* Create variable ct that is a string of the country value (e.g., Nigeria, Senegal)
decode(country), gen(ct)
levelsof ct, local(ctstring)

* Good time for a reminder: Do not save changed data in Stata. Always keep your data in 
* its original form. 
* (If you accidentally change your data, you can retrieve the original 
* file under MY DATA on the IPUMS DHS home page. Find the file; click Revise; then
* click Submit Data Extract.) 

* Create a temporary variable that combines all the country-specific region codes.
* For this to work, you must only have one geo_ variable for each country. In this 
* example, I drop the less specific geography (see paragraph above). 

drop geo_ke2014 geo_rw2014
egen region_temp = rowmax(geo_*)

* Use the temporary variable you created above, plus the country variable, to
* create a unique number for each region in your pooled dataset.  
gen subnational = country*100 + region_temp

* The next command creates string variables for each geographic code. 
* Find the geo_ variables in your variable list. Substitute your first and last
* geo variables for geoalt_ke2014 and geo_ug2016, respectively:
foreach var of varlist geoalt_ke2014-geo_ug2016 {
	decode `var', gen(`var'str)
}
* The following code create idregion, a single variable with values for every sample.  
egen region_label_t_gen = concat(geo*str)
gen region_label_gen = ct + " " + substr(region_label_t_gen,1,30)
egen idregion = group(region_label_gen)

* This look attaches the proper region labels to regionid. 
sort subnational
lab def subnational_gen 1 "temp"
levelsof(idregion), local(levels)

foreach l of local levels {
	gen temp = ""
	replace temp = region_label_gen if idregion == `l'
	levelsof(temp), local(templabel)
	lab def reg_label_gen `l' `templabel', modify
	drop temp
}
label values idregion reg_label_gen
label variable idregion "Subnational regions"

* Get rid of the temporary variables
drop subnational geo*str region_temp region_label_t_gen region_label_gen