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A New Approach to the Study of Parties Entering Government

Published online by Cambridge University Press:  28 May 2014

Garrett Glasgow  and
Sona N. Golder
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Abstract

Previous studies of the factors that influence the ability of parties to join governments have estimated binary choice models using the parties as the unit of analysis, which inappropriately treats each party in a government formation opportunity as an independent observation (a problem that clustered standard errors do not solve) and does not allow researchers to control for important coalition-level effects. This article demonstrates that a preferred methodological approach is to first estimate a standard multinomial choice model (conditional logit or mixed logit) of coalition formation, using government formation opportunities as the unit of analysis and potential governments as the choice alternatives. The probabilities of parties joining governments can then be recovered by simply summing the probabilities for the potential governments that contain each party. An empirical example shows how the substantive conclusions about a party's likelihood of entering office can change depending on the methodological approach taken.

Type
Articles
Information
British Journal of Political Science , Volume 45 , Issue 4 , October 2015 , pp. 739 - 754
Copyright
Copyright © Cambridge University Press 2014 

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Footnotes

*

Department of Political Science, University of California, Santa Barbara (email: [email protected]); Department of Political Science, Pennsylvania State University (email: [email protected]). We gratefully acknowledge support for this project from the Research Center (SFB) 884 ‘Political Economy of Reforms’, funded by the German Research Foundation (DFG). We thank also Matt Golder and the audience at the 2012 Annual Meeting of the European Political Science Association for helpful comments on this article. The data, codebook and all computer code necessary to replicate the results and figures in this analysis will be made publicly available on the authors’ homepages upon publication. Data replication sets are available at http://dx.doi.org/doi: 10.1017/S0007123414000015.

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