# delimit; set more off; clear; log using table7_14growing.log, replace; use data00; drop populati; gen violent_a=violent_; drop violent_; keep if age <=23 & sex!=3; sort year dep_ocu age sex; save one, replace; use pop_sex; keep if year<=2000; sort year dep_ocu age sex; save pop, replace; use one; merge year dep_ocu age sex using pop; if population!=0 { replace death=0 if death==.; replace violent_a=0 if violent_a==.; replace disease=0 if disease==.; replace homicide=0 if homicide==.; replace accident=0 if accident==.; }; gen newage=(age-7)*5; ***keep only males aged 15-59, according to the SAS file - double check the age filter here!; keep if newage>=15 & newage<=60; keep if sex==1; replace newage=15 if newage==20; replace newage=25 if newage==30; replace newage=35 if newage==40; replace newage=45 if newage==50; replace newage=55 if newage==60; ****************************************** ***generate growing department definitions ***NOTE: uncomment line at end if you want a 14 dept. definition of growing rather than a 9 dept.; gen grow94=1 if dep_ocu==13 | dep_ocu==18 | dep_ocu==19 | dep_ocu==50 | dep_ocu==52 | dep_ocu==86 | dep_ocu==95 | dep_ocu==97 | dep_ocu==99; replace grow94=0 if grow94==.; gen plante94=1 if grow94==1 | dep_ocu==20 | dep_ocu==54 | dep_ocu==94; replace plante94=0 if plante94==.; gen plante94p=1 if plante94==1 | dep_ocu==44 | dep_ocu==47; replace plante94p=0 if plante94p==.; *** (*) LINE BELOW IS FOR 14 DEPT. DEFINITION OF GROWING RATHER THAN 9; replace grow94=plante94p; gen DMZ=1 if dep_ocu==50 | dep_ocu==18; replace DMZ=0 if DMZ==.; gen prov_type="Non-growing" if grow94==0; replace prov_type="Growing" if grow94==1; replace prov_type="DMZ" if grow94==1 & DMZ==1; drop _merge; save temp, replace; ***the following creates dept_cat, a set linking dept. numbers with growing and DMZ status, and prov_type; keep dep_ocu DMZ grow94; collapse grow94 DMZ, by(dep_ocu); gen prov_type="Non-growing" if grow94==0; replace prov_type="Growing" if grow94==1; replace prov_type="DMZ" if grow==1 & DMZ==1; sort dep_ocu; save dept_cat, replace; **************************************************; ******************************************************** ****collapsing to sum across groups and categories******; use temp; collapse (sum) death violent_a accident disease homicide population, by(year dep_ocu newage); sort dep_ocu ; save temp1, replace; use temp; collapse (sum) violent if violent!=., by(year dep_ocu newage); sort year dep_ocu newage ; save temp2, replace; use temp1; merge dep_ocu using dept_cat; drop _merge; sort year dep_ocu newage ; merge year dep_ocu newage using temp2; ********************************************************; ********************************************************; gen arate=100000*(accident/population); gen vrate=100000*(violent_a/population); gen drate=100000*(disease/population); gen hrate=100000*(homicide/population); gen lnvrate=log(violent_a/population) if violent_a>0; gen lnvratio=log(violent_a/(death-violent_a)) if violent_a>0 & violent_a0; gen post=1 if year>=1995; replace post=0 if year<1995; gen d9597=1 if year<=1997 & year>=1995; replace d9597=0 if d9597==.; gen d9800=1 if year<=2000 & year>=1998; replace d9800=0 if d9800==.; gen negyear94=-year if year>=1994; replace negyear94=0 if year<1994; gen negyear93=-year if year>=1993; replace negyear93=0 if year<1993; gen growing=1 if prov_type=="Growing"; replace growing=0 if growing==.; gen trend=year-1989; gen bigcity=1 if dep_ocu==5 | dep_ocu==11 | dep_ocu==76; replace bigcity=0 if bigcity==.; keep if bigcity==0; gen clusterid=dep_ocu+(year/100); label variable lnvratio "logit violent death rate"; label variable vrate "violent death rate"; label variable drate "disease death rate"; label variable DMZ "Meta or Cauqeta"; ************************************************** **** Generate all the dummy variables ****; ***interaction variables***; gen growing_negyear93=growing*negyear93; gen DMZ_negyear93=DMZ*negyear93; gen growing_negyear94=growing*negyear94; gen DMZ_negyear94=DMZ*negyear94; ***year, department, age dummies***; separate year, by(year); separate dep_ocu, by(dep_ocu); separate newage, by(newage); drop year2000 newage55 dep_ocu99; recode year1990-newage45 (nonmiss=1) (missing=0); ***transform interaction variables into a set of dummies***; local i=1993; while `i'<=2000 {; gen growing_negyear93_`i'=1 if growing_negyear93==-`i'; replace growing_negyear93_`i'=0 if growing_negyear93_`i'==.; gen DMZ_negyear93_`i'=1 if DMZ_negyear93==-`i'; replace DMZ_negyear93_`i'=0 if DMZ_negyear93_`i'==.; local i=`i'+1; }; local j=1994; while `j'<=2000 {; gen growing_negyear94_`j'=1 if growing_negyear94==-`j'; replace growing_negyear94_`j'=0 if growing_negyear94_`j'==.; gen DMZ_negyear94_`j'=1 if DMZ_negyear94==-`j'; replace DMZ_negyear94_`j'=0 if DMZ_negyear94_`j'==.; local j=`j'+1; }; ***generate trend terms***; gen growing_trend=trend if prov_type=="Growing"; gen non_growing_trend=trend if prov_type=="Non-growing"; gen DMZ_trend=trend if prov_type=="DMZ"; recode growing_trend-DMZ_trend (missing=0); ***Note that the st. errors for the regressions are slightly different than those reported in the paper, ***since SAS and Stata must calculate st. errors differently when clustering; **************************************************; ***** data summary *****; **************************************************; summarize; **************************************************; ***** empirical model -- unweighted *****; **************************************************; reg lnvrate dep_ocu8-dep_ocu97 year1990-year1999 newage15-newage45 growing_negyear93_1993-DMZ_negyear93_2000, cluster(clusterid); **************************************************; ***** empirical model -- weighted *****; **************************************************; reg lnvrate dep_ocu8-dep_ocu97 year1990-year1999 newage15-newage45 growing_negyear93_1993-DMZ_negyear93_2000 [pweight=population], cluster(clusterid); **************************************************; *****empirical model - unweighted -- w/trends*****; **************************************************; reg lnvrate dep_ocu8-dep_ocu97 year1990-year1999 newage15-newage45 growing_negyear94_1994-DMZ_negyear94_2000 growing_trend DMZ_trend , cluster(clusterid); **************************************************; *****empirical model - weighted -- w/trends *****; **************************************************; reg lnvrate dep_ocu8-dep_ocu97 year1990-year1999 newage15-newage45 growing_negyear94_1994-DMZ_negyear94_2000 growing_trend DMZ_trend [pweight=population], cluster(clusterid); erase one.dta; erase pop.dta; erase temp.dta; erase temp1.dta; erase temp2.dta; erase dept_cat.dta; log close;