************************************************************* *Purpose: Merge context data and generate additional vars *Stata Version: 16 ************************************************************* *------------------------------- *generate merged_context_1.dta *------------------------------- use "source_data/unemployment.dta", clear *unemployment gendergap *---------------------- gen unemp_gendergap = unemp_men/unemp_female label var unemp_gendergap "male unemployment rate / female unemployment rate" rename ags_dist ags_county // "county" and "district" used as synonyms label var ags_c " Identifier for County" save "source_data/merged_context_1.dta",replace *----------------------------- *generate merged_context_2.dta *----------------------------- *unemployment data *------------------- use "source_data/unemployment.dta", clear gen unemp_gendergap = unemp_men/unemp_female label var unemp_gendergap "male unemployment rate / female unemployment rate" save "source_data/temp1.dta", replace *refugees by gender *------------------- use "source_data/refugee_gender.dta", clear egen ref_male = rowtotal(all_male0_3 all_male3_6 all_male6_15 all_male15_18 all_male18_25 all_male25_30 all_male30_40 all_male40_50 all_male50_65 all_male65_75 all_male75_up) gen pc_ref_male = ref_male*100/all_totref label var pc_ref_male "% male refugees, of all refugees" label var ref_male "total number of male refugees (all ages)" save "source_data/temp2.dta", replace *education *---------- use "source_data/education.dta", clear *high degree gen pc_hidegree_all2011 = pop15_high_degree*100/pop15_total label var pc_hidegree_all2011 "% population with university entrance exam, incl. still in school" // (census 2011) save "source_data/temp3.dta", replace * sector *-------- use "source_data/sectors.dta", clear gen pc_manufacturing = no_manufacturing/no_employed label var pc_manufacturing "pc_manufacturing" save "source_data/temp4.dta", replace *merge data *---------- /* this is a more comprehensive dataset - start by using a master data file that includes the ags year combinations we need */ use "source_data/population.dta" merge 1:1 ags year using "source_data/temp1.dta" // unemployment drop _m merge 1:1 ags year using "source_data/temp2.dta" // refugees drop _m merge m:1 ags using "source_data/temp3.dta" // education in 2011 this m:1 merge drop _m merge 1:1 ags year using "source_data/temp4.dta" //sectors drop _m rename ags_dist ags_county // "county" and "district" used as synonyms label var ags_c " Identifier for County" save "source_data/merged_context_2.dta",replace erase "source_data/temp1.dta" erase "source_data/temp2.dta" erase "source_data/temp3.dta" erase "source_data/temp4.dta"