Impact evaluations

In a recent article Andres Parrado and I take a look at the two main sources of learning outcomes data in India – NAS and ASER – and conclude that a) NAS data is (most likely) completely unreliable and b) ASER data, while reliable, is a bit noisy.

In my last blog post, I shared some thoughts on Sarah Rose’s excellent recent working paper on how USAID could become more evidence based. TLDR: I argue that USAID doesn’t necessarily need to generate evidence (since there are plenty of other orgs that do that) but it does need to the use the latest and best evidence.

Sarah Rose at the Center for Global Development recently published an excellent note on how to make USAID programming more evidence-based. As a former member of one of the groups mentioned in the article (the Evaluation and Impact Assessment group at the erstwhile Global Development Lab) and a long-time evaluator, this is a topic dear to my cold, data-driven heart.

Last week, Chris Blattman published a long blog post titled “Why ‘what works?’ is the wrong question: evaluating ideas not programs.” In the blog post, which was adapted from a talk he gave at DFID, Blattman argues that a) impact evaluations should focus on deeper, theory-driven questions rather than just whether a program works or not and b) researchers should design impact evaluations to allow for generalizability by paying attention to context and running multiple evaluations in multiple contexts.