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You think randomized controlled trials are great? Actually, they are even better than that-Guest post by Clement de Chaisemartin

My job market paper brings some good news to the impact evaluation community. First, it shows that causal inference in randomized controlled trials (RCTs) relies on weaker assumptions than was previously thought. Second, it shows that RCTs capture local treatment effects that are less local than we previously believed.

Sorting through heterogeneity of impact to enhance policy learning

Jed Friedman's picture

The demand and expectation for concrete policy learning from impact evaluation are high. Quite often we don’t want to know only the basic question that IE addresses: “what is the impact of intervention X on outcome Y in setting Z”. We also want to know the why and the how behind these observed impacts. But these why and how questions, for various reasons often not explicitly incorporated in the IE design, can be particularly challenging.

Should we believe the hype about adolescent girls?

Markus Goldstein's picture

There aren't that many development initiatives I know that have their own slickly produced video, sponsored by a major corporation, let alone a parody. But the "girl effect," which makes the argument that investing in adolescent girls is a great thing, is one.  

Behavioral design: slap or tax yourself into productivity?

David McKenzie's picture

One of those stories going the rounds about a month ago concerns a blogger in San Francisco, who worried he was wasting too much time on Facebook and Reddit. As he writes on his blog, he used a software app which tracked what he was doing with his time and found almost 19 hours a week went to these activities.

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