . . 1 3.051596 376 1975 "15" 33990 117350158 9.611406 .13880835 1 2.7533054 368 2008 "17" 23896 . 5.825396 .13476658 1 2.126992 604 1983 "18" 27765 33000000 8.037464 .1050976 1 2.0099099 470 1965 "21" 51 22400 8.314738 .0045950087 1 1.8006723 214 1986 "19" . . . . 1 1.8231457 724 1998 "21" 48953 1082879290 10.699554 .021806045 1 2.6019115 108 1972 "20" 135 106286 8.375645 .06358926 1 1.095774 372 1989 "17" 11700 161861015 10.007888 .06174143 1 2.714553 516 1995 "15" . . . . 1 2.0225265 96 1995 "20" . . . . 1 2.570822 372 1966 "16" 2200 5598949 9.934739 .012687354 1 2.3446527 364 2005 "16" 5513 21914759 9.318694 .00525496 1 1.9027244 724 2011 "20" 54086 1591978930 10.062232 .02964497 1 2.822752 12 2019 "17" . . . . 1 2.3839655 496 1993 "20" 3822 651502 5.986059 .1612318 1 2.498854 446 1979 "16" 26 27817 7.543027 .0006590955 1 1.810788 480 2015 "17" 5312 48835173 8.915178 .072704375 1 2.574241 608 1987 "22" 16700 23921031 7.910983 .02489253 1 2.1693232 332 1991 "21" 63 82861 . .002948472 1 1.363874 512 1993 "18" 4722 10772460 8.157207 .18682493 1 . 372 1979 "20" 5500 40319929 9.81428 .024314765 1 2.573603 703 1992 "22" 8232 18220416 . .01848247 1 3.1411164 140 1985 "21" 0 0 . 0 1 1.1813396 686 1983 "18" 2010 7103756 8.586774 .06203704 1 1.1182749 458 2010 "18" 54512 248960211 8.394247 .03059076 1 2.8834276 48 1995 "22" . . . . 1 2.2369032 104 2012 "19" 437 . 6.60469 .012525437 1 1.751026 642 2019 "22" 15187 . . .0129635 1 3.273048 76 2009 "15" 1570059 13129746107 9.505106 .22093193 1 2.4285185 620 2003 "16" 1322 33821693 11.624596 .0015562278 1 2.2359996 332 2001 "19" . . . . 1 1.5170646 704 2000 "22" 21529 27003511 8.138831 .01397011 1 1.9720428 203 2005 "20" 45044 297354844 9.470231 .03735596 1 3.6157014 178 1987 "22" 48 296137 9.16687 .006899526 1 1.2876948 218 2016 "15" 111814 1025998348 9.468237 .5349517 1 2.743183 266 1970 "19" . . . . 1 1.1438366 414 2016 "22" 5553 121070905 9.773097 .04327395 1 2.2288787 440 2001 "18" 38332 67401505 7.739053 .16212147 1 2.93794 364 2009 "16" 7905 129743240 9.683297 .006359711 1 2.0762029 834 2005 "19" 1166 666445 6.657646 .013194075 1 1.5467085 288 2018 "19" . . . . 1 2.4956875 356 2003 "16" 476408 201574453 7.405334 .06293902 1 1.8265676 440 2006 "19" 1675 6681870 8.637326 .006533806 1 3.0892184 616 2017 "18" 71561 515210435 8.778302 .029349893 1 3.4042025 484 1983 "16" . . . . 1 1.994423 682 2014 "16" 205 1227467 8.776001 .00022839368 1 2.603033 566 2012 "20" . . . . 1 1.804649 480 1991 "15" 15108 48134115 9.002466 .1286729 1 2.0638387 112 2019 "15" 143586 813732367 9.267206 .3046795 1 . 784 1978 "20" 957 4649708 9.579989 .04981003 1 1.5641943 360 1974 "15" 138680 58643373 8.19294 .22505315 1 1.4179844 158 1978 "22" 21040 47526850 . .01116802 1 1.846436 702 2017 "20" 2954 60773757 9.82436 .007750677 1 3.974208 620 1981 "21" 18600 . 9.658616 .027189007 1 1.6807364 50 1993 "17" . . . . 1 1.5172774 616 1971 "22" 48000 34138817 8.379455 .013396595 1 2.332807 56 2011 "20" 10599 443198482 10.86143 .0221328 1 3.0989954 218 1992 "19" . . . . 1 2.261897 376 1970 "21" 4040 8857143 10.01788 .01978065 1 2.607219 156 1980 "19" . . . . 1 1.7374357 834 1966 "15" 9577 5090398 8.515907 .29767197 1 1.3049003 44 1978 "17" . . . . 1 . 590 1978 "18" 5256 14027000 9.001743 .18535106 1 2.064524 702 1999 "15" 15216 255810619 10.36397 .04467607 1 2.6636856 426 2014 "17" . . . . 1 1.8554567 620 1965 "17" 107200 . 8.304613 .3477042 1 1.3449032 288 1982 "17" 11395 38025455 8.861428 .17106785 1 1.5895158 100 1978 "22" 11400 16147015 . .009575808 1 2.548244 854 2011 "21" . . . . 1 1.1788955 76 2015 "18" 585874 3155217884 8.468601 .07968566 1 2.8136604 158 2015 "21" 49183 669851989 9.751277 .017863635 1 3.2267625 496 1991 "18" 19705 32976907 8.615227 .3537575 1 2.487254 68 1993 "16" 173 708075 11.673643 .004143514 1 2.258371 266 1966 "20" 2971 3704029 8.6796255 .6262648 1 1.1030468 364 1974 "17" 111250 139396998 8.740964 .2920791 1 1.1481007 196 1972 "17" 1902 2059586 8.742876 .07309762 1 2.000166 380 1970 "21" 75000 206399906 9.868371 .022803284 1 2.0640957 40 1993 "19" 7837 154596379 10.252422 .014087671 1 3.00992 578 2018 "15" 52605 2871048017 10.797338 .2405746 1 3.652976 end
Code:
reg share_emp hc i.country1 i.year i.isic1 if tech_intensity==1, robust
Code:
reg share_emp hc i.country1 i.year i.isic1 if tech_intensity==3, robust
