Sophisticated Approval Voting, Ignorance Priors, and Plurality Heuristics: A Behavioral Social Choice Analysis in a Thurstonian Framework Michel Regenwetter University of Illinois at Urbana–Champaign Moon-Ho R. Ho Nanyang Technological University Ilia Tsetlin INSEAD This project reconciles historically distinct paradigms at the interface between individual and social choice theory, as well as between rational and behavioral decision theory. The authors combine a utility-maximizing prescriptive rule for sophisticated approval voting with the ignorance prior heuristic from behavioral decision research and two types of plurality heuristics to model approval voting behavior. When using a sincere plurality heuristic, voters simplify their decision process by voting for their single favorite candidate. When using a strategic plurality heuristic, voters strategically focus their attention on the 2 front-runners and vote for their preferred candidate among these 2. Using a hierarchy of Thurstonian random utility models, the authors implemented these different decision rules and tested them statistically on 7 real world approval voting elections. They cross-validated their key findings via a psychological Internet experiment. Although a substantial number of voters used the plurality heuristic in the real elections, they did so sincerely, not strategically. Moreover, even though Thurstonian models do not force such agreement, the results show, in contrast to common wisdom about social choice rules, that the sincere social orders by Condorcet, Borda, plurality, and approval voting are identical in all 7 elections and in the Internet experiment. Keywords: approval voting, behavioral social choice, expected utility, decision heuristics, sophisticated voting Supplemental materials: http://dx.doi.org/10.1037/0033-295X.114.4.994.supp Behavioral decision research has invested decades of intense study into the interface of normative theory and descriptive data in individual decision making, with particular emphasis on heuristics and biases. Behavioral decision research has profoundly influ- enced economics, including, most prominently, game theory (e.g., Camerer, 2003) and finance (e.g., Thaler, 1993). The importance of behavioral decision research was most unambiguously acknowl- edged through D. Kahneman’s 2002 shared Nobel prize in eco- nomics, in particular for his seminal collaborative work with A. Tversky (e.g., Kahneman & Tversky, 1979; Tversky & Kahneman, 1974, 1981). In contrast, social choice theory has yet to fully incorporate behavioral and descriptive methods. Few researchers have attempted to systematically develop and test formal descrip- tive models of collective choice behavior or to integrate insights from behavioral decision research into social choice theory. Our project links the individual, social, normative, and behavioral decision sciences (see Figure 1). The first facet (Quadrant 1 in Figure 1) concerns a prescriptive– normative rule on how to cast an optimal vote in approval voting (AV) elections. In AV, each voter approves of any subset of the candidates. Each candidate in that set (and no other) scores a point from that voter and the winner(s) is (are) the candidate(s) with the highest point total(s), summed over all voters. According to Mer- rill (1981) and Brams and Fishburn (1983), a sophisticated, that is, utility-maximizing, voter ought to cast votes for those and only Michel Regenwetter, Departments of Psychology and Political Science, University of Illinois at Urbana–Champaign; Moon-Ho R. Ho, Division of Psychology, Nanyang Technological University, Singapore; Ilia Tsetlin, Decision Sciences, INSEAD, Fontainebleau, France, and Singapore. This material is based on work supported by the Research Board of the University of Illinois at Urbana–Champaign, National Institute of Mental Health Training Grant Award PHS 2 T32 MH014257 (to Michel Regen- wetter), Air Force Office of Scientific Research Award FA9550-05-1-0356 (to Michel Regenwetter), the Department of Psychology at the University of Illinois, National Sciences and Engineering Research Council of Canada Award RGPIN 298244 (to Moon-Ho R. Ho), the Center for Decision Making and Risk Analysis at INSEAD, and the INSEAD Alumni Fund. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the various funding sources. We thank Steve Brams, Jerome Busemeyer, Nick Chater, Clintin Davis- Stober, Reid Hastie, Bernard Grofman, Tatsuya Kameda, Jean-Franc ¸ois Laslier, Patrick Laughlin, A. A. J. Marley, Samuel Merrill, William Mess- ner, Donald Saari, Robert Sorkin, and Jack Yellott for various helpful comments or discussions, for example, on earlier versions of this article, as well as for pointers to important background information. We are grateful for all approval voting ballots analyzed here and owe special thanks to Jonathan Baron (University of Pennsylvania) for providing data from his Internet experiment on voting methods. Correspondence concerning this article should be addressed to Michel Regenwetter, Department of Psychology, University of Illinois at Urbana– Champaign, 603 East Daniel Street, Champaign, IL 61820. E-mail: regenwet@uiuc.edu Psychological Review Copyright 2007 by the American Psychological Association 2007, Vol. 114, No. 4, 994 –1014 0033-295X/07/$12.00 DOI: 10.1037/0033-295X.114.4.994 994