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Berk Ozler's blog

Poverty Reduction: Sorting Through the Hype

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After seeing PowerPoint slides of the preliminary findings over the course of more than a year, it’s nice to be able to report that the six-country study that is evaluating the “ultra-poor graduation” approach (originally associated with BRAC) is finally out.

Be an Optimista, not a Randomista (when you have small samples)

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We are often in a world where we are allowed to randomly assign a treatment to assess its efficacy, but the number of subjects available for the study is small. This could be because the treatment (and its study) is very expensive – often the case in medical experiments – or because the condition we’re trying to treat is rare leaving us with two few subjects or because the units we’re trying to treat are like districts or hospitals, of which there are only so many in the country/region of interest.

Preregistration of studies to avoid fishing and allow transparent discovery

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The demand for pre-analysis plans that are registered at a public site prior available for all consumers to be able to examine has recently increased in social sciences, leading to the establishment of several social science registries. David recently included a link to Ben Olken’s JEP paper on pre-analysis plans in Economics. I recently came across a paper by Humphreys, de la Sierra, and van der Windt (HSW hereon) that proposes a comprehensive nonbinding registration of research. The authors end up agreeing on a number of issues with Ben, but still end up favoring a very detailed pre-analysis plan. As they also report on a mock reporting exercise and I am also in the midst of writing a paper that utilized a pre-analysis plan struggling with some of the difficulties identified in this paper, I thought I’d link to it a quickly summarize it before ending the post with a few of my own thoughts.

Weekly Links March 20: Giving away TOMS shoes, evaluating anti-terrorism interventions, Ben Olzer, and more...

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Bruce Wydick on the Impact of giving away TOMS Shoes: He gives kudos to TOMS for being open for evaluation and being responsive to findings, but what caught my eye was this observation: "The bad news is that there is no evidence that the shoes exhibit any kind of life-changing impact,..."

Why is Difference-in-Difference Estimation Still so Popular in Experimental Analysis?

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David McKenzie pops out from under many empirical questions that come up in my research projects, which has not yet ceased to be surprising every time it happens, despite his prolific production. The last time it happened was a teachable moment for me, so I thought I’d share it in a short post that fits nicely under our “Tools of the Trade” tag.

Worm Wars: A Review of the Reanalysis of Miguel and Kremer’s Deworming Study

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This post follows directly from the previous one, which is my response to Brown and Wood’s (B&W) response to “How Scientific Are Scientific Replications?” It will likely be easier for you to digest what follows if you have at least read B&W’s post and my response to it. The title of this post refers to this tweet by @brettkeller, the responses to which kindly demanded that I follow through with my promise of reviewing this replication when it got published online.

Response to Brown and Wood's "How Scientific Are Scientific Replications? A Response"

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I thank Annette Brown and Benjamin Wood (B&W from hereon) for their response to my previous post about the 3ie replication window. It not only clarified some of the thinking behind their approach, but arrived at an opportune moment – just as I was preparing a new post on part 2 of the replication (or reanalysis as they call it) of Miguel and Kremer’s 2004 Econometrica paper titled “Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities,” by Davey et al. (2014b) and the response (Hicks, Kremer, and Miguel 2014b, HKM from hereon).  While I appreciate B&W’s clarifications, I respectfully disagree on two key points, which also happen to illustrate why I think the reanalysis of the original data by Davey et al. (2014b) ends up being flawed.

Friday links November 21

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Confusing a treatment for a cure

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A treatment is an instance of treating someone, say, medically. A cure ends a problem. Sometimes, the treatment is a cure. Other times, it just keeps the problem under control without curing it: if you remove the treatment, the problem comes back…
 

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