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Measuring the measurement error: A method to qualitatively validate survey data

Christopher Blattman (), Julian Jamison, Tricia Koroknay-Palicz, Katherine Rodrigues and Margaret Sheridan

Journal of Development Economics, 2016, vol. 120, issue C, 99-112

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.

Keywords: Measurement error; Survey data; Validation; Field experiments; Liberia; Crime; Drugs; Risky behaviors (search for similar items in EconPapers)
Date: 2016
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Working Paper: Measuring the Measurement Error: A Method to Qualitatively Validate Survey Data (2015) Downloads
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DOI: 10.1016/j.jdeveco.2016.01.005

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