Hostname: page-component-7b7567c8c-7pwfn Total loading time: 0 Render date: 2026-11-12T16:52:41.812Z Has data issue: false hasContentIssue false
  • English
  • Français

Specification Issues in Proximity Models of Candidate Evaluation (with Issue Importance)

Published online by Cambridge University Press:  04 January 2017

Jeffrey D. Grynaviski and
Bryce E. Corrigan
Jeffrey D. Grynaviski*
Affiliation:
Department of Political Science, University of Chicago, 5828 S. University Ave., Chicago, IL 60637
Bryce E. Corrigan
Affiliation:
Department of Political Science, University of Michigan, 5700 Haven Hall, 505 S. State Street, Ann Arbor, MI 48109-1045. e-mail: becorrig@umich.edu
*
e-mail: grynaviski@uchicago.edu (corresponding author)
Get accessRights & Permissions [Opens in a new window]

Abstract

The use of the proximity model to represent the relationship between citizens' policy attitudes and the positions of candidates on the issues of the day has considerable appeal because it offers a bridge between theoretical models of political behavior and empirical work. However, there is little consensus among applied researchers about the appropriate representation of voter behavior with respect to the measurement of issue distance, candidate location, or whether to allow heterogeneity in the weight that each individual places on particular issues. Each of these choices suggests a different, and reasonably complicated, nonlinear relationship between voter utility and candidate and voter issue positions which may have a meaningful influence on the substantive conclusions drawn by the researcher. Yet, little attention has been given to the best way to represent the proximity model in applied work. The purpose of this paper is to identify which forms of the proximity model work best, with particular consideration given to the identification of functional forms that are invariant to the choice of scale for the independent variables.

Information

Type
Research Article
Information
Political Analysis , Volume 14 , Issue 4 , Autumn 2006, pp. 393 - 420
Copyright
Copyright © The Author 2006. Published by Oxford University Press on behalf of the Society for Political Methodology 

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.)

Article purchase

Temporarily unavailable

Footnotes

Authors' note: We thank the anonymous reviewers at Political Analysis for helpful comments on this paper. Data for this project are provided by the Inter-University Consortium for Political and Social Research. Supplementary materials and data are available on the Political Analysis Web site.

References

Akaike, H. 1973. Information theory and an extension of the maximum likelihood principle. In Second International Symposium on Information Theory, ed. Petrox, B. and Caski, F., 267–81. Budapest: Akademia Kaido.Google Scholar
Aldrich, John H., Borgida, Eugene, and Sullivan, John. 1989. Foreign affairs and issue voting: Do presidential candidates ‘waltz before a blind audience?’ American Journal of Political Science 83: 123–41.Google Scholar
Aldrich, John H., Gronke, Paul, and Grynaviski, Jeffrey. 1999. Policy, personality, and presidential performance. Paper presented at the 1999 Midwest Political Science Association meetings, Chicago, IL.Google Scholar
Brambor, Thomas, Clark, William, and Golder, Matt. 2006. Understanding interaction models: Improving empirical analyses. Political Analysis 14: 63–82.Google Scholar
Cohen, J. 1978. Partialed products are interactions; partialed powers are curve components. Psychological Bulletin 85: 858–66.Google Scholar
Converse, Philip. 1964. The nature of belief systems in mass publics. In Ideology and discontent, ed. Apter, David. New York: Free Press.Google Scholar
Converse, Philip, and Markus, Gregory. 1979. Plus ca change: The new CPS election study panel. American Political Science Review 73: 32–49.Google Scholar
Corrigan, Bryce, and Grynaviski, Jeffrey. 2005. The endogenous estimation of issue importance: Mixture models of heterogeneity in candidate evaluation. A Paper presented at the Midwest Political Science Association meetings, Chicago, IL.Google Scholar
Dahl, Robert. 1956. A preface to democratic theory. Chicago, IL: University of Chicago Press.Google Scholar
Davis, Otto, Hinich, Melvin, and Ordeshook, Peter. 1970. An expository development of a mathematical model of the electoral process. American Political Science Review 64: 426–8.Google Scholar
Eagley, Alice, and Chaiken, Shelly. 1998. Attitude structure and function. In The handbook of social psychology. 4th ed. Vol. 1, ed. Gilbert, D., Frist, S. T., and Lindzey, G., 269–313. New York: McGraw Hill.Google Scholar
Enelow, James, Hinich, Melvin, and Mendell, Nancy. 1986. An empirical evaluation of alternative spatial models of elections. Journal of Politics 48: 675–93.Google Scholar
Enelow, James, Mendell, Nancy, and Ramesh, Subha. 1988. A comparison of two distance metrics through regression diagnostics of a model of relative candidate evaluation. Journal of Politics 50: 1057–71.Google Scholar
Funk, Carolyn. 1999. Bringing the candidate into models of candidate evaluation. Journal of Politics 61: 700–20.Google Scholar
Gershkoff, Amy. 2005. How issue interest can save the American public. Paper presented at the 2005 Midwest Political Science Association meetings, Chicago, IL (August 25, 2005 revision).Google Scholar
Grynaviski, Jeffrey. 2003. Do issue publics exist? An application of Bayesian mixture models. A Paper presented at the American Political Science Association meetings, Philadelphia, PA.Google Scholar
Hill, Jennifer, and Kriesi, Hanspeter. 2001. An extension and test of converse’ ‘black and white’ model of response stability. American Political Science Review 95: 397–413.Google Scholar
Hinich, Melvin H., and Munger, Michael C. 1997. Analytical politics. Cambridge: Cambridge University Press.Google Scholar
Hutchings, Vincent. 2003. Public opinion and democratic accountability. Princeton, NJ: Princeton University Press.Google Scholar
Kinder, Donald. 1986. Presidential character revisited. In Political cognition, ed. Lau, Richard and Sears, David. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
King, G., Honaker, J., Joseph, A., and Scheve, K. 2001. Analyzing incomplete political science data: An alternative algorithm to multiple imputation. The American Political Science Review 95: 49–69.Google Scholar
Krosnick, Jon A. 1988. The role of attitude importance in social evaluation: A study of policy preferences, presidential candidate evaluations, and voting behavior. Journal of Personality and Social Psychology 55: 196–210.Google Scholar
Krosnick, Jon A. 1989. Attitude importance and attitude change. Journal of Experimental Social Psychology 24: 240–55.Google Scholar
Krosnick, Jon A. 1990. Government policy and citizen passion: A study of issue publics in contemporary America. Political Behavior 12: 59–92.Google Scholar
Macdonald, Stuart Elaine, Rabinowitz, George, and Listhaug, Ola. 2001. Sophistry versus science: On further efforts to rehabilitate the proximity model. The Journal of Politics 63: 482–500.Google Scholar
Miller, Joanne, and Peterson, David. 2004. Theoretical and empirical implications of attitude strength. Journal of Politics 66: 847–67.Google Scholar
Miller, Warren, and Shanks, Merrill. 1996. The new American voter. Cambridge, MA: Harvard University Press.Google Scholar
Niemi, Richard G., and Bartels, Larry M. 1985. New measures of issue salience. Journal of Politics 47: 1212–20.Google Scholar
Page, Benjamin I., and Jones, C. C. 1979. Reciprocal effects of policy preferences, party loyalties, and the vote. American Political Science Review 73: 1071–89.Google Scholar
Pennock, J. R. 1979. Democratic political theory. Princeton, NJ: Princeton University Press.Google Scholar
Peterson, David. 2004. Certainty or accessibility: Attitude strength in candidate evaluations. American Journal of Political Analysis 48: 513–20.Google Scholar
Rabinowitz, George, Prothro, James W., and Jacoby, William. 1982. Salience as a factor in the impact of issues on candidate evaluation. Journal of Politics 44: 41–63.Google Scholar
Raftery, A. E. 1995. Bayesian model selection in social research (with discussion). In Sociological methodology 1995, ed. Marsden, P. V., 411–27. Cambridge, MA: Blackwell.Google Scholar
Rahn, Wendy. 1995. Candidate evaluation in complex information environments: Cognitive organization and comparison process. In Political judgement, ed. Lodge, Milton and McGraw, Kathleen. Ann Arbor: University of Michigan Press.Google Scholar
Rahn, Wendy, Aldrich, John, Borgida, Eugene, and Sullivan, John. 1990. A social cognitive model of candidate appraisal. In Information and democratic process, ed. Ferejohn, John and Kuklinski, James. Chicago, IL: University of Chicago Press.Google Scholar
Repass, David. 1971. Issue salience and party choice. American Political Science Review 65: 389–400.Google Scholar
Rubin, Donald. 1987. Multiple imputation for nonresponse in surveys. New York: Wiley.Google Scholar
Schafer, Joseph L. 1997. Analysis of incomplete multivariate data. London: Chapman and Hall.Google Scholar
Schwarz, G. 1978. Estimating the dimension of a model. Annals of Statistics 6: 461–64.Google Scholar
Visser, Penny, Bizer, George, and Krosnick, Jon. 2003. Distinguishing the cognitive and behavioral consequences of attitude importance and certainty. Journal of Experimental Social Psychology 39: 118–41.Google Scholar
Westholm, Anders. 2001. On the return of epicycles: Some crossroads in spatial modeling revisited. Journal of Politics 63: 436–81.Google Scholar
Supplementary material: PDF

Grynaviski and Corrigan Supplementary Material

Supplementary Material

Download Grynaviski and Corrigan Supplementary Material(PDF)
PDF 137 KB