Attrition in Randomized Control Trials: Using Tracking Information to Correct Bias

90 Pages Posted: 21 Apr 2017

See all articles by Karen Macours

Karen Macours

Paris School of Economics (PSE)

Teresa Molina Millán

New University of Lisbon - Nova School of Business and Economics

Multiple version iconThere are 2 versions of this paper

Date Written: April 2017

Abstract

This paper starts from a review of RCT studies in development economics, and documents many studies largely ignore attrition once attrition rates are found balanced 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 characteristics. 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.

Keywords: attrition, long-term evaluation, randomized control trials

JEL Classification: C31, C81, C93, O12

Suggested Citation

Macours, Karen and Molina Millán, Teresa, Attrition in Randomized Control Trials: Using Tracking Information to Correct Bias (April 2017). CEPR Discussion Paper No. DP11962. Available at SSRN: https://ssrn.com/abstract=2954483

Karen Macours (Contact Author)

Paris School of Economics (PSE) ( email )

48 Boulevard Jourdan
Paris, 75014 75014
France

Teresa Molina Millán

New University of Lisbon - Nova School of Business and Economics ( email )

Campus de Campolide
Lisbon, 1099-032
Portugal

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