----------------------------------------------------------------------------------------------------------------- name: log: /Users/bernardofanfani/Desktop/teaching/research_topics_labor/lab_7/seventh_lab/lecture_7.log log type: text opened on: 17 Nov 2024, 18:50:42 . . ********************************************* . * FIRST EXAMPLE: . /* > Application of the DD method to Lalonde's (1985) data to estimate > the effect of NWD program participation on income. > */ . . * We open the Lalonde (1985) database. . . use t1_lalonde_nsw, clear . . des Contains data from t1_lalonde_nsw.dta Observations: 722 Variables: 10 18 May 2012 09:35 ----------------------------------------------------------------------------------------------------------------- Variable Storage Display Value name type format label Variable label ----------------------------------------------------------------------------------------------------------------- data_id str14 %14s treat byte %8.0g age byte %8.0g education byte %8.0g black byte %8.0g hispanic byte %8.0g married byte %8.0g nodegree byte %8.0g re75 float %9.0g re78 float %9.0g ----------------------------------------------------------------------------------------------------------------- Sorted by: . . * we generate outcome Y as income in 1975. . . gen Y = re75 . . * we generate a variable t equal to the year 1975 . . gen t = 1975 . . * we generate a variable X =1 if the person participates in the NWD . . gen X = treat . . * we keep only these variables and save the database . keep Y t X . describe Contains data from t1_lalonde_nsw.dta Observations: 722 Variables: 3 18 May 2012 09:35 ----------------------------------------------------------------------------------------------------------------- Variable Storage Display Value name type format label Variable label ----------------------------------------------------------------------------------------------------------------- Y float %9.0g t float %9.0g X float %9.0g ----------------------------------------------------------------------------------------------------------------- Sorted by: Note: Dataset has changed since last saved. . . save panel1975.dta, replace file panel1975.dta saved . . * we open the Lalonde database again (1985) and repeat for 1978. . use t1_lalonde_nsw, clear . . des Contains data from t1_lalonde_nsw.dta Observations: 722 Variables: 10 18 May 2012 09:35 ----------------------------------------------------------------------------------------------------------------- Variable Storage Display Value name type format label Variable label ----------------------------------------------------------------------------------------------------------------- data_id str14 %14s treat byte %8.0g age byte %8.0g education byte %8.0g black byte %8.0g hispanic byte %8.0g married byte %8.0g nodegree byte %8.0g re75 float %9.0g re78 float %9.0g ----------------------------------------------------------------------------------------------------------------- Sorted by: . . * we generate outcome Y as income in 1978. . . gen Y = re78 . . * we generate a variable t equal to the year 1978 . . gen t = 1978 . . * we generate a variable X =1 if the person participates in the NWD . . gen X = treat . . * we keep only these variables and append the panel 1975 . keep Y t X . . describe Contains data from t1_lalonde_nsw.dta Observations: 722 Variables: 3 18 May 2012 09:35 ----------------------------------------------------------------------------------------------------------------- Variable Storage Display Value name type format label Variable label ----------------------------------------------------------------------------------------------------------------- Y float %9.0g t float %9.0g X float %9.0g ----------------------------------------------------------------------------------------------------------------- Sorted by: Note: Dataset has changed since last saved. . . append using panel1975.dta . . des Contains data from t1_lalonde_nsw.dta Observations: 1,444 Variables: 3 18 May 2012 09:35 ----------------------------------------------------------------------------------------------------------------- Variable Storage Display Value name type format label Variable label ----------------------------------------------------------------------------------------------------------------- Y float %9.0g t float %9.0g X float %9.0g ----------------------------------------------------------------------------------------------------------------- Sorted by: Note: Dataset has changed since last saved. . . ta t t | Freq. Percent Cum. ------------+----------------------------------- 1975 | 722 50.00 50.00 1978 | 722 50.00 100.00 ------------+----------------------------------- Total | 1,444 100.00 . ta X X | Freq. Percent Cum. ------------+----------------------------------- 0 | 850 58.86 58.86 1 | 594 41.14 100.00 ------------+----------------------------------- Total | 1,444 100.00 . su Y Variable | Obs Mean Std. dev. Min Max -------------+--------------------------------------------------------- Y | 1,444 4248.766 5815.088 0 60307.93 . . * DiD regression can be estimated as: . . reg Y i.X##i.t Source | SS df MS Number of obs = 1,444 -------------+---------------------------------- F(3, 1440) = 23.07 Model | 2.2374e+09 3 745785215 Prob > F = 0.0000 Residual | 4.6558e+10 1,440 32331972.4 R-squared = 0.0459 -------------+---------------------------------- Adj R-squared = 0.0439 Total | 4.8795e+10 1,443 33815243.2 Root MSE = 5686.1 ------------------------------------------------------------------------------ Y | Coefficient Std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- 1.X | 39.41544 430.0431 0.09 0.927 -804.1626 882.9935 | t | 1978 | 2063.366 390.0647 5.29 0.000 1298.21 2828.521 | X#t | 1 1978 | 846.8883 608.1728 1.39 0.164 -346.1113 2039.888 | _cons | 3026.683 275.8174 10.97 0.000 2485.636 3567.73 ------------------------------------------------------------------------------ . . . . ********************************************* . * SECOND EXAMPLE: . /* > Application of the DiD method based on the paper > Draca, Mirko, Stephen Machin and John Van Reenen. 2011. "Minimum Wages and Firm Profitability." American Econom > ic Journal: Applied Economics, 3(1): 129-51. > */ . . . use "draca_etal_2011_AEJ.dta", clear . . describe Contains data from draca_etal_2011_AEJ.dta Observations: 20,914 Variables: 42 16 Oct 2018 15:13 (_dta has notes) ----------------------------------------------------------------------------------------------------------------- Variable Storage Display Value name type format label Variable label ----------------------------------------------------------------------------------------------------------------- regno str8 %9s compay registration number year float %9.0g year month byte %9.0g reporting month turn long %12.0g turnover(in 1000s) emp long %12.0g employment (headcount) renu long %12.0g renumeration data from DVD in thousands netprofit long %12.0g net ebit profits cap long %12.0g tangible fixed assets (in 1000s) avwage float %9.0g Average firm-level wage (raw) net_pcm float %9.0g netprof/turn ln_avwage float %9.0g Average firm-level wage (logged) uksic int %8.0g 4-digit industry code 2003 numeric format unionmem float %9.0g sic4 industry proportion of union members female float %9.0g sic4 industry proportion of female workers ptwk float %9.0g sic4 industry proportion of part-time workers gorwk float %27.0g gorwklbl government office region lnemp float %9.0g log number of employees (headcount) manuf float %9.0g firms operating in manufacturing whsle float %9.0g firms operating in wholesale trade retail float %9.0g firms operating in retail trade hospitality float %9.0g firms operating in hospitality bizservices float %9.0g firms operating in business services capsale float %9.0g capital sales ratio grad2 float %9.0g graduate proportion per gorwk region-sic2 sic2 float %9.0g 2-digit uksic placebo float %9.0g placebo policy time period, 1997-1999 ptreat float %9.0g constant indicator of placebo treatment group (avwage<£10,800 in 1996) ptreat_placebo float %9.0g ptreat*placebo interaction term sic3 float %9.0g NMW float %9.0g NMW policy period, 2000-2002 ctreat1 float %9.0g constant indicator of NMW treatment group (avwage<£12,000 in 1999) treat1_NMW float %9.0g ctreat1*NMW interaction term c_avwage99 float %9.0g constant indicator of avwage in 1999 avwage99_NMW float %9.0g c_avwage99*NMW interaction c_avwage96 float %9.0g constant indicator of avwage in 1996 avwage96_plac~o float %9.0g c_avwage99*NMW interaction pp float %9.0g final sample for min wage period ff float %9.0g final sample for placebo period wb_sales float %9.0g renu/turn turnemp float %9.0g turnover/employment lturnemp float %9.0g log(turnover/employment) split byte %8.0g 2 quantiles of sic3_ebit_pcm ----------------------------------------------------------------------------------------------------------------- Sorted by: . . ta year year | Freq. Percent Cum. ------------+----------------------------------- 1994 | 1,734 8.29 8.29 1995 | 2,189 10.47 18.76 1996 | 2,277 10.89 29.65 1997 | 2,317 11.08 40.72 1998 | 2,362 11.29 52.02 1999 | 2,451 11.72 63.74 2000 | 2,444 11.69 75.42 2001 | 2,580 12.34 87.76 2002 | 2,560 12.24 100.00 ------------+----------------------------------- Total | 20,914 100.00 . . * Definition of treatment group. . * firms with average wage less than or = 12 thousand in 1999 are X=1 . gen treat = 1 if avwage<=12 & year==1999 (20,594 missing values generated) . . * firms with average wages between 12 and 20 thousand in 1999 are the control group . replace treat = 0 if avwage>12 & avwage <= 20 & year==1999 (754 real changes made) . . * we now assign treatment to years other than 1999. . * if a firm is treat=1 in 1999 -> treat=1 in all other years . * if a firm is treat=0 in 1999 -> treat=0 in all other years . sort regno treat . by regno: replace treat = treat[1] (5,801 real changes made) . . * After Policy Dummy . gen post = 1 if year >= 2000 (13,330 missing values generated) . replace post = 0 if year >= 1997 & year < 2000 (7,130 real changes made) . . * Interaction . gen post_treat = treat * post (15,817 missing values generated) . . . ***** . * ESTIMATES OF THE DD EFFECTS OF THE MINIMUM WAGE ON AVERAGE WAGES AND PROFITS. . . * Has the minimum wage had any effect on the average wage of firms? . * * Log Wages . reg ln_avwage post_treat post treat if pp==1,cluster(regno) Linear regression Number of obs = 4,112 F(3, 950) = 352.31 Prob > F = 0.0000 R-squared = 0.5007 Root MSE = .25342 (Std. err. adjusted for 951 clusters in regno) ------------------------------------------------------------------------------ | Robust ln_avwage | Coefficient std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- post_treat | .1109065 .0285971 3.88 0.000 .0547858 .1670272 post | .1179274 .0072592 16.25 0.000 .1036815 .1321732 treat | -.6259053 .0238656 -26.23 0.000 -.6727408 -.5790699 _cons | 2.775202 .0066674 416.23 0.000 2.762118 2.788287 ------------------------------------------------------------------------------ . . * we can include other independent variables to make the DD hypothesis more credible... . . reg ln_avwage post_treat post treat NMW grad2 unionmem ptwk female i.sic2 i.year i.gorwk if pp==1,cluster(regno > ) note: NMW omitted because of collinearity. note: 2002.year omitted because of collinearity. Linear regression Number of obs = 4,112 F(71, 950) = . Prob > F = . R-squared = 0.5899 Root MSE = .23174 (Std. err. adjusted for 951 clusters in regno) ---------------------------------------------------------------------------------------------- | Robust ln_avwage | Coefficient std. err. t P>|t| [95% conf. interval] -----------------------------+---------------------------------------------------------------- post_treat | .090286 .025872 3.49 0.001 .0395131 .141059 post | .2122048 .0124446 17.05 0.000 .1877827 .236627 treat | -.5477864 .0247391 -22.14 0.000 -.596336 -.4992368 NMW | 0 (omitted) grad2 | .3390989 .1139424 2.98 0.003 .1154911 .5627068 unionmem | -.3345902 .0962635 -3.48 0.001 -.5235039 -.1456766 ptwk | -1.002254 .1871082 -5.36 0.000 -1.369447 -.6350604 female | .1226728 .0861486 1.42 0.155 -.0463908 .2917364 | sic2 | 5 | -.3420638 .0749231 -4.57 0.000 -.4890976 -.19503 10 | .089203 .0959293 0.93 0.353 -.0990549 .2774609 14 | -.1553175 .1939303 -0.80 0.423 -.5358987 .2252637 15 | -.1430617 .0820198 -1.74 0.081 -.3040225 .0178992 17 | -.1564547 .0889702 -1.76 0.079 -.3310555 .0181462 18 | -.1892294 .1639873 -1.15 0.249 -.5110485 .1325898 20 | -.1863092 .0833485 -2.24 0.026 -.3498776 -.0227409 21 | -.0389195 .0843741 -0.46 0.645 -.2045006 .1266617 22 | -.1430063 .0890632 -1.61 0.109 -.3177896 .0317769 23 | -.0894711 .0886463 -1.01 0.313 -.2634362 .0844941 24 | -.1635381 .0928641 -1.76 0.079 -.3457805 .0187044 25 | -.1566978 .0906109 -1.73 0.084 -.3345185 .0211229 26 | -.0761725 .0882435 -0.86 0.388 -.2493473 .0970023 27 | -.0163217 .0954076 -0.17 0.864 -.2035557 .1709124 28 | -.0967456 .0815506 -1.19 0.236 -.2567857 .0632945 29 | -.0947883 .0863439 -1.10 0.273 -.2642352 .0746585 30 | -.4244965 .0961395 -4.42 0.000 -.6131668 -.2358263 31 | -.1920032 .0888823 -2.16 0.031 -.3664315 -.0175749 32 | -.2303803 .0848812 -2.71 0.007 -.3969566 -.0638041 33 | -.2136567 .1235428 -1.73 0.084 -.456105 .0287916 34 | -.0505265 .1166866 -0.43 0.665 -.2795198 .1784668 35 | -.0247522 .09486 -0.26 0.794 -.2109115 .1614071 36 | -.1394822 .0812642 -1.72 0.086 -.2989604 .0199959 40 | -.0300801 .1625407 -0.19 0.853 -.3490604 .2889002 41 | .033569 .0927836 0.36 0.718 -.1485155 .2156535 45 | -.0612454 .0827997 -0.74 0.460 -.2237369 .1012461 50 | -.0977614 .0763663 -1.28 0.201 -.2476275 .0521047 51 | -.1500427 .0774111 -1.94 0.053 -.3019591 .0018738 52 | .1082318 .0979741 1.10 0.270 -.0840388 .3005025 55 | -.0316873 .0913653 -0.35 0.729 -.2109884 .1476138 60 | -.0672338 .0854375 -0.79 0.432 -.234902 .1004343 61 | -.2114776 .1003874 -2.11 0.035 -.4084842 -.014471 62 | .1359076 .0963807 1.41 0.159 -.053236 .3250512 63 | -.0910476 .0969327 -0.94 0.348 -.2812745 .0991792 64 | -.0714363 .1133696 -0.63 0.529 -.2939202 .1510475 65 | -.1299506 .0870054 -1.49 0.136 -.3006955 .0407944 66 | -.1172152 .0925507 -1.27 0.206 -.2988425 .0644122 67 | -.2029004 .0827887 -2.45 0.014 -.3653702 -.0404306 70 | -.1198563 .0875448 -1.37 0.171 -.2916599 .0519473 71 | -.1157559 .089517 -1.29 0.196 -.2914297 .059918 72 | .7941027 .4247853 1.87 0.062 -.0395231 1.627729 74 | -.1742999 .0836048 -2.08 0.037 -.3383714 -.0102285 80 | .0362365 .1496316 0.24 0.809 -.2574102 .3298831 85 | .0286772 .1159837 0.25 0.805 -.1989367 .2562912 91 | -.1244881 .0830494 -1.50 0.134 -.2874695 .0384934 92 | -.0881516 .0848154 -1.04 0.299 -.2545989 .0782957 93 | -.0564046 .0892817 -0.63 0.528 -.2316168 .1188076 95 | .3256092 .105291 3.09 0.002 .1189794 .5322389 | year | 1998 | .0201024 .0071263 2.82 0.005 .0061174 .0340875 1999 | .0182901 .0088637 2.06 0.039 .0008954 .0356847 2000 | -.1527635 .011026 -13.85 0.000 -.1744016 -.1311253 2001 | -.0603148 .0085045 -7.09 0.000 -.0770046 -.043625 2002 | 0 (omitted) | gorwk | Rest of Nth East | .1130188 .0643958 1.76 0.080 -.0133556 .2393932 Greater Manchester | .0224784 .0612553 0.37 0.714 -.097733 .1426898 Merseyside | -.0005063 .0719286 -0.01 0.994 -.1416637 .1406511 Rest of Nth West | -.0687794 .058957 -1.17 0.244 -.1844804 .0469216 South Yorkshire | -.0619397 .0682396 -0.91 0.364 -.1958575 .0719782 West Yorkshire | -.0209016 .0578596 -0.36 0.718 -.134449 .0926458 Rest Ykshr & Humberside | .0320627 .0628495 0.51 0.610 -.0912771 .1554026 West Midlands & Met Country | -.0173477 .0554515 -0.31 0.754 -.1261693 .0914739 Rest of West Midlands | -.0031915 .0570302 -0.06 0.955 -.1151112 .1087282 Eastern | .0382811 .054649 0.70 0.484 -.0689657 .1455278 Inner London | -.0823723 .0621765 -1.32 0.186 -.2043915 .0396469 Outer London | .0040667 .0594446 0.07 0.945 -.1125912 .1207246 South East | .0293111 .055973 0.52 0.601 -.0805339 .1391562 South West | .0012553 .0538031 0.02 0.981 -.1043314 .106842 Wales | .0415225 .0605864 0.69 0.493 -.0773761 .1604212 Rest of Scotland | -.0058419 .0555208 -0.11 0.916 -.1147994 .1031157 Nthn Ireland | .0532132 .0669761 0.79 0.427 -.078225 .1846514 | _cons | 3.016971 .1013174 29.78 0.000 2.818139 3.215803 ---------------------------------------------------------------------------------------------- . . . * Has the minimum wage had any effect on corporate profits? . * * Log profit margin . reg net_pcm post_treat post treat if pp==1,cluster(regno) Linear regression Number of obs = 4,112 F(3, 950) = 9.81 Prob > F = 0.0000 R-squared = 0.0199 Root MSE = .15237 (Std. err. adjusted for 951 clusters in regno) ------------------------------------------------------------------------------ | Robust net_pcm | Coefficient std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- post_treat | -.0273999 .0137241 -2.00 0.046 -.054333 -.0004668 post | -.0118679 .0041968 -2.83 0.005 -.020104 -.0036318 treat | .0580316 .013659 4.25 0.000 .0312263 .0848368 _cons | .0698972 .0048096 14.53 0.000 .0604586 .0793358 ------------------------------------------------------------------------------ . . * se includiamo altre variabili dipendenti... . reg net_pcm post_treat post treat NMW grad2 unionmem ptwk female i.sic2 i.year i.gorwk if pp==1,cluster(regno) note: NMW omitted because of collinearity. note: 2002.year omitted because of collinearity. Linear regression Number of obs = 4,112 F(71, 950) = . Prob > F = . R-squared = 0.2943 Root MSE = .13046 (Std. err. adjusted for 951 clusters in regno) ---------------------------------------------------------------------------------------------- | Robust net_pcm | Coefficient std. err. t P>|t| [95% conf. interval] -----------------------------+---------------------------------------------------------------- post_treat | -.0289454 .0121353 -2.39 0.017 -.0527606 -.0051303 post | -.0119636 .0072968 -1.64 0.101 -.0262833 .0023562 treat | .0368204 .0132953 2.77 0.006 .0107288 .062912 NMW | 0 (omitted) grad2 | -.0238561 .0631265 -0.38 0.706 -.1477396 .1000274 unionmem | .115439 .0977575 1.18 0.238 -.0764066 .3072847 ptwk | -.1294503 .053951 -2.40 0.017 -.2353273 -.0235733 female | .0631261 .0512248 1.23 0.218 -.0374008 .163653 | sic2 | 5 | -.2187885 .0127806 -17.12 0.000 -.24387 -.193707 10 | -.0738286 .059216 -1.25 0.213 -.190038 .0423808 14 | -.0672375 .091611 -0.73 0.463 -.2470209 .1125458 15 | -.0199682 .0317888 -0.63 0.530 -.0823526 .0424161 17 | -.0583793 .0307329 -1.90 0.058 -.1186916 .001933 18 | -.0531366 .0397816 -1.34 0.182 -.1312066 .0249334 20 | .0153645 .0201133 0.76 0.445 -.024107 .0548361 21 | .0014435 .0422532 0.03 0.973 -.0814769 .0843638 22 | .0064535 .0363915 0.18 0.859 -.0649634 .0778705 23 | .0259704 .0512643 0.51 0.613 -.0746339 .1265747 24 | -.04265 .0379469 -1.12 0.261 -.1171194 .0318194 25 | -.024397 .0224687 -1.09 0.278 -.068491 .0196971 26 | -.0100184 .0421445 -0.24 0.812 -.0927255 .0726886 27 | -.0512774 .0449552 -1.14 0.254 -.1395004 .0369457 28 | -.0240923 .021147 -1.14 0.255 -.0655926 .017408 29 | -.025374 .0276484 -0.92 0.359 -.079633 .028885 30 | -.0848942 .0343312 -2.47 0.014 -.1522679 -.0175205 31 | -.0366194 .0316031 -1.16 0.247 -.0986393 .0254005 32 | -.0144483 .0262278 -0.55 0.582 -.0659194 .0370229 33 | -.0138588 .019783 -0.70 0.484 -.0526822 .0249647 34 | -.0960627 .0500254 -1.92 0.055 -.1942358 .0021103 35 | -.0541444 .0510353 -1.06 0.289 -.1542994 .0460106 36 | -.0026967 .0196803 -0.14 0.891 -.0413185 .0359251 40 | .2161956 .1625683 1.33 0.184 -.1028388 .53523 41 | .1840912 .064635 2.85 0.004 .0572474 .310935 45 | -.0089427 .0220469 -0.41 0.685 -.052209 .0343235 50 | -.0164829 .0116892 -1.41 0.159 -.0394225 .0064567 51 | -.0082298 .0124876 -0.66 0.510 -.0327363 .0162767 52 | .0242509 .0219012 1.11 0.268 -.0187294 .0672312 55 | .0923189 .0219446 4.21 0.000 .0492535 .1353843 60 | -.0358863 .0328247 -1.09 0.275 -.1003036 .028531 61 | .0411558 .0887408 0.46 0.643 -.1329948 .2153065 62 | -.1015586 .0650382 -1.56 0.119 -.2291936 .0260765 63 | -.0100305 .0303319 -0.33 0.741 -.0695557 .0494947 64 | .0103387 .0568713 0.18 0.856 -.1012693 .1219467 65 | .0556443 .0414208 1.34 0.179 -.0256425 .136931 66 | .0634439 .0488024 1.30 0.194 -.0323292 .1592169 67 | -.0559661 .0326205 -1.72 0.087 -.1199826 .0080504 70 | .2621033 .0561671 4.67 0.000 .1518774 .3723292 71 | .0677007 .0391029 1.73 0.084 -.0090373 .1444386 72 | -.1117122 .1242916 -0.90 0.369 -.35563 .1322056 74 | .0054855 .0233446 0.23 0.814 -.0403274 .0512984 80 | -.0634733 .0672516 -0.94 0.346 -.1954521 .0685055 85 | -.055061 .0627729 -0.88 0.381 -.1782506 .0681286 91 | -.0224707 .0294892 -0.76 0.446 -.0803421 .0354008 92 | .0189964 .0293237 0.65 0.517 -.0385503 .0765431 93 | .0325954 .0260261 1.25 0.211 -.0184798 .0836707 95 | .0744843 .0336602 2.21 0.027 .0084274 .1405412 | year | 1998 | .0083172 .0042431 1.96 0.050 -9.72e-06 .0166442 1999 | -.0036338 .0055612 -0.65 0.514 -.0145475 .0072799 2000 | .0084429 .0063027 1.34 0.181 -.0039259 .0208117 2001 | .0020354 .0053991 0.38 0.706 -.0085601 .012631 2002 | 0 (omitted) | gorwk | Rest of Nth East | -.0044754 .0277291 -0.16 0.872 -.0588927 .0499419 Greater Manchester | .0131044 .0293975 0.45 0.656 -.044587 .0707959 Merseyside | .0205962 .0304912 0.68 0.500 -.0392418 .0804341 Rest of Nth West | .0244285 .0259744 0.94 0.347 -.0265453 .0754023 South Yorkshire | .0090059 .0257918 0.35 0.727 -.0416096 .0596213 West Yorkshire | -.0212258 .0267639 -0.79 0.428 -.073749 .0312973 Rest Ykshr & Humberside | -.0114739 .039878 -0.29 0.774 -.0897331 .0667853 West Midlands & Met Country | .0256921 .0253692 1.01 0.311 -.0240941 .0754783 Rest of West Midlands | .0072005 .0276893 0.26 0.795 -.0471388 .0615397 Eastern | .0077825 .0254758 0.31 0.760 -.0422128 .0577779 Inner London | .0282619 .0322297 0.88 0.381 -.0349877 .0915116 Outer London | .0310905 .0285178 1.09 0.276 -.0248746 .0870557 South East | .0203681 .0262494 0.78 0.438 -.0311455 .0718816 South West | .0163464 .0250736 0.65 0.515 -.0328596 .0655525 Wales | .0130439 .0316288 0.41 0.680 -.0490265 .0751143 Rest of Scotland | .0140426 .0254969 0.55 0.582 -.0359942 .0640794 Nthn Ireland | .0225572 .0317088 0.71 0.477 -.0396701 .0847845 | _cons | .0180569 .0326084 0.55 0.580 -.0459358 .0820497 ---------------------------------------------------------------------------------------------- . . . ***** . * EVENT STUDY SPECIFICATION (not performed in the Draca et al. paper) . * this specification allows testing for the presence of . * "parallel trends" . . reg net_pcm i.year##i.treat if pp==1, cluster(regno) Linear regression Number of obs = 4,112 F(11, 950) = 3.98 Prob > F = 0.0000 R-squared = 0.0215 Root MSE = .15239 (Std. err. adjusted for 951 clusters in regno) ------------------------------------------------------------------------------ | Robust net_pcm | Coefficient std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- year | 1998 | .0036753 .0048508 0.76 0.449 -.0058442 .0131947 1999 | -.0094913 .0060185 -1.58 0.115 -.0213024 .0023198 2000 | -.0067129 .006691 -1.00 0.316 -.0198438 .006418 2001 | -.0173143 .0064151 -2.70 0.007 -.0299037 -.0047249 2002 | -.0203263 .0073264 -2.77 0.006 -.0347041 -.0059485 | 1.treat | .040096 .0155143 2.58 0.010 .0096498 .0705422 | year#treat | 1998 1 | .0203926 .0137357 1.48 0.138 -.0065631 .0473484 1999 1 | .0296416 .0165639 1.79 0.074 -.0028644 .0621476 2000 1 | -.0132727 .0198344 -0.67 0.504 -.052197 .0256515 2001 1 | -.0104384 .0209385 -0.50 0.618 -.0515294 .0306527 2002 1 | -.0030203 .0199008 -0.15 0.879 -.0420749 .0360342 | _cons | .0722012 .0063045 11.45 0.000 .0598288 .0845736 ------------------------------------------------------------------------------ . . * we can graph the coefficients. . * first we install this useful command to produce the graphs . ssc install coefplot, replace checking coefplot consistency and verifying not already installed... the following files will be replaced: /Users/bernardofanfani/Library/Application Support/Stata/ado/plus/c/coefplot.ado installing into /Users/bernardofanfani/Library/Application Support/Stata/ado/plus/... installation complete. . . coefplot, vertical yline(0, lcolor(red)) /// > title("Placebo and year-specific DD effects on profits") subtitle("Differenza condizionata crescita profitti ri > spetto al 1997 tra X=1 e X=0") /// > keep(1997.year#1.treat 1998.year#1.treat 1999.year#1.treat 2000.year#1.treat 2001.year#1.treat 2002.year#1.trea > t) /// > rename(1997.year#1.treat="1997" 1998.year#1.treat="1998" 1999.year#1.treat="1999" 2000.year#1.treat="2000 (post > )" 2001.year#1.treat="2001 (post)" 2002.year#1.treat="2002 (post)") . . * We also test this specification for wages. . reg ln_avwage i.year##i.treat if pp==1, cluster(regno) Linear regression Number of obs = 4,112 F(11, 950) = 115.44 Prob > F = 0.0000 R-squared = 0.5224 Root MSE = .2481 (Std. err. adjusted for 951 clusters in regno) ------------------------------------------------------------------------------ | Robust ln_avwage | Coefficient std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- year | 1998 | .0268626 .0074997 3.58 0.000 .0121448 .0415804 1999 | .037859 .0087498 4.33 0.000 .0206878 .0550301 2000 | .0874624 .0097776 8.95 0.000 .0682741 .1066507 2001 | .1514148 .0111654 13.56 0.000 .1295032 .1733264 2002 | .1995937 .0124918 15.98 0.000 .175079 .2241085 | 1.treat | -.5984525 .0313003 -19.12 0.000 -.6598782 -.5370268 | year#treat | 1998 1 | -.0222472 .0222664 -1.00 0.318 -.0659443 .0214499 1999 1 | -.0525236 .0258848 -2.03 0.043 -.1033216 -.0017255 2000 1 | -.0139055 .0321543 -0.43 0.666 -.0770072 .0491961 2001 1 | .1096799 .0431278 2.54 0.011 .0250431 .1943166 2002 1 | .1797789 .0468814 3.83 0.000 .0877759 .271782 | _cons | 2.751994 .0097155 283.26 0.000 2.732928 2.77106 ------------------------------------------------------------------------------ . . coefplot, vertical yline(0, lcolor(red)) /// > title("Placebo and year-specific DD effects on average wages") /// > keep(1997.year#1.treat 1998.year#1.treat 1999.year#1.treat 2000.year#1.treat 2001.year#1.treat 2002.year#1.trea > t) /// > rename(1997.year#1.treat="1997" 1998.year#1.treat="1998" 1999.year#1.treat="1999" 2000.year#1.treat="2000 (post > )" 2001.year#1.treat="2001 (post)" 2002.year#1.treat="2002 (post)") . . . *** TABLE 3: PLACEBO EXPERIMENT FOR WAGES AND PROFITS (this is included in the Draca et al. paper) . **Placebo Policy: ff = 1 if 1/4/1993-31/3/1996 (pre-placebo policy) or 1/4/1996-31/3/1999 (post-placebo policy) . . * Treatment group for placebo . gen plactreat = 1 if avwage<=12 & year==1996 (20,502 missing values generated) . replace plactreat = 0 if avwage>12 & avwage <= 20 & year==1999 (754 real changes made) . sort regno plactreat . by regno: replace plactreat = plactreat[1] (5,768 real changes made) . . * After Policy Dummy . gen placpost = 1 if year >= 1997 & year <= 1999 (13,784 missing values generated) . replace placpost = 0 if year < 1997 (6,200 real changes made) . . * Interaction . gen placpost_treat = plactreat * placpost (16,199 missing values generated) . . * net profits . reg net_pcm placpost_treat placpost plactreat,cluster(regno) Linear regression Number of obs = 4,689 F(3, 1087) = 0.92 Prob > F = 0.4315 R-squared = 0.0008 Root MSE = 5.5326 (Std. err. adjusted for 1,088 clusters in regno) -------------------------------------------------------------------------------- | Robust net_pcm | Coefficient std. err. t P>|t| [95% conf. interval] ---------------+---------------------------------------------------------------- placpost_treat | .2760885 .4393673 0.63 0.530 -.5860155 1.138192 placpost | .1161078 .0898231 1.29 0.196 -.0601384 .2923541 plactreat | -.3337987 .4310618 -0.77 0.439 -1.179606 .5120088 _cons | .0411154 .0439367 0.94 0.350 -.045095 .1273258 -------------------------------------------------------------------------------- . reg net_pcm placpost_treat placpost plactreat NMW grad2 unionmem ptwk female i.sic2 i.year i.gorwk,cluster(reg > no) note: NMW omitted because of collinearity. note: 1999.year omitted because of collinearity. Linear regression Number of obs = 4,670 F(74, 1081) = . Prob > F = . R-squared = 0.0561 Root MSE = 5.4346 (Std. err. adjusted for 1,082 clusters in regno) ---------------------------------------------------------------------------------------------- | Robust net_pcm | Coefficient std. err. t P>|t| [95% conf. interval] -----------------------------+---------------------------------------------------------------- placpost_treat | .2513195 .4559719 0.55 0.582 -.6433706 1.14601 placpost | .6570616 .5100248 1.29 0.198 -.3436892 1.657812 plactreat | -.3590823 .3565291 -1.01 0.314 -1.05865 .3404852 NMW | 0 (omitted) grad2 | 2.841097 1.766012 1.61 0.108 -.6241013 6.306296 unionmem | 3.162278 2.439767 1.30 0.195 -1.624937 7.949493 ptwk | -.9892233 1.113671 -0.89 0.375 -3.174425 1.195978 female | .5789898 .550581 1.05 0.293 -.5013387 1.659318 | sic2 | 5 | .1739014 .3732938 0.47 0.641 -.5585611 .9063639 10 | -1.919327 1.60636 -1.19 0.232 -5.071264 1.232611 14 | -21.00767 15.03126 -1.40 0.163 -50.50142 8.486078 15 | -1.133035 .866558 -1.31 0.191 -2.833361 .5672916 16 | -1.66638 1.406757 -1.18 0.236 -4.426665 1.093904 17 | -1.093279 .8142376 -1.34 0.180 -2.690944 .5043858 18 | -.5743096 .6201476 -0.93 0.355 -1.791139 .6425197 19 | -.1881168 .5370662 -0.35 0.726 -1.241927 .8656936 20 | .0580392 .3445504 0.17 0.866 -.6180241 .7341025 21 | -1.28987 1.014936 -1.27 0.204 -3.281337 .701597 22 | -1.064565 .755586 -1.41 0.159 -2.547147 .4180161 23 | -.9327068 .8318537 -1.12 0.262 -2.564938 .699524 24 | -1.348903 .9605146 -1.40 0.161 -3.233587 .5357816 25 | -.5993299 .526436 -1.14 0.255 -1.632282 .4336223 26 | -1.249371 1.01068 -1.24 0.217 -3.232487 .7337453 27 | -1.41172 1.202832 -1.17 0.241 -3.771869 .9484287 28 | -.5835358 .5516836 -1.06 0.290 -1.666028 .4989562 29 | -1.131028 .871338 -1.30 0.195 -2.840734 .5786772 30 | -1.3491 .9073475 -1.49 0.137 -3.129462 .4312616 31 | -.8557554 .6543473 -1.31 0.191 -2.13969 .4281793 32 | -.8106254 .6191315 -1.31 0.191 -2.025461 .4042103 33 | -.5848116 .4861141 -1.20 0.229 -1.538646 .3690226 34 | -1.65249 1.279799 -1.29 0.197 -4.163661 .8586806 35 | -1.926941 1.466166 -1.31 0.189 -4.803795 .9499121 36 | -.3141423 .4169392 -0.75 0.451 -1.132244 .5039596 37 | -.3296915 .5963836 -0.55 0.581 -1.499892 .8405091 40 | -2.170888 1.795473 -1.21 0.227 -5.693895 1.352119 41 | -1.613423 1.405314 -1.15 0.251 -4.370875 1.14403 45 | -1.021338 .6715309 -1.52 0.129 -2.33899 .2963136 50 | .1047994 .3370195 0.31 0.756 -.5564871 .7660859 51 | -.1453198 .310994 -0.47 0.640 -.7555401 .4649006 52 | .0908433 .562918 0.16 0.872 -1.013692 1.195379 55 | .6105987 .7454018 0.82 0.413 -.8519995 2.073197 60 | -1.409632 1.099586 -1.28 0.200 -3.567196 .7479317 61 | -4.259234 3.09907 -1.37 0.170 -10.34011 1.82164 62 | -1.732492 1.449342 -1.20 0.232 -4.576334 1.111349 63 | -.6417498 .6195342 -1.04 0.300 -1.857376 .5738761 64 | -1.676873 1.39342 -1.20 0.229 -4.410986 1.057241 65 | -.8250928 .655961 -1.26 0.209 -2.112194 .4620081 66 | -1.350216 .9482097 -1.42 0.155 -3.210756 .510324 67 | -.8936143 .611088 -1.46 0.144 -2.092667 .3054387 70 | -.6850962 .9428385 -0.73 0.468 -2.535097 1.164905 71 | .0923105 .3243886 0.28 0.776 -.5441921 .7288131 72 | -1.854901 .9564303 -1.94 0.053 -3.731572 .0217688 73 | -4.500064 2.2064 -2.04 0.042 -8.829375 -.170752 74 | -.4918305 .4236039 -1.16 0.246 -1.323009 .3393486 75 | -2.07342 1.504333 -1.38 0.168 -5.025164 .8783239 80 | -2.666799 1.55477 -1.72 0.087 -5.717507 .3839095 85 | -1.412958 .9595379 -1.47 0.141 -3.295726 .4698093 90 | -1.99901 1.566432 -1.28 0.202 -5.072602 1.074582 91 | -.5569832 .4855957 -1.15 0.252 -1.5098 .3958336 92 | -.7576717 .5202941 -1.46 0.146 -1.778573 .2632291 93 | .1404155 .5210506 0.27 0.788 -.8819696 1.162801 95 | .946743 1.248137 0.76 0.448 -1.502304 3.39579 | year | 1995 | .7139141 .5778204 1.24 0.217 -.4198625 1.847691 1996 | .7089113 .5924046 1.20 0.232 -.4534819 1.871305 1997 | -.021546 .0568218 -0.38 0.705 -.1330396 .0899476 1998 | .2007 .1937673 1.04 0.301 -.1795026 .5809025 1999 | 0 (omitted) | gorwk | Rest of Nth East | .0636853 .1417957 0.45 0.653 -.2145408 .3419114 Greater Manchester | .0949402 .1068673 0.89 0.375 -.1147507 .304631 Merseyside | .0288415 .1000967 0.29 0.773 -.1675643 .2252474 Rest of Nth West | .0402402 .1020739 0.39 0.693 -.1600451 .2405255 South Yorkshire | -.0797731 .1757773 -0.45 0.650 -.4246763 .2651302 West Yorkshire | -.0199 .1060337 -0.19 0.851 -.2279552 .1881552 Rest Ykshr & Humberside | .1186779 .1936551 0.61 0.540 -.2613045 .4986603 West Midlands & Met Country | .0389489 .097535 0.40 0.690 -.1524304 .2303282 Rest of West Midlands | .1091201 .1141838 0.96 0.339 -.114927 .3331671 Eastern | .1427855 .1081226 1.32 0.187 -.0693684 .3549394 Inner London | -.7320955 .7351839 -1.00 0.320 -2.174645 .7104535 Outer London | -.1001944 .2484413 -0.40 0.687 -.5876763 .3872875 South East | -.063227 .1011291 -0.63 0.532 -.2616586 .1352046 South West | .0096339 .0927826 0.10 0.917 -.1724206 .1916884 Wales | .1281834 .1178262 1.09 0.277 -.1030106 .3593773 Rest of Scotland | .1325245 .0979548 1.35 0.176 -.0596786 .3247276 Nthn Ireland | 3.067261 2.329671 1.32 0.188 -1.503927 7.63845 | _cons | -.9634348 .7247108 -1.33 0.184 -2.385434 .4585645 ---------------------------------------------------------------------------------------------- . . . * Log Wages . reg ln_avwage placpost_treat placpost plactreat,cluster(regno) Linear regression Number of obs = 4,661 F(3, 1087) = 208.75 Prob > F = 0.0000 R-squared = 0.3484 Root MSE = .43819 (Std. err. adjusted for 1,088 clusters in regno) -------------------------------------------------------------------------------- | Robust ln_avwage | Coefficient std. err. t P>|t| [95% conf. interval] ---------------+---------------------------------------------------------------- placpost_treat | .056702 .0409242 1.39 0.166 -.0235974 .1370015 placpost | .1027403 .0097878 10.50 0.000 .0835352 .1219453 plactreat | -.6951566 .0361213 -19.25 0.000 -.766032 -.6242812 _cons | 2.660453 .0112699 236.07 0.000 2.638339 2.682566 -------------------------------------------------------------------------------- . reg ln_avwage placpost_treat placpost plactreat NMW grad2 unionmem ptwk female i.sic2 i.year i.gorwk,cluster(re > gno) note: NMW omitted because of collinearity. note: 1999.year omitted because of collinearity. Linear regression Number of obs = 4,642 F(74, 1081) = . Prob > F = . R-squared = 0.4725 Root MSE = .39837 (Std. err. adjusted for 1,082 clusters in regno) ---------------------------------------------------------------------------------------------- | Robust ln_avwage | Coefficient std. err. t P>|t| [95% conf. interval] -----------------------------+---------------------------------------------------------------- placpost_treat | .0681268 .0399162 1.71 0.088 -.0101951 .1464488 placpost | .1564608 .0185115 8.45 0.000 .1201383 .1927833 plactreat | -.6441639 .0342062 -18.83 0.000 -.711282 -.5770459 NMW | 0 (omitted) grad2 | .0314979 .3706552 0.08 0.932 -.6957872 .758783 unionmem | -.2217231 .1640801 -1.35 0.177 -.5436746 .1002284 ptwk | -1.001246 .1964839 -5.10 0.000 -1.386779 -.615713 female | .0400731 .143556 0.28 0.780 -.241607 .3217531 | sic2 | 5 | 1.57009 .5796541 2.71 0.007 .4327157 2.707465 10 | 1.783029 .5874636 3.04 0.002 .6303311 2.935728 14 | .825274 .8618233 0.96 0.338 -.8657619 2.51631 15 | 1.745439 .5858141 2.98 0.003 .5959779 2.894901 16 | 1.315117 .5856797 2.25 0.025 .1659194 2.464315 17 | 1.742382 .5848361 2.98 0.003 .5948397 2.889925 18 | 1.734653 .5878851 2.95 0.003 .5811274 2.888178 19 | 1.58367 .6075026 2.61 0.009 .3916519 2.775688 20 | 1.682046 .5822577 2.89 0.004 .5395631 2.82453 21 | 1.783835 .5866154 3.04 0.002 .6328015 2.934869 22 | 1.656482 .5922308 2.80 0.005 .4944297 2.818534 23 | 1.772484 .5997252 2.96 0.003 .5957268 2.949241 24 | 1.692621 .5981203 2.83 0.005 .519013 2.866229 25 | 1.710322 .5871311 2.91 0.004 .5582768 2.862368 26 | 1.768305 .587405 3.01 0.003 .6157223 2.920889 27 | 1.783175 .5868635 3.04 0.002 .6316541 2.934695 28 | 1.734177 .5818539 2.98 0.003 .5924864 2.875868 29 | 1.731935 .5858411 2.96 0.003 .5824208 2.88145 30 | 1.576632 .6244556 2.52 0.012 .3513491 2.801914 31 | 1.727682 .5884661 2.94 0.003 .5730166 2.882347 32 | 1.664528 .589075 2.83 0.005 .5086676 2.820388 33 | 1.675638 .5911445 2.83 0.005 .5157174 2.835559 34 | 1.6494 .5823747 2.83 0.005 .5066868 2.792112 35 | 1.812356 .5967942 3.04 0.002 .6413501 2.983362 36 | 1.73185 .5837769 2.97 0.003 .5863863 2.877315 37 | 1.613485 .5792555 2.79 0.005 .476892 2.750077 40 | 1.92165 .6609487 2.91 0.004 .6247619 3.218537 41 | 1.960814 .5937088 3.30 0.001 .7958618 3.125766 45 | 1.690202 .5847832 2.89 0.004 .5427636 2.837641 50 | 1.757137 .5795564 3.03 0.002 .619954 2.89432 51 | 1.724257 .5829695 2.96 0.003 .5803772 2.868137 52 | 2.049306 .588259 3.48 0.001 .8950475 3.203565 55 | 1.950641 .5844071 3.34 0.001 .8039401 3.097341 60 | 1.725078 .5832466 2.96 0.003 .580654 2.869501 61 | 1.60173 .5990875 2.67 0.008 .4262237 2.777236 62 | 1.903058 .5895656 3.23 0.001 .7462356 3.059881 63 | 1.636446 .5874145 2.79 0.005 .4838438 2.789047 64 | 1.766305 .596671 2.96 0.003 .5955409 2.93707 65 | 1.917332 .5930314 3.23 0.001 .7537087 3.080955 66 | 1.618686 .5980327 2.71 0.007 .4452491 2.792122 67 | 1.715194 .5898046 2.91 0.004 .557902 2.872485 70 | 1.755469 .5983105 2.93 0.003 .5814876 2.92945 71 | 1.837976 .587006 3.13 0.002 .6861758 2.989776 72 | 2.058628 .6112974 3.37 0.001 .8591642 3.258092 73 | 2.238396 .7205814 3.11 0.002 .8244989 3.652292 74 | 1.724547 .5989472 2.88 0.004 .5493165 2.899778 75 | 2.015298 .5940631 3.39 0.001 .8496508 3.180946 80 | 1.902622 .6361432 2.99 0.003 .6544066 3.150837 85 | 2.027149 .6032977 3.36 0.001 .8433822 3.210916 90 | 1.908895 .5991309 3.19 0.001 .7333036 3.084486 91 | 2.089869 .6125735 3.41 0.001 .8879014 3.291837 92 | 1.822326 .5935708 3.07 0.002 .6576448 2.987008 93 | 1.861167 .5871063 3.17 0.002 .7091705 3.013164 95 | 2.494492 .6042774 4.13 0.000 1.308803 3.680182 | year | 1995 | .0273707 .0158673 1.72 0.085 -.0037636 .0585049 1996 | .0316121 .0172428 1.83 0.067 -.0022212 .0654453 1997 | -.0575883 .013493 -4.27 0.000 -.0840637 -.0311128 1998 | -.0331465 .0123433 -2.69 0.007 -.057366 -.008927 1999 | 0 (omitted) | gorwk | Rest of Nth East | .0879321 .0914471 0.96 0.336 -.0915019 .267366 Greater Manchester | .0917497 .0914841 1.00 0.316 -.0877568 .2712561 Merseyside | -.0084806 .0989665 -0.09 0.932 -.2026687 .1857076 Rest of Nth West | -.0912725 .0858302 -1.06 0.288 -.2596851 .0771401 South Yorkshire | -.0713055 .1020164 -0.70 0.485 -.2714781 .1288672 West Yorkshire | -.0334245 .0892161 -0.37 0.708 -.2084809 .1416319 Rest Ykshr & Humberside | .0693911 .0908781 0.76 0.445 -.1089264 .2477086 West Midlands & Met Country | .0001044 .0839926 0.00 0.999 -.1647026 .1649115 Rest of West Midlands | .0327883 .085799 0.38 0.702 -.135563 .2011397 Eastern | .0668563 .0852623 0.78 0.433 -.100442 .2341545 Inner London | -.1096498 .1272996 -0.86 0.389 -.3594321 .1401326 Outer London | .0551959 .091116 0.61 0.545 -.1235883 .2339801 South East | -.0338886 .0920023 -0.37 0.713 -.214412 .1466348 South West | .015662 .0836545 0.19 0.852 -.1484816 .1798056 Wales | .0418473 .0879524 0.48 0.634 -.1307294 .2144241 Rest of Scotland | .0317548 .0867287 0.37 0.714 -.1384209 .2019306 Nthn Ireland | .1910394 .1444506 1.32 0.186 -.0923958 .4744747 | _cons | 1.075238 .5841929 1.84 0.066 -.0710423 2.221519 ---------------------------------------------------------------------------------------------- . . . cap log close