Some WASHwatch related reading…
Looking at the sources of GDP figures for African countries, and the methods used to derive them. Discovers that
a) GDP cannot be used to consistently or accurately rank African economies by size
b) Many African GDP estimates are significant underestimates (as I always point out in the MIC debates, this doesn’t mean people are not poor, it just means our definition of poverty is wrong)
c) Partly as a consequence of b) many African GDP growth estimates are significant overestimates
d) More support and investment needs to put into national statistics offices, who need to be empowered to measure the things that matter to the country, rather than the things that matter to the donors.
To be aware of if anyone quotes GDP at you, and strong argument for discounting any development econometrics that uses a regression of GDP changes over time against any other variable (even sanitation!). Interesting points made about tendency in development research for economics to go deeper into ‘established’ datasets (e.g. Worldbank world development indicators, JMP WASH access) rather than deeper into countries themselves to understand the context that produced those numbers.
Based on Duncan Green’s recommendation in his blog. Loads of the examples are ‘water-based’ since the terminology is about stocks and flows, so rivers and lakes make good metaphors. But basically a very short, highly readable intro to systems thinking and complexity. Plenty to mull over about ‘how change happens’ and ‘how to make changes’ in complex non-linear systems. Highly recommend to all.