Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-12-01T00:56:12.892Z Has data issue: false hasContentIssue false
  • English
  • Français

Specification Issues in Assessing the Moderating Role of Issue Importance: A Comment on Grynaviski and Corrigan (2006)

Published online by Cambridge University Press:  04 January 2017

Neil Malhotra  and
Alexander Tahk
Neil Malhotra*
Affiliation:
Graduate School of Business, Stanford University, 655 Knight Way, Stanford, CA 94305-7298
Alexander Tahk
Affiliation:
Department of Political Science, University of Wisconsin, Madison, 110 North Hall, 1050 Bascom Mall, Madison, WI 53706
*
e-mail: [email protected] (corresponding author)
Get access Rights & Permissions [Opens in a new window]

Abstract

The empirical study of spatial issue voting has experienced a resurgence in recent years due to advances in data collection and research design. Grynaviski and Corrigan make several important contributions to this literature. In this note, we comment on one of Grynaviski and Corrigan's recommendations—to not include a main effect for issue importance when estimating models assessing the interactive relationship between importance and policy proximity. According to the authors, including the main importance term is incorrect because it is not necessary in representing a scale-invariant functional form under some assumptions and is insufficient under others. In deriving their reduced-form expression, the authors produce a model that is unintuitive and inappropriate for most data. Moreover, the restrictions Grynaviski and Corrigan impose on their model can produce perverse empirical predictions. We show that a model including main effect terms for importance is indeed scale invariant and that inclusion of the main importance term is necessary for scale invariance with respect to partial utility functions.

Type
Research Article
Information
Political Analysis , Volume 19 , Issue 3 , Summer 2011 , pp. 342 - 350
Copyright
Copyright © The Author 2011. 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.)

Footnotes

Authors' note: We thank Jon Krosnick, Daniel Schneider, Jonathan Wand, Jeff Grynaviski, Wendy Tam Cho, the editors, and anonymous reviewers for valuable feedback.

References

Aiken, Lenora S., and West, Stephen G. 1991. Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA: Sage Publishing.Google Scholar
Brambor, Thomas, Clark, William Roberts, and Golder, Matt. 2006. Understanding interaction models: Improving empirical analyses. Political Analysis 14: 63–82.Google Scholar
Carter, Michael. 2001. Foundations of mathematical economics. Cambridge, MA: MIT Press.Google Scholar
Downs, Anthony. 1957. An economic theory of democracy. New York: Harper and Row.Google Scholar
Griepentrog, Gary L., Michael Ryan, J., and Douglas Smith, L. 1982. Linear transformations of polynomial regression models. The American Statistician 36: 171–4.Google Scholar
Grynaviski, Jeffrey D., and Corrigan, Bryce E. 2006. Specification issues in proximity models of candidate evaluation (with issue importance). Political Analysis 14: 393–420.Google Scholar
Jessee, Stephen A. 2009. Spatial voting in the 2004 presidential election. American Political Science Review 103: 59–81.Google Scholar
Kalandrakis, Tasos. 2010. Rationalizable voting. Theoretical Economics 5: 93–125.Google Scholar
MacDonald, Stuart Elaine, Rabinowitz, George, and Listhaug, Ola. 2001. Sophistry versus science: On further efforts to rehabilitate the proximity model. Journal of Politics 63: 482–500.Google Scholar
Merrill, Samuel. 1995. Discriminating between the directional and proximity spatial models of electoral competition. Electoral Studies 14(3): 273–87.Google Scholar
Merrill, Samuel, and Grofman, Bernard. 1999. A unified theory of voting: Directional and proximity spatial models. Cambridge, UK: Cambridge University Press.Google Scholar
Rabinowitz, George, and Macdonald, Stuart Elaine. 1989. A directional theory of issue voting. American Political Science Review 83: 93–121.Google Scholar
Tomz, Michael, and Van Houweling, Robert P. 2008. Candidate positioning and voter choice. American Political Science Review 102: 303–18.Google Scholar
Westholm, Anders. 2001. On the return of epicycles: Some crossroads in spatial modeling revisited. Journal of Politics 63: 436–81.Google Scholar