Discussion paper

DP11962 Attrition in Randomized Control Trials: Using tracking information to correct bias

This paper starts from a review of RCT studies in development economics, and
documents many studies largely ignore attrition once attrition rates are found bal-
anced between treatment arms. The paper analyzes the implications of attrition for
the internal and external validity of the results of a randomized experiment with
balanced attrition rates, and proposes a new method to correct for attrition bias.
We rely on a 10-years longitudinal data set with a final attrition rate of 10 percent,
obtained after intensive tracking of migrants, and document the sensitivity of ITT
estimates for schooling gains and labour market outcomes for a social program in
Nicaragua. We find that not including those found during the intensive tracking
leads to an overestimate of the ITT effects for the target population by more than
35 percent, and that selection into attrition is driven by observable baseline char-
acteristics. We propose to correct for attrition using inverse probability weighting
with estimates of weights that exploit the similarities between missing individuals
and those found during an intensive tracking phase. We compare these estimates
with alternative strategies using regression adjustment, standard weights, bounds
or proxy information.

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Citation

Macours, K (2017), ‘DP11962 Attrition in Randomized Control Trials: Using tracking information to correct bias‘, CEPR Discussion Paper No. 11962. CEPR Press, Paris & London. https://cepr.org/publications/dp11962