Skip to main content Accessibility help
×
Hostname: page-component-848d4c4894-tn8tq Total loading time: 0 Render date: 2024-06-15T20:55:09.306Z Has data issue: false hasContentIssue false

4 - Comparing the Empirical Fit of the Directional and Proximity Models for Voter Utility Functions

Published online by Cambridge University Press:  04 December 2009

Samuel Merrill, III
Affiliation:
Wilkes University, Pennsylvania
Bernard Grofman
Affiliation:
University of California, Irvine
Get access

Summary

All politics … are based on the indifference of the majority.

James Reston, The New York Times (June 12, 1968)

Discriminating between Models

We may assess a voter's evaluation of a candidate through either (1) voter choice, i.e., whom the voter votes for, or (2) voter utility, i.e., the voter's quantitative evaluation of the candidate on some scale. Whom one votes for may be the ultimate question, but utility – which relates to enthusiasm for (or against) a candidate – has important secondary effects. For example, if the value attached to getting one's preferred candidate elected is high enough, the citizen may be motivated not merely to vote but also to participate in politics as an opinion leader, activist, or financial contributor. Moreover, such participatory and contributory activities on the part of one voter may well influence how others vote.

Discrimination between competing models of voter choice may appear more difficult than discriminating among competing models of voter utility, because focusing only on the either-or decision of voter choice makes use of only some of the information available to us about the shape of voter preferences. On the other hand, as we shall see in Chapters 6 and 7, statistical testing of voter choice models may avoid certain methodological difficulties that plague attempts to test models of voter utility. Models that make clearly different predictions about the shape of voter utility functions may have much greater predictive overlap in terms of voter choice (especially for only two alternatives); however, as we will see in Chapter 10, different models may make very different predictions about the spatial configurations of candidates or parties as they respond to voter evaluations.

Type
Chapter
Information
A Unified Theory of Voting
Directional and Proximity Spatial Models
, pp. 52 - 66
Publisher: Cambridge University Press
Print publication year: 1999

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×