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From my inbox: Three enquiries on winsorizing, testing balance, and dealing with low take-up

David McKenzie's picture

I’ve been travelling the past week, and had several people contact me with questions about impact evaluation while away. I figured these might come up again, and so I’d put up the questions and answers here in case they are useful for others.
Question 1: Winsorizing – “do we do this on the whole sample, or do we do it within treatment and control, baseline and follow-up?”
Winsorizing is commonly used to deal with outliers, for example, you might set all data points above the 99th percentile equal to the 99th percentile. It is key here that you don’t use different cut-offs for treatment and control. For example, suppose you have a treatment for businesses that makes 4 percent of the treatment group grow their sales massively. If you winsorize separately at the 95th percentile of the treatment distribution for the treatment group and at the 95th percentile of the control distribution for the control groups, you might end up completely missing the treatment effect. I think it makes sense to do this with separate cutoffs by survey round to allow for seasonal effects and so you aren’t winsorizing more points from one round than another (which could be the case if you used the same global cutoffs for all rounds).

Testing different behavioral approaches to get people to attend business training

David McKenzie's picture

A while back I blogged about work using active choice and enhanced active choice to get people to get flu shots and prescription refills. The basic idea here is that relatively small modifications to the way a choice is presented can have large impacts on the take-up of a program. This seemed useful in the context of many of our training programs– attendance rates averaged 65 percent in a review of business training programs I did with Chris Woodruff. Therefore for an ongoing evaluation of the GET AHEAD business training program in Kenya, we decided to test out this approach.
 

Enhanced Active Choice: Utilizing Behavioral Economics to Increase Program Take-up

David McKenzie's picture
Shifting from opt-in to opt-out defaults is one of the clearest success stories for policy to emerge from behavioral economics, as evidenced by the large increases in organ donor rates and contributions to retirement savings plans obtained when opt-out defaults are used instead of opt-in. 
                However, there are several limits of opt-out policies: