Michael Hanmer, Antoine Banks, and Ismail White have a new paper in Political Analysis that returns to a longstanding problem in voting and survey research: overreporting bias among survey respondents.
From the abstract:
Voting is a fundamental part of any democratic society. But survey-based measures of voting are problematic because a substantial proportion of nonvoters report that they voted. This over-reporting has consequences for our understanding of voting as well as the behaviors and attitudes associated with voting. Relying on the “bogus pipeline” approach, we investigate whether altering the wording of the turnout question can cause respondents to provide more accurate responses. We attempt to reduce over-reporting simply by changing the wording of the vote question by highlighting to the respondent that: (1) we can in fact find out, via public records, whether or not they voted; and (2) we (survey administrators) know some people who say they voted did not. We examine these questions through a survey on US voting-age citizens after the 2010 midterm elections, in which we ask them about voting in those elections. Our evidence shows that the question noting we would check the records improved the accuracy of the reports by reducing the over-reporting of turnout.
What is neat about this paper is that the authors suggest a relatively simple way to reduce (but not eliminate–see the attached graphic) the bias.
Courtesy of Oxford University Press
Michael Hanmer, Antoine Banks, and Ismail White have a new paper in Political Analysis that returns to a longstanding problem in voting and survey research: overreporting bias among survey respondents.
From the abstract:
What is neat about this paper is that the authors suggest a relatively simple way to reduce (but not eliminate–see the attached graphic) the bias.
It’s also notable that the research comes out of the TESS (Time Sharing Experiments in Social Science), an innovative and low-cost project funded by the Political Science Program of the National Science Foundation (Congress: are you listening?).