As part of a new series looking how institutions are approaching impact evaluation, DI virtually sat down with Nick York, Head of Evaluation and Gail Marzetti, Deputy Head, Research and Evidence Division. For Part I of this series, see yesterday’s post. Today we focus on DFID’s funding for research and impact evaluation.
As part of a new series looking how institutions are approaching impact evaluation, DI virtually sat down with Nick York, Head of Evaluation and Gail Marzetti, Deputy Head, Research and Evidence Division
I am in the midst of a trip working on impact evaluations in Ghana and Tanzania and these have really brought home the potential and pitfalls of working with program’s monitoring data.
In many evaluations, the promise is significant. In some cases, you can even do the whole impact evaluation with program monitoring data (for example when a specific intervention is tried out with a subset of a program’s clients). However, in most cases a combination of monitoring and survey data is required.
In a New York Times column last Friday David Brooks discussed a book by Jim Manzi, and extolled the idea of randomized field trials as a way for the US to make better policies.
While it’s nice to welcome Citizen Brooks into the fold, there are a couple of points in his article worth exploring a bit.
It is increasingly recognized that well-defined property rights are crucial for realizing the benefits of market exchange and that such rights are not exogenously given but evolve over time in response to economic and political forces. The reduction of expropriation risk and the facilitation of market transactions are the two main categories through which property rights systems affect economic outcomes. However, the mechanisms by which these two categories affect outcomes differ in important ways.
My last two blogs, Lessons on School-Based Management from a Randomized Experiment and Empowering Parents to Improve Schooling: Powerful Evidence from Rural Mexico, have focused on empowering parents to help increase accountability in schools. However, too often, decentralization programs are designed without adequately conveying the messages about their purpose to the intended audiences; or, it is done in such a way that the program is rendered useless.
Does an increase in household wealth decrease child labor in poorer households? Available literature in economics suggests that when poorer households need to make their ends meet, they tend not to dispense on child labor. And as households’ income increases, child labor declines in favor of schooling. However, if schools are few and far, and their infrastructure and teachers’ performance are deficient, there is less incentives for parents to send their children to school. Child labor would then appear as a sensible option, not only for increasing family’s current income but also for training children in skilled work. Thus, an appropriate question is: To what extent and under what conditions an increase in household wealth can either decrease or increase child labor in poor households?
So this past week I was in Ghana following up on some of the projects I am working on there with one of my colleagues. We were designing an agricultural impact evaluation with some of our counterparts, following up on the analysis of the second round of a land tenure impact evaluation and a financial literacy intervention, and exploring the possibility of some work in the rural financial sector. In no particular order, here are some of the things I learned and some things I am still wondering about:
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.
I was in a meeting the other week where we were wrestling with the issue of how to capture better labor supply in agricultural surveys. This is tough – the farms are often far from the house, tasks are often dispersed across time, with some of them being a small amount of hours – either in total or on a given day. Families can have more than one farm, weakening what household members know about how the others spend their time. One of the interesting papers that came up was a study by Elena Bardasi, Kathleen Beegle, Andrew Dllon and Pieter Serneels. Before turning to their results its worth spending a bit more time discussing what could be going on.
Two things would seem to matter (among others). First, who you ask could shape the information you get. We’ve had multiple posts in the past about imperfections in within household information. These posts have talked about income and consumption and while labor would arguably be easier to observe, it may suffer from the same strategic motives for concealment and thus be underreported when the enumerator asks someone other than the actual worker to respond on this.