We want to increase (girls) education… but what’s the best way to do this?
If you are like most people working with quantitative data in development, getting too many statistically significant results is probably not your most pressing problem. On the contrary, if you are lucky enough to find a star, whether it's of the 1%, 5% or 10% type, there are plenty of star-killers to choose from. In what is perhaps the only contribution to the rare genre of 'econometrics haiku', Keisuke Hirano reflects on one of them: T-stat looks too good // Try clustered standard errors - // Significance gone (in Angrist and Pischke's MHE).
- trial registry
Across developing countries, there is considerable under-investment in children's human capital; it is reflected in low immunization rates, child malnutrition, high drop-out rates, etc. Because of the (both individual and aggregate) long-term effects of human capital investment during childhood, governments across the globe have designed and implemented policies to encourage parents to invest more in the health and education of their children (numerous conditional cash transfer programs across countries are some examples).
In the 1960s, black and white individuals in the United States had radically different labor market outcomes. In 1962, the unemployment rate for African-Americans was 13 percent while it was only 6 percent for whites. Fifty years have passed, enough time for Martin Luther King to go from movement leader to monument, but as of 2010, the unemployment rate in the U.S.
Poor households in rural areas are exposed to substantial weather shocks that can generate great fluctuations in income and consumption if insurance markets are not complete (Dercon and Christiaensen 2011, etc.).
This week, we are starting a new series where those of you on the job market will be blogging drawing on their dissertation work. As you will remember, about 3 weeks ago we invited you to submit your JM papers to Development Impact. Many of you did, and we have subsequently invited some of you to be a guest blogger for a day.
It is well recognized that the stock of knowledge among development practitioners matters to development impact. How then do the operational staff of the largest international development agency value and use its research for their work?
A veritable bounty of interesting links this week:
· A summary of take-up results of a vocational training program for youth in Kenya by Miguel, Kremer and co-authors in the World Bank’s HD note.
For the World AIDS Day, there is a sign at the World Bank that states that taking ARVs reduces rate of HIV transmission by 96%. If this was last year, a sign somewhere may well have read “A cheap microbicidal gel that women can use up to 12 hours before sexual intercourse reduces HIV infection risk by more than half – when used consistently.” Well, sadly, it turns out, so much for that.
One of the things I learned from other folks at the Bank I work with is the usefulness of doing a workshop early in the early design of an impact evaluation to bring the project and the impact evaluation team together to hammer out design. With one of my colleagues, I did one of these during my recent trip to Ethiopia and a bunch of things stuck out.