Voters’ Preferences in a Quantum Framework

Polina Khrennikova () and Emmanuel Haven ()
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Polina Khrennikova: University of Leicester
Emmanuel Haven: University of Leicester

A chapter in The Palgrave Handbook of Quantum Models in Social Science, 2017, pp 141-155 from Palgrave Macmillan

Abstract: Abstract Politics is regarded as a vital area of social science and strongly relies on the assumptions of voters’ rationality and as such the stability of preferences (at least in decisions that are made simultaneously). The phenomenon of divided government that has dominated the US political arena for many election periods over the last 40 years is not consistent with the notion of stable preferences of voters. The authors claim that there is no well defined ranking of their preferences on their utility function of “political preferences.” Recently, this problem has been handled by using the novel approach based on the formalism of quantum mechanics. The theory of quantum decision-making is applicable to the modeling of irrational and biased behavior of voters as well as to the nonseparability of their preferences. Irrationality, biases, and nonseparability lead to a deeper uncertainty than classical probabilistic uncertainty. In particular, quantum probability describes well the violation of Bayesian rationality. The authors model this nonclassical uncertainty in voters’ preferences by using elements of the fundamental quantum information structures such as superposition and entanglement. The chapter is an introduction to the quantum modeling of the behavior of an electorate with unstable preferences (contextual preferences) and the authors use one of the most potent theories of adaptive dynamics, namely, the theory of open quantum systems. In this model a voter’s decision is created in the process of interaction with an information bath in which the mass media play the key role.

Keywords: Presidential Election; Belief State; Quantum Model; Open Quantum System; Congressional Election (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1057/978-1-137-49276-0_8

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