In the first equation, piped water coverage is a function of national income.
In the second equation, wash related mortality is a function
of piped coverage, and in the third equation, we try to
estimate economic losses as a function of deaths, illnesses, and other costs
that households incur, from having poor water and sanitation conditions.
It's actually rather surprising, that this hasn't been done before.
But, what I'm going to to show you then, is a picture of where the
world's headed in terms of water and
sanitation coverage, and where problems will remain.
The data we're going to use to estimate
this simulation model are at the country level.
They're country level averages.
Now there are problems with using country
level averages, particularly for big countries like
China and India, which households are going to
have many different conditions in modern sanitation.
But, we're going to take an average of those conditions, for the whole country.
We also have con, variables for coverage, for piped water, and
sanitation services, from the JMP, from 1990 to 2008.
And, we have WASH-related mortality statistics
from 2004, from the World Health Organization.
In addition to these country level data we also are going to
use data on urbanization, world regions,
literacy, fertility, governance and some time trends.
We're also going to look to the literature to help us understand
the relationship between income and the value of a statistical life.
We need to do this in order to estimate economic losses associated
with poor water and sanitation conditions today and then on into the future.