Saying versus doing: a new donation method for measuring ideal points

Nicholas Haas () and Rebecca Morton
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Nicholas Haas: New York University

Public Choice, 2018, vol. 176, issue 1, No 6, 79-106

Abstract: Abstract Scaling methods pioneered by Poole and Rosenthal (Am J Polit Sci 29(2):357–384, 1985) redefined how scholars think about and estimate the ideologies of representatives seated in the US Congress. Those methods also have been used to estimate citizens’ ideologies. Whereas studies evaluating Congress typically use a behavioral measure, roll call votes, to estimate where representatives stand on the left-right ideological spectrum, those of the public most often have relied on survey data of stated, rather than revealed, preferences. However, measures of individuals’ preferences and, accordingly, estimates of their ideal points, may differ in important ways based on how preferences are elicited. In this paper, we elicit the same individuals’ preferences on the same 10 issues using two different methods: standard survey responses measured on a Likert scale and a donation exercise wherein individuals are forced to divide $1.50 between interest groups with diametrically opposed policy preferences. Importantly, expressing extreme views is costless under the former, but not the latter, method. We find that the type of elicitation method used is a significant predictor of individuals’ ideal points, and that the elicitation effect is driven primarily by Democratic respondents. Under the donation method, the ideal points of Democrats in the aggregate shift left, particularly for those Democrats who are politically engaged. In contrast, wealthy Democrats’ ideal points shift to the right. We also document effects for Republicans and Independents and find that overall polarization is similar under both elicitation methods. We conclude with a discussion of our results, and the consequences and tradeoffs of each elicitation method.

Keywords: Survey methods; Polarization; Preference elicitation; Ideal point estimation; Bayesian estimation (search for similar items in EconPapers)
JEL-codes: C1 C83 D7 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11127-018-0558-9

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