Sophisticated voting under the sequential voting by veto

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12 Scopus citations

Abstract

The research reported here was the first empirical examination of strategic voting under the Sequential Voting by Veto (SVV) voting procedure, proposed by Mueller (1978). According to this procedure, a sequence of n voters must select s out of s+m alternatives (m ≥ n ≥ 2; s > 0). Hence, the number of alternatives exceeds the number of participants by one (n+1). When the ith voter casts her vote, she vetoes the alternative against which a veto has not yet been cast, and the s remaining non-vetoed alternatives are elected. The SVV procedure invokes the minority principle, and it has advantages over all majoritarian procedures; this makes SVV a very desirable means for relatively small groups to make collective decisions. Felsenthal and Machover (1992) pointed out three models of voting under SVV: sincere, optimal, and canonical. The current research investigated, through laboratory experiments, which cognitive model better accounts for the voters' observed behavior and the likelihood of obtaining the optimal outcome as a function of the size of n (when s = 1). The findings suggest that while voters under SVV use all three models, their choice is conditioned by group size. In the small groups (n = 3), the canonical mode was a better predictor than the sincere model. In the larger groups (n = 5), the sincere model was a better predictor than the canonical model. There is also evidence of players' learning during the experiment.

Original languageEnglish
Pages (from-to)343-369
Number of pages27
JournalTheory and Decision
Volume53
Issue number4
DOIs
StatePublished - 1 Dec 2002
Externally publishedYes

Keywords

  • Minority principle
  • Strategic voting
  • Veto
  • Voters' behavior

ASJC Scopus subject areas

  • General Decision Sciences
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Applied Psychology
  • General Social Sciences
  • General Economics, Econometrics and Finance
  • Computer Science Applications

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