Should the identity of the author affect the interpretation of the existing evidence? You might answer ‘no,’ but it does. And when it does, it may affect the decision of influential people and institutions, such as a multilateral donor organization or, in the following case, a high level panel discussing the post-MDGs development agenda.
- On the IDB First steps blog, evidence from CCT programs that the long-term impacts are greater when kids get this in the womb and in their first two years of life versus even when aged 2 to 5: children who were exposed to the CCT while in-utero and during the first two years of life score 0.15 standard deviations higher in the cognitive development assessment than those boys who were exposed to the program when they were 2 to 5 years old.
About 15 years ago, when I was doing my dissertation research with a professor with experience in fieldwork, we did a 15 round survey with households in Ghana. Given the frequency of the visits, we based the enumerators in the village. But we were careful to hire enumerators from nearby big towns -- not the villages in which we were working. This was partly for skills, but mostly to make sure that the enumerators wouldn't be asking sensitive questions of people they knew.
Standard economic theory would suggest that a one-time infusion of cash should have at most a temporary effect on business profitability – over time, individuals facing high returns should be able to re-invest business profits and bit-by-bit bootstrap themselves up to the steady-state size. Yet in an experiment I did with Suresh de Mel and Chris Woodruff in Sri Lanka, we find a one-time grant has sustained impacts five years later on male microenterprise owners.
- Call for papers – NEUDC conference November 2-3 at Harvard. This is a fun conference which allows you to see lots of new work in development .
Of all the impact evaluation methods, the one that consistently (and justifiably) comes last in the methods courses we teach is matching. We de-emphasize this method because it requires the strongest assumptions to yield a valid estimate of causal impact. Most importantly this concerns the assumption of unconfoundedness, namely that selection into treatment can be accurately captured solely as a function of observable covariates in the data.
At the end of this month, Google will close down Google Reader. We have about 1500 Google Reader subscribers, and we want to make sure you keep reading us once this happens. So here are some options (apart from the obvious one of coming directly to our blog page):
Given Jed's post last week on thinking through performance incentives for health workers, and the fact that the World Bank is in the throes of a reform process itself, a fascinating new paper from Imran Rasul and Daniel Rogger on autonomy and performance based incentives in Nigeria gives us some other food for thought. In a nutshell, Rasul and Rogger
Most experiments in development economics involve giving the treatment group something they want (e.g. cash, health care, schooling for their kids) or at least offering something they might want and can choose whether or not to take up (e.g. business training, financial education). Indeed among the most common justifications for randomization is that there is not enough of the treatment for everyone who wants it, leading to oversubscription or randomized phase-in designs.