Today we ran a very public randomization for our field experiment in Uganda. Village and parish leaders gathered for a presentation and meeting, and after introductions and some discussion, everyone lined up to take turns selecting villages into treatment and control. Despite some hiccups, a big success.
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But some level of blocking/stratification is possible even with a public lottery right? The fairness principle can be pushed one level down and you can say that we'll make sure all parishes get a proportional number of villages in Phase 1! It should work – though it's potentially more baskets. Did you consider it?
Also, the bigger risk in public randomization is substitution bias – since a district-level government may decide to prioritize other spending to the control group – and the fairness criteria would support that. Is this a problem for you? Can you at least measure it to make sure it's not a problem for the analysis?
Good job regardless!
According to Gary King, pairwise randomization is where you get the most leverage because non-compliance means you only through out one pair rather than having your entire pool potentially contaminated. However, it's far harder to sell the norms necessary to do pairwise randomization publicly.
I've had a number of conversations with people in the NGO world about randomization and they just don't like it, it seems deeply unfair to them. They think that way even though they don't have the capacity necessary to scale up to all localities at once, but (in these conversations) they argue that other norms are more important. I'm wondering if the NGOs are more bothered by the randomization than are the constituencies receiving the services …
When you don't have enough resources to get *everyone*, rando is really helpful–the villagers I worked with in Ghana laughed and cried based on the number they drew, but in the end we never once heard anyone cry foul. This is a big deal in places where people think things are generally rigged.