** DIMENSIONAL BREADDOWN *******************************************************
** Censored Headcount
** We identify those individuals who are poor using a poverty cut-off X and deprived
** at the same time. First, we need to define the poverty cut-off and then we can
** calculate the censored headcount and contributions per dimension
local k=40
foreach var of global indicators {
gen ch_`var'_k`k'p= (ci>=`k'/100 & hh_d_`var'==1)
label var ch_`var'_k`k'p "Censored headcount of dimension`var' with k=`k'"
}
** The Censored headcount ratio of a dimension is the proportion of the population
** that are poor with respect to a certain cutoff and are deprived in that dimension
** at the same time. First you should define the poverty cut-off (k) in percentage
** (i.e., 10 =10%)
su ch_*_k`k'p[aw=weight], sep(7)
** Contributions (WEIGTHED & RELATIVE)
su m0_`k'p [aw=weight]
local m0_`k'p=r(mean)
foreach var of global indicators {
gen abs_cont_`var'_k`k'p= ch_`var'_k`k'p*w_`var'
label var abs_cont_`var'_k`k'p "Weigthed contribution of dimension `var' to M0 with k=`k'"
gen rel_cont_`var'_k`k'p= ch_`var'_k`k'p*w_`var'/`m0_`k'p'
label var rel_cont_`var'_k`k'p "National contribution of dimension `var' to M0 with k=`k'"
}
su abs_cont_*_k`k'p [aw=weight], sep(6)
su rel_cont_*_k`k'p [aw=weight], sep(6)
* SUBGROUP DECOMPOSITION ******************************************************
** Subgroup Decomposition in the screen
tabstat h_40p a_40p m0_40p [aw=weight], by (region)
tabstat hh_d_* [aw=weight], by (region)
tabstat ch_*_k40p [aw=weight], by (region)
tabstat abs_cont_*_k40p [aw=weight], by (region)
* to get the relative contribution by region please divide the abs. by the M0 of each region