* Replication of Table 3.4, Age at First Marriage, in the India 1998-99 DHS (NFHS-2) 

set more off
use "C:\Users\26216\ICF\Analysis - Shared Resources\Data\DHSdata\IAIR42FL.dta" , clear

log using e:\DHS\programs\age_at_first_marriage\age_at_first_marriage_NFHS-2_do_6June2018, replace

drop if v024==35
numlabel,add
tab v503,m

gen afm=.
replace afm=s114 if v503==1
replace afm=s111 if v503==2

* everyone should have an afm that is less than or equal to their current age
replace afm=. if afm>v012

svyset v021 [pweight=v005], strata(v022) singleunit(centered)


gen awfactt_100=awfactt/100
gen awfactu_100=awfactu/100


* Begin a loop through all six cutoff ages (columns of the table)

local cutoff_age 13 15 18 20 22 25
foreach lage of local cutoff_age {

  scalar cutoff_age=`lage'
  if cutoff_age==13 | cutoff_age==15 {
  scalar sv013min=1
  }

  scalar cutoff_age=`lage'
  if cutoff_age==18 | cutoff_age==20 {
  scalar sv013min=2
  }

  scalar cutoff_age=`lage'
  if cutoff_age==22 | cutoff_age==25 {
  scalar sv013min=3
  }

gen M`lage'=0
replace M`lage'=100 if afm<`lage'
replace M`lage'=0   if afm>49

* For each cutoff age, calculate the urban, rural, and total panels by current age

scalar place_of_residence="Urban"
scalar list cutoff_age place_of_residence
svy: ratio M`lage'/awfactu_100 if v013>=sv013min & v025==1, over(v013)

scalar place_of_residence="Rural"
scalar list cutoff_age place_of_residence
svy: ratio M`lage'/awfactu_100 if v013>=sv013min & v025==2, over(v013)

scalar place_of_residence="Total"
scalar list cutoff_age place_of_residence
svy: ratio M`lage'/awfactt_100 if v013>=sv013min, over(v013)

}