(PhysOrg.com) -- International development and aid groups are making decisions and distributing funds to African nations based on national statistics that are incomplete and untrustworthy, says Simon Fraser University economic historian Morten Jerven.
There is an unjustified numbers game that has a misleading air of accuracy, says Jerven, a School for International Studies assistant professor, who spent several months observing statistical collection methods in countries including Ghana, Nigeria, Uganda, Kenya, Malawi, Tanzania and Zambia.
He found that little is actually known about the countries economic status. Theres a great variation across time and across countries on what kind of data is available for what kind of indicators, he says.
Thats because statistics offices are chronically underfunded and tend to use windfall funding from strategic donors to produce statistics that only interest the donors. These are often social indicators related to health delivery, maternal health or school attainment, rather than broader, more useful economic statistics related to employment, industry, agriculture and economic growth.
As a result, the countries statistical systems are incomplete and the type and reliability of data collected varies from country to country.
Many data users are not aware of this variation in quality, says Jerven, adding most aggregate statistics on African economies involve a lot of guesswork.
This all raises questions about which of these indicators we should use to select countries for a particular project, and how we know whether a project is working or not, he says.
Jerven has presented his findings to World Bank officials and several conferences. The research has also resulted in a book, Poor Numbers: Facts, Assumptions and Controversy in African Development Statistics, which is forthcoming from Cornell University Press.
Jervens aim is to initiate discussions with donors and aid organizations about what kind of statistics should be a priority and how to align them with the priorities of local African economies.
Explore further: Stereotypes lower math performance in women, but effects go unrecognized