Measuring the Measurement Error: A Method to Qualitatively Validate Survey Data

This research is part of the Gender, Growth and Labour Markets in Low-Income Countries programme

Abstract

Empirical social science relies heavily on self-reported data, but subjects may misreport behaviors, especially sensitive ones such as crime or drug abuse. If a treatment influences survey misreporting, it biases causal estimates. We develop a validation technique that uses intensive qualitative work to assess survey misreporting and pilot it in a field experiment where subjects were assigned to receive cash, therapy, both, or neither. According to survey responses, both treatments reduced crime and other sensitive behaviors. Local researchers spent several days with a random subsample of subjects after surveys, building trust and obtaining verbal confirmation of four sensitive behaviors and two expenditures. In this instance, validation showed survey underreporting of most sensitive behaviors was low and uncorrelated with treatment, while expenditures were under reported in the survey across all arms, but especially in the control group. We use these data to develop measurement error bounds on treatment effects estimated from surveys.

This research is part of the Gender, Growth and Labour Markets in Low-Income Countries programme

Citation

Christopher Blattman, Julian Jamison, Tricia Koroknay-Palicz, Katherine Rodrigues, Margaret Sheridan, Measuring the measurement error: A method to qualitatively validate survey data, Journal of Development Economics, Volume 120, 2016, Pages 99-112 https://doi.org/10.1016/j.jdeveco.2016.01.005.

Measuring the Measurement Error: A Method to Qualitatively Validate Survey Data

Updates to this page

Published 1 January 2016