Many important policies are implemented at the national level. Monetary policy, fiscal policy, and many regulations are key examples. Pure time series or before-after analysis of the impacts of changes in these policies on the economy of a country will be contaminated by other changes going on in the economy. Simply trying to difference out global trends will not account for systematic differences in the growth path of the country where the reform took place from the average global growth path. This makes evaluation of the impacts of such policies difficult.
· A new From Evidence to Policy note looks at the impact of a community grant program in Indonesia which gave grants to communities for health and education services. The program lowered malnutrition, and finds performance-based incentives lead to improved performance.
Worker training and skill upgrading programs are a major focus in impact evaluation work. The design of such training programs implicitly involves the identification of the activities that a worker needs to accomplish in a job. Only then can the program offer training in the set of skills required to complete these identified tasks.
· On the FAI blog, Jonathan Morduch discusses what’s next in microfinance, in terms of how experiments can move towards allowing greater external validity.
On the World Bank’s today page today I saw the following:
This seemed really high to me, and a strange way of presenting statistics. Following the link, it directs you to this World Bank Data Viz Tumblir which has a bunch of statistics all presented in the form, if the World had only 100 people, then…
When I drop my kids off at daycare, it does occasionally occur to me: what am I doing to them? (This thought is particularly acute when they wrap themselves around my legs). Last year, 3ie put out a systematic review on the impact of daycare programs. The conclusions are instructive:
Since I’ve had three emails in one week asking me about this issue, I figured I might as well blog about it and have something to refer people to instead. The questions have all been variants of:
· Are women better remitters than men?
· Does having mothers migrate result in worse outcomes for kids than having their fathers migrate?
In recent conversations on research, I’ve noticed that we often get confused when discussing the placebo effect. The mere fact of positive change in a control group administered a placebo does not imply a placebo effect – the change could be due to simple regression to the mean.
So I have blogged in the past about the potential and the use of gender disaggregated data, but my work this past week in Ghana made me realize (again and in new ways) how complicated it can get in practice.