- On the CGD blog, William Savedoff summarizes a conference held last week at CGD on impact evaluation – he includes a nice graph from his presentation which shows the growth in the number of impact evaluations over time
In our continuing series on discussing institutional approaches to impact evaluation, DI virtually sat down with Jack Molyneaux, Director of Independent Evaluations at the Millennium Challenge Corporation. (Please note that these are Jack’s opinions, not that of the MCC)
DI: Impact Evaluation seems to be something that's pretty important at the MCC. Can you tell us a bit about how this focus came about?
JM: Since its inception MCC’s mandate has included demonstrating results. Rigorous impact evaluations have always been a key component of that mandate.
A new book Chronicles from the Field: The Townsend Thai Project provides a behind-the-scenes look at putting together one of the most impressive data collection projects in development - Rob Townsend’s Thai data, which has conducted monthly surveys on a panel of Thai households for over 150 consecutive months, as well as annual surveys. The Townsend Thai data is available online and has spurred a number of research papers by Rob and his co-authors. This book looks at what it takes to produce all this data.
I’ve been reading Evidence-based policy: a practical guide to doing it better by Nancy Cartwright and Jeremy Hardle. The book is about how one should go about using existing evidence to move from “it works there” to “it will work here”. I was struck by their critique of external validity as it is typically discussed.
I have just come back from the pilot for a survey on perceptions of inequality in Lao Cai, near the northern border of Vietnam. Many tourists visit via the overnight train from Hanoi to trek through the green hills filled with terraced rice paddies and see something of the culture of the region’s ethnic minority groups. Despite all the tourist money, the region remains one of Vietnam’s poorest.
When we want to target a poor population for an anti-poverty program, we first need to figure out who is actually poor. This isn’t straightforward – there are a range of potential targeting criteria and options. In countries where poverty is less dense and data is decent, two of the more common options are self-targeting and proxy means tests. A nice recent paper by Vivi Alatas, Abjijit Banerjee, Rema Hanna, Benjamin Olken, Ririn Purnamasari, and Matthew Wai-Poi sheds some light on th
There are a number of things we would like to measure for which a direct question may be refused or met with an inaccurate answer. Three new papers demonstrate some of the methods that can be used to help overcome these problems.
Micro-insurance pilot programs begin with grand hopes that the target population will enroll and obtain program benefits, but many are disappointed that after much planning and effort so few actually take up the program. Apparently take-up rates greater than 30% are rare and often do not exceed 15%. Furthermore, only a fraction of beneficiaries choose to renew their participation after the initial enrollment period.