Validating the “Genuine Pipeline” to Limit Social Desirability Bias in Survey Estimates of Voter Turnout

Abstract

Abstract It is well documented that survey overreporting of voter turnout due to social desirability bias threatens inference about political behavior. This paper reports four studies that contained question wording experiments to test questions designed to minimize that bias using a “pipeline” approach. The “pipeline” informs survey participants that researchers can perform vote validation to verify turnout self-reports. This approach reduced self-reported turnout by 5.7 points in the 2020 American National Election Study, which represents a majority of the estimated overreporting bias. It reduced reported turnout by 4 points in two nonprobability samples. No effect was found in a third nonprobability study with Amazon Mechanical Turk workers. Validated vote data also confirm that the pipeline approach reduced overreporting. We tested heterogeneous effects for sophistication and several other variables, but results were inconclusive. The pipeline approach reduces overreporting of voter turnout and produces more accurate estimates of voters’ characteristics.