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| cd "${mainpath}"
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| use D_all_data, clear
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| replace val = val/(10^9)
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| sort hts10 modate
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| preserve
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| gen pre = 1 if year<2018
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| replace pre=0 if pre!=1
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| keep if (pre==1 | year==2021) & target_ever301==1
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| egen count_year = tag(year pre action301)
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| egen count_affected = tag(hts10 pre)
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| gen val_duty = val*duty301_scaled
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| collapse (sum) val val_duty count_affected count_year, by(pre action301)
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| gen duty = 100*val_duty/val
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| replace val = val/count_year
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| drop val_duty count_year
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| reshape wide val count_affected duty, i(action301) j(pre)
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| keep action301 val1 count_affected1 val0 duty0
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| order action301 count_affected1 duty0 val1 val0
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| export excel using Results\data_description_301.xlsx, sheet("tariff_coverage") sheetmodify firstrow(variables)
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| restore
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| preserve
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| gen hts10_affected = 1 if action301!="" & action301!="99038816"
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| keep if hts10_affected==1
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| gen china = 0
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| replace china = 1 if ctryname=="China"
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| collapse (sum) val, by(year china)
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| reshape wide val, i(china) j(year)
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| export excel using Results\data_description_301.xlsx, sheet("annual_imports") sheetmodify firstrow(variables)
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| restore
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| preserve
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| gen mtype = 0
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| replace mtype=1 if ctryname=="China"
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| replace mtype=2 if ctryname=="China" & target_current301==1
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| collapse (sum) val, by(modate mtype)
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| reshape wide val, i(modate) j(mtype)
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| label var val0 "Rest of world"
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| label var val1 "China nonsubject"
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| label var val2 "China subject"
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| export excel using Results\data_description_301.xlsx, sheet("fig_imports") sheetmodify firstrow(varlabels)
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| restore
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| preserve
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| gen china = 0
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| replace china=1 if ctryname=="China"
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| gen hts10_affected = 1 if action301!="" & action301!="99038816"
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| keep if hts10_affected==1 & !missing(p)
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| egen first_tag = tag(hts10 ctryname)
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| gen normp_set1 = p*first_tag
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| egen normp_set2 = max(normp_set1), by(hts10 ctryname)
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| gen normp = 100*p/normp_set2
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| gen normpduty = normp*(1+duty301_scaled)
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| by modate, sort: egen plo = pctile(normp), p(5)
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| by modate, sort: egen phi = pctile(normp), p(95)
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| keep if inrange(normp, plo, phi)
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| replace normp = normp*q1
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| replace normpduty = normpduty*q1
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| collapse (sum) q1 normp normpduty, by(modate china)
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| replace normp = normp/q1
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| replace normpduty = normpduty/q1
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| drop q1
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| reshape wide normp normpduty, i(modate) j(china)
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| drop normpduty0
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| label var normp0 "Rest of world"
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| label var normp1 "China not including tariff"
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| label var normpduty1 "China including tariff"
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| export excel using Results\data_description_301.xlsx, sheet("fig_auv") sheetmodify firstrow(varlabels)
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| restore
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| gen topsector = 0
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| foreach n in "3152" "3344" "3341" "3371" "3363" "3359" "3399" "3343" "3339" "3261" {
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| replace topsector=1 if naics4=="`n'"
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| }
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| keep if topsector==1
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| preserve
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| keep if ctryname=="China"
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| merge m:1 naics4 using D_naics4_descriptions, nogen keep(3)
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| replace naics4_description = proper(naics4_description)
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| gen val_affected = val*target_ever301
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| gen val_duties = val*duty301_scaled
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| collapse (sum) val_affected val val_duties (first) naics4_description, by(year naics4)
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| gen duties = val_duties/val
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| drop val_duties
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| gen tar_set = duties if year==2020
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| egen tar = max(tar_set), by(naics4)
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| replace tar = 100*tar
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| drop tar_set duties
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| keep if year==2017 | year==2016
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| collapse (sum) val_affected val (mean) tar (first) naics4_description, by(naics4)
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| replace val_affected = val_affected/2
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| replace val = val/2
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|
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| order naics4 naics4_description val_affected val tar
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| gsort -val_affected
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| label var naics4 "NAICS"
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| label var naics4_description "Description"
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| label var val_affected "Value of affected imports (\$B)"
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| label var val "Value of all imports (\$B)"
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| label var tar "Average tariff in 2020"
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| export excel using Results\data_description_301.xlsx, sheet("top_sectors") sheetmodify firstrow(varlabels)
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| restore
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| levelsof naics4, local(sectors)
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| foreach n of local sectors {
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| preserve
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| keep if naics4=="`n'"
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| gen mtype = 0
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| replace mtype=1 if ctryname=="China"
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| replace mtype=2 if ctryname=="China" & target_current301==1
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| collapse (sum) val, by(modate mtype)
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| reshape wide val, i(modate) j(mtype)
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| label var val0 "Other"
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| label var val1 "China nonsubject"
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| label var val2 "China subject"
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| export excel using Results\fig_imports_301.xlsx, sheet("imports_`n'") sheetmodify firstrow(varlabels)
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| restore
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| }
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| preserve
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| collapse (sum) val, by(ctryname naics4)
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| egen source_rank=rank(-val) if ctryname!="China", by(naics4)
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| gen source_top=ctryname if source_rank<=3 | ctryname=="China"
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| replace source_top = "ROW" if source_top==""
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| replace source_rank = 0 if source_top=="China"
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| replace source_rank = 4 if source_top=="ROW"
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| collapse (sum) val, by(naics4 source_top source_rank)
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| sort naics4 source_rank
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| reshape wide source_top val, i(naics4) j(source_rank)
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| export excel using Results\data_description_301.xlsx, sheet("tab_top_sources") sheetmodify firstrow(varlabels)
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| restore
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| preserve
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| import excel "D_GO_by_NAICS.xlsx", sheet("GO_by_NAICS") firstrow case(lower) clear
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| rename (d e f g h i) (val2016 val2017 val2018 val2019 val2020 val2021)
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| rename naicscode naics4
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| replace naics4 = substr(naics4,1,4)
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| collapse (sum) val2016 val2017 val2018 val2019 val2020 val2021, by(naics4)
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| reshape long val, i(naics4) j(year)
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| replace val = val/(10^3)
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| replace naics4="3152" if naics4=="3150"
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| replace naics4="3162" if naics4=="3160"
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| tempfile dom_data
|
| save `dom_data', replace
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|
|
| import excel "D_price_indices.xlsx", sheet("BLS PPI") firstrow case(lower) clear
|
| rename annual* plevel*
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| drop plevel2022
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| reshape long plevel, i(naics4) j(year)
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| tostring naics4, replace
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| merge 1:1 naics4 year using `dom_data', keep(3) nogen
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| gen source="United States"
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| reshape wide val plevel, i(naics4 source) j(year)
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| save `dom_data', replace
|
| restore
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|
|
| gen source=ctryname
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| drop if year>=2022
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| replace source="Rest of world" if source!="United States" & source!="China"
|
| collapse (sum) val q1, by(hts10 naics4 year source)
|
| gen p = val/q1
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| egen first_tag = tag(hts10 source)
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| gen normp_set1 = p*first_tag
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| egen normp_set2 = max(normp_set1), by(hts10 source)
|
| gen normp = 100*p/normp_set2
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| gen normval = val*(q1!=.)
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|
|
| replace normp = normp*normval
|
| collapse (sum) val normval normp, by(naics4 year source)
|
| replace normp = normp/normval
|
| drop normval
|
| rename normp plevel
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|
|
| reshape wide val plevel, i(naics4 source) j(year)
|
| append using `dom_data'
|
|
|
| forvalues yy=21(-1)16 {
|
|
|
| replace plevel20`yy' = 100*plevel20`yy'/plevel2016
|
| }
|
|
|
|
|
|
|
|
|
|
|
| levelsof naics4, local(sectors)
|
| foreach n of local sectors {
|
| preserve
|
| keep if naics4=="`n'"
|
| drop plevel*
|
| gen mtype = 0 if source=="China"
|
| replace mtype = 1 if source=="United States"
|
| replace mtype = 2 if source=="Rest of world"
|
| gsort mtype
|
| drop mtype
|
| export excel using Results\sector_subsections_imports.xlsx, sheet("imports_`n'") sheetmodify firstrow(varlabels) keepcellfmt
|
| restore
|
| }
|
|
|
|
|
|
|
|
|
|
|
| levelsof naics4, local(sectors)
|
| foreach n of local sectors {
|
| preserve
|
| keep if naics4=="`n'"
|
| drop val*
|
| gen mtype = 0 if source=="China"
|
| replace mtype = 1 if source=="United States"
|
| replace mtype = 2 if source=="Rest of world"
|
| gsort mtype
|
| drop mtype
|
| export excel using Results\sector_subsections_auv.xlsx, sheet("auv_`n'") sheetmodify firstrow(varlabels) keepcellfmt
|
| restore
|
| } |
