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Empirical foundation of valence using Aldrich-McKelvey scaling

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  • Fabian Gouret

    (THEMA - Théorie économique, modélisation et applications - CNRS - Centre National de la Recherche Scientifique - CY - CY Cergy Paris Université)

Abstract

This paper uses data from the 2004 pre-election survey of the American National Election Study to test empirically different ways of incorporating a valence parameter into a Downsian utility function. We call particular attention to the problem of interpersonal incomparability of responses to the liberal-conservative scale, and use Aldrich–McKelvey’s pathbreaking method to obtain accurate distances between respondents and candidates, the key regressors. We find that the utility function the most supported by the empirical evidence, the intensity valence utility function, is the one which permits to make the better predictions for the 2004 presidential election. We also consider counterfactual analyses wherein we test if Bush, the candidate with the highest intensity valence, has dominant strategies which would have insured him to obtain a majority of the popular vote. According to the theory, it is known that the candidate with the highest intensity valence does not have such dominant strategies if the distribution of voters in the policy space is too heterogenous. Nevertheless, we show that the distribution of voters in 2004 is sufficiently homogenous for Bush to have dominant strategies.
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Suggested Citation

  • Fabian Gouret, 2021. "Empirical foundation of valence using Aldrich-McKelvey scaling," Post-Print hal-03637791, HAL.
  • Handle: RePEc:hal:journl:hal-03637791
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    Cited by:

    1. Fabian Gouret, 2024. "Additive valence and the single-crossing property," THEMA Working Papers 2024-05, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.

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    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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