# Chapter 18 Water Supply and Sanitation

Indicators related to drinking water, sanitation and hygiene (WASH) monitor progress on basic living conditions of households and provide important information on health, education, and welfare that cannot be captured from monetary expenditure or income variables.

In SARMD, there are several variables that represent water and sanitation condition. The binary variables, piped_water and toilet_acc, indicate whether a household has access to piped water and basic sanitation facility such as a flush toilet. Piped water is considered improved water supply in contrast to other kinds of access to water like surface water, unprotected water, or wells (which, in some cases, are contaminated). Quality of drinking water can also be identified with variable water_source, which indicates the source of drinking water, but most of the harmonized surveys in the region do not have this variable.

As explained in the Introduction, the comparability across countries is difficult due to different definitions of the WASH indicators. Thus, users need to be cautious when comparing estimates across countries in the region like the share of access to water and sanitation. For instance, the questionnaires of most countries make explicit distinction between access to piped water from inside or outside the dwelling. However, survey data for Nepal does not make such a distinction, which precludes the comparability across the countries in the region. The original toilet variable of survey data for Bangladesh includes three latrine categories, but Nepal surveys includes only one communal latrine. Thus, the access to toilet can be over/under-represented for the question that has more options for flush toilets or other sanitation systems when the indicator is harmonized based on different categories.

Overall, less than half of the population do not have access to piped water. In Afghanistan and Bangladesh, only 9.7 and 11.3 percent of the population have access to piped water and the rest of them reply on informal and relatively unsafe water sources. Nepal has the highest access among SAR countries, but 60 percent of the population still does not have safe water sources.

Even though the share of households that have access to toilet is relatively higher than the one for piped-water supply, more than a third of the population in most countries do not have proper sanitation system. Except for Sri Lanka, at least 30 percent of households in each country suffer from the shortage of proper sanitation facility. In Nepal, the condition of access to toilet is even worse where only about 30 percent of the households can use toilet.

Overall improvement in the toilet access has primarily occurred among rich households. In Nepal, 29 percent of non-poor households have access to proper sanitation but only 4.3 percent of the bottom 40 group has access to toilet. A slightly higher growth rate of the access coverage among poor households still confirms that they started with extremely low conditions compared to non-poor households.

Most of the population in South Asia live without safe water and sanitation, and poor people tend to encounter more severe shortage of basic conditions. This limited access to safe water and sanitation may lead to poor hygiene behaviors, which are generally associated with child mortality, morbidity, undernutrition and, indirectly, poor provision of quality education (World Health Organization and UNICEF 2014). Thus, establishing proper infrastructure for marginalized groups to have more access to water and sanitation would be crucial in mitigating greater health and thus poverty challenges.

## Stata code

The calculations above are performed for all the countries and years avaialable. However, you may find below a short version of the code only for Pakistan 2015.

cap which quantiles
if _rc ssc install quantiles

datalibweb, countr(PAK) year(2015) type(SARMD) clear

drop if welfare==.
quantiles welfare [aw=wgt], gen(q) n(5)
gen poor=(q<=2)
gen npoor=(q>2)
foreach v in toilet_acc piped_water {
g p_v'=(v'==1&poor==1)
g np_v'=(v'==1&poor==0)
g ur_v'=(v'==1&urban==1)
g ru_v'=(v'==1&urban==0)
}

cap tab water_source, gen(wat_)
collapse (mean) toilet_acc piped_water p_* np_* ur_* ru_* wat_* [aw=wgt], by(countrycode year )

foreach v in toilet_acc piped_water p_* np_* ur_* ru_* {
ren v' re_v'
}

reshape long re_, i(countrycode year) j(indicator, string)
ren re_ value


You may access our full Stata do-file by accessing the following link. Our work consists of running the following command for each dataset and saving the results in order to export to Tableau.

### References

World Health Organization, and UNICEF. 2014. “Progress on Drinking Water and Sanitation.” Geneva, Switzerland: WHO/UNICEF. https://www.who.int/water_sanitation_health/publications/2014/jmp-report/en/.