In an interesting new paper, Jens Ludwig, Jeffrey Kling and Sendhil Mullainathan argue that economists should be doing more experiments to identify behavioral mechanisms, and that these can be central to policy, even if the experiments themselves are far from what a policymaker would implement. So what are these mechanism experiments, and what can we learn from them?
David McKenzie's blog
· At bigthink.com - Does abstinence help kids stay in school? The difficulties of inference from observational studies.
Busia is the project home in Kenya of the Dutch NGO International Child Support (ICS), and is home of many of the first randomized experiments in development economics.
Yesterday Martin Ravallion argued that the fact that much of the impact evaluation taking place involves assessing the impact of specific projects one at a time is not that helpful in assessing development impact because it doesn’t tell us about the impact of overall portfolios if there are interactions between policies or if the subset of projects which get evaluated in an overall portfolio are not a representative sample.
A key issue in any impact evaluation is take-up (i.e. the proportion of people offered a program who use it). This is particularly an issue in many finance and private sector (FPD) programs. In many health and education programs such as vaccination campaigns or getting children to school programs, the goal of the program is actually to have all eligible individuals participate. In contrast, universal take-up is not the goal of most FPD programs, and, even when it is a goal, it is seldom the reality.
I've just been alerted to the From Evidence to Policy series produced by the World Bank's Human Development network. These short and slick notes present some of the key findings from impact evaluations the World Bank has been doing in the HD area.
At a recent seminar someone joked that the effect size in any education intervention is always 0.1 standard deviations, regardless of what the intervention actually is. So a new study published last week in Science which has a 2.5 standard deviation effect certainly deserves attention. And then there is the small matter of one of the authors (Carl Wieman) being a Nobel Laureate in Physics and a Science advisor to President Obama.
Diseases like malaria, diarrhea and intestinal worms plague hundreds of millions of people in the developing world. A major puzzle for development researchers and practitioners is why the poor do not purchase available prevention technologies that could reduce the burden of these diseases. While much of the recent literature has focused on price elasticities of demand and behavioral explanations, another potential explanation is that liquidity constraints prevent the poor from undertaking profitable health investments.
Concerns about external validity are a common critique of micro work in development, especially experimental work. While not denying that it is useful to learn what works in a variety of different settings, there seems to be two forms of double-standard (or a double double-standard) going on: first, economic journals and economists in general seem to apply it to work on developing countries more than they do to other forms of research; and second, this concern seems to be expressed about experiments more than other micro work in development.