Do schooling effects of cash transfer programs vary by poverty levels? It depends…
Having stumbled upon this development economics symposium, which took place in DC on Saturday, this paper
external validity
Thinking about the placebo effect as a “meaning response” and the implication for policy evaluation
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.
Weighting for external validity, then waiting for election results
Well I’m writing this on Election Day evening here in the U.S., and am rather consumed by the events at hand.
Mind Your Cowpeas and Cues: Inference and External Validity in RCTs
There is a minor buzz this week in Twitter and the development economics blogosphere about a paper (posted on the CSAE 2012 Conference website) that discusses a double blind experiment of providing different seeds of cowpeas to farmers in Tanzania.
WEIRD samples and external validity
A core concern for any impact evaluation is the degree to which its findings can be generalized to other settings and contexts, i.e. its “external validity”. But of course external validity concerns are not unique to economic policy evaluation; in fact they are present (implicitly or explicitly) in any empirical research with prescriptive implications.
What the HIV prevention gel trial failure implies for trials in economics
For the World AIDS Day, there is a sign at the World Bank that states that taking ARVs reduces rate of HIV transmission by 96%. If this was last year, a sign somewhere may well have read “A cheap microbicidal gel that women can use up to 12 hours before sexual intercourse reduces HIV infection risk by more than half – when used consistently.” Well, sadly, it turns out, so much for that.
Moving from Internal to External Validity – and problems with Partner Selection Bias
When done well, randomized experiments at least provide internal validity – they tell us the average impact of a particular intervention in a particular location with a particular sample at a particular point in time. Of course we would then like to use these results to predict how the same intervention would work in other locations or with other groups or in other time periods.
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Teachers don’t matter says Nobel Laureate: A new study in Science, and why economists would never publish it…
At a recent seminar someone joked that the effect size in any education intervention is always 0.1 standard deviations, regardless of what the intervention actually is. So a new study published last week in Science which has a 2.5 standard deviation effect certainly deserves attention. And then there is the small matter of one of the authors (Carl Wieman) being a Nobel Laureate in Physics and a Science advisor to President Obama.
It worked for you. Will it work for me?
Following on David’s rant on external validity yesterday, which turned out to be quite popular, I decided to keep the thread going. Despite the fact that the debate is painted in ‘either/or’ terms, my feeling is that there are things that careful researchers/evaluators can do to improve the external validity of their studies.
A rant on the external validity double double-standard
Concerns about external validity are a common critique of micro work in development, especially experimental work. While not denying that it is useful to learn what works in a variety of different settings, there seems to be two forms of double-standard (or a double double-standard) going on: first, economic journals and economists in general seem to apply it to work on developing countries more than they do to other forms of research; and second, this concern seems to be expressed about experiments more than other micro work in development.