Joshua D. Clinton <email@example.com> is Associate Professor of Political Science and Co-Director of the Center for the Study of Democratic Institutions at Vanderbilt University, 301 Calhoun Hall, Box 1817 Station B, Nashville, TN 37235.
To Simulate or NOMINATE?
Version of Record online: 7 JAN 2011
2009 Comparative Legislative Research Center at the University of Iowa
Legislative Studies Quarterly
Volume 34, Issue 4, pages 593–621, November 2009
How to Cite
CLINTON, J. D. and JACKMAN, S. (2009), To Simulate or NOMINATE?. Legislative Studies Quarterly, 34: 593–621. doi: 10.3162/036298009789869691
- Issue online: 7 JAN 2011
- Version of Record online: 7 JAN 2011
Carroll et al. (2009) summarize the similarities and differences between the NOMINATE and IDEAL methods of fitting spatial voting models to binary roll-call data. As those authors note, for the class of problems with which either NOMINATE and the Bayesian quadratic-normal model can be used, the ideal point estimates almost always coincide, and when they do not, the discrepancy is due to the somewhat arbitrary identification and computational constraints imposed by each method. There are, however, many problems for which the Bayesian quadratic-normal model can be easily generalized, so as to address a broad array of questions and take advantage of additional data. Given the nature and source of the differences between NOMINATE and the Bayesian approach—as well as the fact that both approaches are approximations of the decision-making processes being modeled—we believe that it is preferable to choose the more flexible Bayesian approach.