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Fuzzy Social Choice Models

Explaining the Government Formation Process

  • Peter C. Casey
  • Michael B. Gibilisco
  • Carly A. Goodman
  • Kelly Nelson Pook
  • John N. Mordeson
  • Mark J. Wierman
  • Terry D. Clark

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 318)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Peter C. Casey, Michael B. Gibilisco, Carly A. Goodman, Kelly Nelson Pook, John N. Mordeson, Mark J. Wierman et al.
    Pages 1-11
  3. Peter C. Casey, Michael B. Gibilisco, Carly A. Goodman, Kelly Nelson Pook, John N. Mordeson, Mark J. Wierman et al.
    Pages 13-31
  4. Peter C. Casey, Michael B. Gibilisco, Carly A. Goodman, Kelly Nelson Pook, John N. Mordeson, Mark J. Wierman et al.
    Pages 33-50
  5. Peter C. Casey, Michael B. Gibilisco, Carly A. Goodman, Kelly Nelson Pook, John N. Mordeson, Mark J. Wierman et al.
    Pages 51-80
  6. Peter C. Casey, Michael B. Gibilisco, Carly A. Goodman, Kelly Nelson Pook, John N. Mordeson, Mark J. Wierman et al.
    Pages 81-128
  7. Peter C. Casey, Michael B. Gibilisco, Carly A. Goodman, Kelly Nelson Pook, John N. Mordeson, Mark J. Wierman et al.
    Pages 129-147
  8. Peter C. Casey, Michael B. Gibilisco, Carly A. Goodman, Kelly Nelson Pook, John N. Mordeson, Mark J. Wierman et al.
    Pages 149-171
  9. Back Matter
    Pages 173-183

About this book

Introduction

This book explores the extent to which fuzzy set logic can overcome some of the shortcomings of public choice theory, particularly its inability to provide adequate predictive power in empirical studies. Especially in the case of social preferences, public choice theory has failed to produce the set of alternatives from which collective choices are made.  The book presents empirical findings achieved by the authors in their efforts to predict the outcome of government formation processes in European parliamentary and semi-presidential systems.  Using data from the Comparative Manifesto Project (CMP), the authors propose a new approach that reinterprets error in the coding of CMP data as ambiguity in the actual political positions of parties on the policy dimensions being coded. The range of this error establishes parties’ fuzzy preferences. The set of possible outcomes in the process of government formation is then calculated on the basis of both the fuzzy Pareto set and the fuzzy maximal set, and the predictions are compared with those made by two conventional approaches as well as with the government that was actually formed. The comparison shows that, in most cases, the fuzzy approaches outperform their conventional counterparts.

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Keywords

CMP project Collective choices Comparative Manifesto Project Fuzzy maximal set Fuzzy multi-dimensional models Fuzzy one-dimensional models Fuzzy preferences Fuzzy public choice models Public choice theory Weighted fuzzy models

Authors and affiliations

  • Peter C. Casey
    • 1
  • Michael B. Gibilisco
    • 2
  • Carly A. Goodman
    • 3
  • Kelly Nelson Pook
    • 4
  • John N. Mordeson
    • 5
  • Mark J. Wierman
    • 6
  • Terry D. Clark
    • 7
  1. 1.Department of Political ScienceWashington University in St. LouisSt. LouisUSA
  2. 2.Department of Political ScienceUniversity of RochesterRochesterUSA
  3. 3.West CorporationCreighton UniversityOmahaUSA
  4. 4.Department of Political ScienceCreighton UniversityOmahaUSA
  5. 5.Department of MathematicsCreighton UniversityOmahaUSA
  6. 6.Computer Science and InformaticsCreighton UniversityOmahaUSA
  7. 7.Department of Political ScienceCreighton UniversityOmahaUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-08248-6
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-08247-9
  • Online ISBN 978-3-319-08248-6
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site
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