The issue of statistical capacity building in developing countries is actually becoming a sexy issue. I can’t believe I am saying this. Though, we can ask Hal Varian for his opinion on that here.
As Wikiprogress is a community with several networks looking for better indicators of well-being, I think that we need to recognise something before we go any further.
There is a crisis of official data production
Recent discussions at the OECD with Paris 21 (see snazzy new website here) and around the world here are really bringing this issue to the forefront. However, in Bill Gates’ 2013 letter he says on page 1:
“In the past year I have been struck again and again by how important measurement is to improving the human condition. You can achieve amazing progress if you set a clear goal and find a measure that will drive progress toward that goal—in a feedback loop”.
Well, that is proving to be difficult….
I recently read Morten Jerven's new book Poor Numbers which is an analysis of the production and use of African economic development statistics. Jerven’s research shows how the statistical capacities of sub-Saharan African economies have fallen into disarray. He reports that the numbers substantially misstate the actual state of affairs. As a result, scarce resources are misapplied. Development policy does not deliver the benefits expected. Policymakers’ attempts to improve the lives of the citizenry are frustrated. Donors have no accurate sense of the impact of the aid they supply. The book outlines that statistics tell us less about African development then we would like to think. He says that the main problem is a lack of investment in statistics production. Jerven gives the Zambia example where there is one person working in all of national accounts.
That isn’t very sexy.
New demands but where is the supply?
With the rather intense debates around the post-2015 framework, it is hard to believe that producing good numbers isn’t a bigger focus of the chatter. There is more pressure being placed on the NSOs for quality data but there doesn’t seem be a strong push to raise the capacity of these offices. Developing countries faced with the buzz word “evidence based policy” are feeling the squeeze in that policies cannot be made or monitored without good data.
This isn’t a developing country phenomenon. OECD countries are also looking at ways to meet new (and expensive) demands. Data coming from sources like Google and others are beginning to compete with the NSOs because they can produce data that is timelier. In this world of instant this and instant that, people will not wait 5 years for the next survey result.
Solutions include:
- invest more money in producing high quality statistics (i.e. make it a priority)
- NSOs should work with other producers of statistics in public private partnerships
- international goals such as the post-2015 framework should have a goal for statistical quality.
- involve citizens and local perspectives in the production process
I recommend reading Jergen's book which is chock full of history and recommendations. Follow the Paris 21 website for more on this topic as well. I also welcome your views on this blog.
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