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

A-Tier
Journal: Journal of Development Economics
Year: 2016
Volume: 120
Issue: C
Pages: 99-112

Authors (5)

Blattman, Christopher (University of Chicago) Jamison, Julian (not in RePEc) Koroknay-Palicz, Tricia (World Bank Group) Rodrigues, Katherine (not in RePEc) Sheridan, Margaret (not in RePEc)

Score contribution per author:

0.804 = (α=2.01 / 5 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:eee:deveco:v:120:y:2016:i:c:p:99-112
Journal Field
Development
Author Count
5
Added to Database
2026-01-24