Small Chamber Ideal Point Estimation

2009 ◽  
Vol 17 (3) ◽  
pp. 276-290 ◽  
Author(s):  
Michael Peress
Keyword(s):  
Supreme Court ◽  
Latin American ◽  
Ideal Point ◽  
Point Estimation ◽  
Multidimensional Space ◽  
Incidental Parameters ◽  
Ideal Points ◽  
Point Estimators ◽  
The Ideal ◽  
Ideal Point Estimation

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.

Nonparametric Ideal-Point Estimation and Inference

2018 ◽  
Vol 26 (2) ◽  
pp. 131-146 ◽  
Author(s):  
Alexander Tahk
Keyword(s):  
Supreme Court ◽  
Voting Behavior ◽  
Ideal Point ◽  
Point Estimation ◽  
The Other ◽  
Hypothesis Tests ◽  
Consistent Estimation ◽  
Nonparametric Approach ◽  
Ideal Points ◽  
Ideal Point Estimation

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.

Ideal Point Estimation in Political Hierarchies: A Framework and an Application to the US Executive Branch

2019 ◽  
Author(s):  
Alex Acs
Keyword(s):  
Ideal Point ◽  
The United States ◽  
Executive Branch ◽  
Point Estimation ◽  
The Us ◽  
Political Hierarchy ◽  
Public Bureaucracy ◽  
Ideal Points ◽  
Using Data ◽  
The Ideal

Abstract This article develops a procedure for estimating the ideal points of actors in a political hierarchy, such as a public bureaucracy. The procedure is based on a spatial auditing model and is motivated by the idea that while agents within a political hierarchy are typically segregated in different policy fiefdoms, they are bound to a common principal that can scrutinize their policy proposals through selective reviews, or audits. The theoretical model shows how a principal’s decision to audit an agent’s proposal can reveal both actors’ spatial preferences, despite the strategic nature of the interaction. Empirical identification of the ideal points comes from leveraging settings where elections replace principals over time, but not agents. Although the procedure is quite general, I provide an illustration using data on federal regulatory policymaking in the United States and recover ideal point estimates for presidents and agencies across three administrations.

Unpredictable Voters in Ideal Point Estimation

2010 ◽  
Vol 18 (2) ◽  
pp. 151-171 ◽  
Author(s):  
Benjamin E. Lauderdale
Keyword(s):  
Voting Behavior ◽  
Ideal Point ◽  
Error Variance ◽  
Point Estimation ◽  
Point Estimator ◽  
Ideal Points ◽  
Variance Parameters ◽  
Point Estimators ◽  
Low Dimensional ◽  
Specific Error

Ideal point estimators are typically based on an assumption that all legislators are equally responsive to modeled dimensions of legislative disagreement; however, particularistic constituency interests and idiosyncrasies of individual legislators introduce variation in the degree to which legislators cast votes predictably. I introduce a Bayesian heteroskedastic ideal point estimator and demonstrate by Monte Carlo simulation that it outperforms standard homoskedastic estimators at recovering the relative positions of legislators. In addition to providing a refinement of ideal point estimates, the heteroskedastic estimator recovers legislator-specific error variance parameters that describe the extent to which each legislator's voting behavior is not conditioned on the primary axes of disagreement in the legislature. Through applications to the roll call histories of the U.S. Congress, the E.U. Parliament, and the U.N. General Assembly, I demonstrate how to use the heteroskedastic estimator to study substantive questions related to legislative incentives for low-dimensional voting behavior as well as diagnose unmodeled dimensions and nonconstant ideal points.

scholarly journals Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953–1999

2002 ◽  
Vol 10 (2) ◽  
pp. 134-153 ◽  
Author(s):  
Andrew D. Martin ◽  
Kevin M. Quinn
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Supreme Court ◽  
Ideal Point ◽  
Point Estimation ◽  
Judicial Behavior ◽  
Preference Change ◽  
Ideal Points ◽  
The U.S

At the heart of attitudinal and strategic explanations of judicial behavior is the assumption that justices have policy preferences. In this paper we employ Markov chain Monte Carlo methods to fit a Bayesian measurement model of ideal points for all justices serving on the U.S. Supreme Court from 1953 through 1999. We are particularly interested in determining to what extent ideal points of justices change throughout their tenure on the Court. This is important because judicial politics scholars oftentimes invoke preference measures that are time invariant. To investigate preference change, we posit a dynamic item response model that allows ideal points to change systematically over time. Additionally, we introduce Bayesian methods for fitting multivariate dynamic linear models to political scientists. Our results suggest that many justices do not have temporally constant ideal points. Moreover, our ideal point estimates outperform existing measures and explain judicial behavior quite well across civil rights, civil liberties, economics, and federalism cases.

Ideal Point Estimation with a Small Number of Votes: A Random-Effects Approach

2001 ◽  
Vol 9 (3) ◽  
pp. 192-210 ◽  
Author(s):  
Michael Bailey
Keyword(s):  
Monte Carlo ◽  
Random Effects ◽  
Bayesian Approach ◽  
Fixed Effects ◽  
Ideal Point ◽  
Point Estimation ◽  
Standard Errors ◽  
Fixed Effects Models ◽  
Ideal Points ◽  
Ideal Point Estimation

Many conventional ideal point estimation techniques are inappropriate when only a limited number of votes are available. This paper presents a covariate-based random-effects Bayesian approach that allows scholars to estimate ideal points based on fewer votes than required for fixed-effects models. Using covariates brings more information to bear on the estimation; using a Bayesian random-effects approach avoids incidental parameter problems. Among other things, the method allows us to estimate directly the effect of covariates such as party on preferences and to estimate standard errors for ideal points. Monte Carlo results, an empirical application, and a discussion of further applications demonstrate the usefulness of the method.

scholarly journals Measuring Judicial Ideal Points in New Democracies: The Case of the Philippines

2014 ◽  
Vol 1 (1) ◽  
pp. 125-164 ◽  
Author(s):  
Lucia Dalla Pellegrina ◽  
Laarni Escresa ◽  
Nuno Garoupa
Keyword(s):  
Supreme Court ◽  
Judicial Politics ◽  
The Philippines ◽  
Interesting Case ◽  
Presidential Appointments ◽  
The Supreme Court ◽  
The Us ◽  
Ideal Points ◽  
The Empirical Analysis ◽  
The Ideal

AbstractThis paper extends the empirical analysis on the determinants of judicial behaviour by measuring the ideal points for the Justices of the Philippine Supreme Court for 1986−2010. The Philippines is an interesting case given the US influence in designing the Supreme Court while the political and social context differs significantly. The estimated ideal points allow us to focus on political coalitions based on presidential appointments. We find strong evidence to support the existence of such coalitions along a government-opposition policy space. Implications for comparative judicial politics are discussed.

Monetary Policy Committees and Voting Behavior

2019 ◽  
pp. 38-58
Author(s):  
Sylvester Eijffinger ◽  
Ronald Mahieu ◽  
Louis Raes
Keyword(s):  
Monetary Policy ◽  
Voting Behavior ◽  
Ideal Point ◽  
Point Estimation ◽  
Point Estimates ◽  
Monetary Policy Committees ◽  
Using Data ◽  
Traditional Approaches ◽  
Ideal Point Estimation

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.

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