A Caltech Library Service

Theory Driven Bias in Ideal Point Estimates—A Monte Carlo Study

Hirsch, Alexander V. (2011) Theory Driven Bias in Ideal Point Estimates—A Monte Carlo Study. Political Analysis, 19 (1). pp. 87-102. ISSN 1047-1987.

Full text is not posted in this repository. Consult Related URLs below.

Use this Persistent URL to link to this item:


This paper analyzes the use of ideal point estimates for testing pivot theories of lawmaking such as Krehbiel's (1998, Pivotal politics: A theory of U.S. lawmaking. Chicago, IL: University of Chicago) pivotal politics and Cox and McCubbins's (2005, Setting the Agenda: Responsible Party Government in the U.S. House of Representations. New York: Cambridge University Press) party cartel model. Among the prediction of pivot theories is that all pivotal legislators will vote identically on all successful legislation. Clinton (2007, Lawmaking and roll calls. Journal of Politics 69:455–67) argues that the estimated ideal points of the pivotal legislators are therefore predicted to be statistically indistinguishable and false when estimated from the set of successful final passage roll call votes, which implies that ideal point estimates cannot logically be used to test pivot theories. I show using Monte Carlo simulation that when pivot theories are augmented with probabilistic voting, Clinton's prediction only holds in small samples when voting is near perfect. I furthermore show that the predicted bias is unlikely to be consequential with U.S. Congressional voting data. My analysis suggests that the methodology of estimating ideal points to compute theoretically relevant quantities for empirical tests is not inherently flawed in the case of pivot theories.

Item Type:Article
Related URLs:
URLURL TypeDescription
Additional Information:© 2010 The Author. Published by Oxford University Press on behalf of the Society for Political Methodology. The author gratefully acknowledges Keith Krehbiel, Kenneth W. Shotts, Marc Meredith, Michael Peress, Maggie Peters, Carlos Lever, Marcello Miccoli, Ruth Kricheli, Zac Peskowitz, and anonymous referees at Political Analysis for helpful comments and advice. The author would especially like to acknowledge Josh Clinton, whose generous advice significantly improved this paper and went well beyond the call of duty. Supplementary materials for this article are available on the Political Analysis Web site.
Issue or Number:1
Record Number:CaltechAUTHORS:20190506-142217393
Persistent URL:
Official Citation:Hirsch, A. (2011). Theory Driven Bias in Ideal Point Estimates—A Monte Carlo Study. Political Analysis, 19(1), 87-102. doi:10.1093/pan/mpq028
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:95257
Deposited By: Tony Diaz
Deposited On:06 May 2019 21:27
Last Modified:03 Oct 2019 21:11

Repository Staff Only: item control page