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.
I was circumcised in the hospital as a very young infant. Most children do get circumcised in Turkey, although I suspect that many are not as lucky as I was, including my younger brother, who went through the ordeal when he was around six years-old. I remember him in some pain and discomfort for what seemed like a long period of time to me at the time, even though it was probably no longer than a few weeks if not days…
Low birth weight, usually defined as less than 2500 grams at birth, is an important determinant of infant mortality. It is also significantly associated with adverse outcomes well into adulthood such as reduced school attainment and lower earnings. Maternal nutrition is a key determinant of low birth weight and it’s no surprise that nutrition interventions targeted at pregnant mothers can have significant impacts.
I recently came across a paper by Kelsey Jack which is a white paper for the J-PAL and CEGA Agricultural Technology Adoption Initiative (ATAI). This paper systematically explores the barriers to technology adoption that come from market inefficiencies, what we know about these, and what research is going on (under ATAI) to fill these gaps.
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.
Regardless of whether we do empirical or theoretical work, we all have to utilize information given to us by others. In the field of development economics, we rely heavily on surveys of individuals, households, facilities, or firms to find out about all sorts of things. However, this reliance has been diminishing over time: we now also collect biological data, try to incorporate more direct observation of human behavior, or conduct audits of firms.
David has started a discussion that I find intrinsically interesting and one that well-designed impact evaluations can help clarify: why don’t more people adopt low-cost efficacious health technologies? We may be able to think of examples in our own lives – i.e. “why don’t I take vitamins more regularly?” or “why, if diabetic, don’t I self-test my blood sugar more frequently?” These same questions also resonate for large-scale health programs in many settings.
OK, let’s put two blog posts in a pot and stir. In a previous post on measuring consumption, Jed gave us some food for thought, while over on Aid Thoughts, Matt is talking about how a respondent is seeing the enumerator on the sly to conceal land that he doesn’t want his wife to know about. Put it together, and what do you have?
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.