Modeling Preferences Using Roll Call Votes in Parliamentary Systems

2016 ◽  
Vol 24 (2) ◽  
pp. 189-210 ◽  
Author(s):  
Thomas Bräuninger ◽  
Jochen Müller ◽  
Christian Stecker

Models of ideal point estimation usually build on the assumption of spatial preferences. This ignores legislators' non-policy incentives and is thus likely to produce implausible results for many legislatures. We study this problem in parliamentary systems and develop a model of roll call voting that considers both thepolicyand the non-policy,tacticalincentives of legislators. We go on to show how the relative weight of these policy and tactical incentives is influenced by the identity of the mover and characteristics of the motion. Analyses of two data sets of 2174 roll call votes in German state legislatures and 3295 roll call votes in the British House of Commons result in three main findings. First, we show that tactical incentives may be more important than policy incentives, and second, that the importance of tactical incentives varies with the importance of motions. Third, there are interesting twists: backbench private members' bills may reverse tactical incentives whereas proposals from anti-system parties are virtually always rejected by moderate parties, rendering these votes uninformative. Our findings have implications for ideal point estimation in parliamentary systems, as well as for research on separation of power systems.

2009 ◽  
Vol 1 (1) ◽  
pp. 67-96 ◽  
Author(s):  
Mark P. Jones ◽  
Wonjae Hwang ◽  
Juan Pablo Micozzi

This article employs roll call vote data and Bayesian ideal point estimation to examine inter-party dynamics in the Argentine Chamber of Deputies between 1989 and 2007. It highlights the presence in the Argentine Congress of a strong government vs. opposition dimension as well as identifies the relative position on this dimension, vis-à-vis the governing party, of the most prominent non-governing parties. Special attention is paid to the evolution of inter-party legislative dynamics during Argentina's brief experience with coalition government (1999-2001) and to party behavior in the Chamber during the final two years of President Néstor Kirchner's term in office (2005-07).


2018 ◽  
Vol 26 (2) ◽  
pp. 131-146 ◽  
Author(s):  
Alexander Tahk

Existing approaches to estimating ideal points offer no method for consistent estimation or inference without relying on strong parametric assumptions. In this paper, I introduce a nonparametric approach to ideal-point estimation and inference that goes beyond these limitations. I show that some inferences about the relative positions of two pairs of legislators can be made with minimal assumptions. This information can be combined across different possible choices of the pairs to provide estimates and perform hypothesis tests for all legislators without additional assumptions. I demonstrate the usefulness of these methods in two applications to Supreme Court data, one testing for ideological movement by a single justice and the other testing for multidimensional voting behavior in different decades.


Author(s):  
Sylvester Eijffinger ◽  
Ronald Mahieu ◽  
Louis Raes

In this chapter we suggest to use Bayesian ideal point estimation to analyze voting in monetary policy committees. Using data from the Riksbank we demonstrate what this entails and we compare ideal point estimates with the results from traditional approaches. We end by suggesting possible extensions.


2018 ◽  
Vol 27 (1) ◽  
pp. 69-89 ◽  
Author(s):  
Max Goplerud

This paper creates a multinomial framework for ideal point estimation (mIRT) using recent developments in Bayesian statistics. The core model relies on a flexible multinomial specification that includes most common models in political science as “special cases.” I show that popular extensions (e.g., dynamic smoothing, inclusion of covariates, and network models) can be easily incorporated whilst maintaining the ability to estimate a model using a Gibbs Sampler or exact EM algorithm. By showing that these models can be written and estimated using a shared framework, the paper aims to reduce the proliferation of bespoke ideal point models as well as extend the ability of applied researchers to estimate models quickly using the EM algorithm. I apply this framework to a thorny question in scaling survey responses—the treatment of nonresponse. Focusing on the American National Election Study (ANES), I suggest that a simple but principled solution is to treat questions as multinomial where nonresponse is a distinct (modeled) category. The exploratory results suggest that certain questions tend to attract many more invalid answers and that many of these questions (particularly when signaling out particular social groups for evaluation) are masking noncentrist (typically conservative) beliefs.


2009 ◽  
Vol 17 (3) ◽  
pp. 276-290 ◽  
Author(s):  
Michael Peress

Ideal point estimation is a topic of central importance in political science. Published work relying on the ideal point estimates of Poole and Rosenthal for the U.S. Congress is too numerous to list. Recent work has applied ideal point estimation to the state legislatures, Latin American chambers, the Supreme Court, and many other chambers. Although most existing ideal point estimators perform well when the number of voters and the number of bills is large, some important applications involve small chambers. We develop an estimator that does not suffer from the incidental parameters problem and, hence, can be used to estimate ideal points in small chambers. Our Monte Carlo experiments show that our estimator offers an improvement over conventional estimators for small chambers. We apply our estimator to estimate the ideal points of Supreme Court justices in a multidimensional space.


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