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Why do we insist on working at the national level again?

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The BBC has posted an interesting map of Nigeria that captures the spatiality of politics, ethnicity, wealth, health, literacy and oil.  There are significant problems with this map.  The underlying data has fairly large error bars that are not acknowledged, and the presentation of the data is somewhat problematic; for example, the ethnic “areas” in the country are represented only by the majority group, hiding the heterogeneity of these areas, and other data is aggregated at the state level, blurring heterogenous voting patterns, incomes, literacy rates and health situations. I really wish that those who create this sort of thing would do a better job addressing some of these issues, and pointing out the issues they cannot address to help the reader better evaluate the data.

But even with all of these caveats, this map is a striking illustration of the problems with using national-level statistics to guide development policy and programs.  Look at the distributions of wealth, health and literacy in the country – error bars or no, this data clearly demonstrates that national measures of wealth cannot guide useful economic policy, national measures of literacy might obscure regional or ethnic patterns of educational neglect, and national vaccination statistics tell us nothing about the regional variations in disease ecology and healthcare delivery that shape health outcomes in this country.

This is not to say that states don’t matter – they matter a lot.  However, when we use national-scale data for just about anything, we are making very bad assumptions about the heterogeneity of the situation in that country . . . and we are probably missing key opportunities and challenges we should be addressing in our work.


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