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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)
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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 

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Footnotes

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

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