William Easterly, respected for his contributions to the development debate and widely know for his opposition to the Jeff Sachs camp, recently published an interesting piece entitled How the Millennium Development Goals are Unfair to Africa. The article reveals specific statistical misrepresentations and non-standard methods of calculating progress toward the MDGs, ultimately concluding that such methods "paint an unfairly bleak portrait of Africa."

Easterly identifies a number of decisions regarding data selection and representation, all of which seem to downplay Africa's progress and throw its development shortcomings into even sharper relief against improvements made by other regions. These statistics involve the selected benchmark year, absolute vs. percentage changes, change targets vs. level targets, and the use of positive vs. negative indicators to compare improvements.

Even for someone - such as myself - with limited exposure to advanced statistics, (most) of Easterly's arguments immediately register as common sense, and raise some important questions. These are questions not just for development agencies pursuing the MDG grail, but also for investors, markets, and governments who make use of development data (and overall conclusions).

They are also some of the same questions that crossed my mind when I read an editorial last month arguing that, due to the "large statistical glitch" of using outdated calculations of purchasing power parity in China, the number of Chinese living below the World Bank's poverty line ($1 a day) may in fact be 3 times more than previously thought - 300 million, not 100 million.

Now, if you were a sizeable MNC and suddenly found that your market had shrunk or expanded by two thirds, what would you do?

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On Wednesday, I attended a presentation by Jessica Cohen on her doctoral research experiment (co-authored with Pascaline Dupas) about distribution schemes for anti-malarial long-lasting bednets. The randomized experiment, conducted in rural, western Kenya, aimed to test the difference between free distribution and cost-sharing schemes in terms of their direct impact on malaria prevention in pregnant women and their infants. A draft of their paper is available through the Brookings Institution.

In the past, I have been an advocate for the continued use of social marketing (cost-sharing) and for profit-based BoP business models to produce and distribute insecticide treated nets (ITNs). Because of this history, I was a little apprehensive about what Cohen's presentation would reveal. After all, the report's summary stated clearly that the experiment produced "no evidence that cost-sharing reduces wastage on those that will not use the product: women who received free ITNs [insecticide-treated nets] are not less likely to use them than those who paid subsidized positive prices."

It turns out, though, that the real conclusion of the experiment in no way supports any blanket claims, such as those made to the New York Times by Dr. Arata Kochi, Director of the WHO's malaria program: "Virtually the only way to get the nets to poor people is to hand out millions free." Instead, the study arrives at this cautious and tempered conclusion: free distribution of bednets is not the way but also a way, in some cases, for lowering malaria rates in a cost-effective manner.

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