Measuring Bias and Uncertainty in DW-NOMINATE Ideal Point Estimates via the Parametric Bootstrap

2009 ◽  
Vol 17 (3) ◽  
pp. 261-275 ◽  
Author(s):  
Royce Carroll ◽  
Jeffrey B. Lewis ◽  
James Lo ◽  
Keith T. Poole ◽  
Howard Rosenthal
Keyword(s):  
Political Science ◽  
Ideal Point ◽  
Parametric Bootstrap ◽  
Standard Errors ◽  
Point Estimates ◽  
Ideal Points ◽  
Measuring Bias ◽  
The U.S ◽  
Over Time

DW-NOMINATE scores for the U.S. Congress are widely used measures of legislators' ideological locations over time. These scores have been used in a large number of studies in political science and closely related fields. In this paper, we extend the work of Lewis and Poole (2004) on the parametric bootstrap to DW-NOMINATE and obtain standard errors for the legislator ideal points. These standard errors are in the range of 1%–4% of the range of DW-NOMINATE coordinates.

Measuring Bias and Uncertainty in Ideal Point Estimates via the Parametric Bootstrap

2004 ◽  
Vol 12 (2) ◽  
pp. 105-127 ◽  
Author(s):  
Jeffrey B. Lewis ◽  
Keith T. Poole
Keyword(s):  
Ideal Point ◽  
Parametric Bootstrap ◽  
Two Dimensions ◽  
Standard Errors ◽  
Legislative Politics ◽  
Political Methodology ◽  
Working Paper ◽  
Political Analysis ◽  
Measuring Bias ◽  
Quantities Of Interest

Over the last 15 years a large amount of scholarship in legislative politics has used NOMINATE or other similar methods to construct measures of legislators' ideological locations. These measures are then used in subsequent analyses. Recent work in political methodology has focused on the pitfalls of using such estimates as variables in subsequent analysis without explicitly accounting for their uncertainty and possible bias (Herron and Shotts 2003, Political Analysis 11:44–64). This presents a problem for those employing NOMINATE scores because estimates of their unconditional sampling uncertainty or bias have until now been unavailable. In this paper, we present a method of forming unconditional standard error estimates and bias estimates for NOMINATE scores using the parametric bootstrap. Standard errors are estimated for the 90th U.S. Senate in two dimensions. Standard errors of first—dimension placements are in the 0.03 to 0.08 range. The results are compared with those obtained using the Markov chain Monte Carlo estimator of Clinton et al. (2002, Stanford University Working Paper). We also show how the bootstrap can be used to construct standard errors and confidence intervals for auxiliary quantities of interest such as ranks and the location of the median senator.

Measuring Bias and Uncertainty in DW-NOMINATE Ideal Point Estimates via the Parametric Bootstrap

2008 ◽  
Author(s):  
Royce Carroll ◽  
Jeffrey B. Lewis ◽  
James Lo ◽  
Keith T. Poole ◽  
Howard Rosenthal
Keyword(s):  
Ideal Point ◽  
Parametric Bootstrap ◽  
Point Estimates ◽  
Measuring Bias

Valuing Policy Alternatives: A Generalization

2003 ◽  
Vol 11 (4) ◽  
pp. 397-418 ◽  
Author(s):  
Nathan Dietz ◽  
Lawrence S. Rothenberg
Keyword(s):  
Political Science ◽  
Predictive Accuracy ◽  
Ideal Point ◽  
Standard Errors ◽  
Parameter Estimates ◽  
Policy Alternatives ◽  
Point Estimates ◽  
Utility Models ◽  
The Impact ◽  
Consistent Parameter

Those interested in political phenomena such as voting have found random utility models, originally developed for decisions such as transportation choice, especially attractive, as the underlying model can yield a statistical model with a few simple, realistic assumptions. Unfortunately, such models have proven difficult to apply to situations with more than two votes and three alternatives or an unknown cutpoint. Additionally, as we show, standard applications of such models to voting, while producing consistent parameter estimates, yield standard errors that are too small and, due to a failure to employ all relevant theoretical information, biased ideal point estimates. We specify a general model applicable to any number of votes and alternatives, with correct standard errors and unbiased ideal point estimates. We apply this model to a number of cases studied by previous scholars involving legislative voting over the minimum wage: (1) when there are two votes and two known cutpoints (K. Krehbiel and D. Rivers, American Journal of Political Science, 1988, 32, 1151–1174); (2) when there are three votes and three known cutpoints (J. Wilkerson, American Journal of Political Science, 1991, 35, 613–623); and (3) when there are three votes but where one cutpoint is unknown given a lack of knowledge about the impact of a policy (J. Wilkerson, American Journal of Political Science, 1991, 35, 613–623) or the possibility of sophisticated voting (C. Volden, Journal of Politics, 1998, 60, 149–173). We show that in various contexts our analysis improves on existing methods, yielding consistent and efficient ideal point estimates and a better-fitting model with improved predictive accuracy.

scholarly journals Change We Can Believe In? Using Political Science to Predict Policy Change in the Obama Presidency

2009 ◽  
Vol 42 (02) ◽  
pp. 329-333 ◽  
Author(s):  
Jonathan Woon
Keyword(s):  
Political Science ◽  
Policy Change ◽  
Presidential Election ◽  
Ideal Point ◽  
Congressional Elections ◽  
Congressional Election ◽  
Partisan Polarization ◽  
Point Estimates

Based on the results of the 2008 presidential and congressional elections, an analysis using theories and methods of modern political science (pivotal politics theory, ideal point estimates, and bootstrap simulations) suggests that the conditions are ripe for real policy change. Specifically, we should expect policies to move significantly in a liberal direction, few or no policies should move in a conservative direction, and many of the outcomes will be moderate or somewhat to the left of center (rather than far left). Furthermore, the predictions depend as much on partisan polarization and the results of the congressional election as they do on the outcome of presidential election itself.

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

2011 ◽  
Vol 19 (1) ◽  
pp. 87-102 ◽  
Author(s):  
Alexander V. Hirsch
Keyword(s):  
New York ◽  
Monte Carlo ◽  
Ideal Point ◽  
Monte Carlo Study ◽  
Small Samples ◽  
Party Government ◽  
Congressional Voting ◽  
Cambridge University ◽  
Point Estimates ◽  
Ideal Points

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.

scholarly journals Primaries and Candidates: Examining the Influence of Primary Electorates on Candidate Ideology

2015 ◽  
Vol 5 (2) ◽  
pp. 397-408 ◽  
Author(s):  
Lindsay Nielson ◽  
Neil Visalvanich
Keyword(s):  
Ideal Point ◽  
The United States ◽  
Primary Elections ◽  
Science Literature ◽  
Primary Election ◽  
Point Estimates ◽  
Level Data ◽  
Ideal Points ◽  
Selection Of

Primary elections in the United States have been under-studied in the political science literature. Using new data to estimate the ideal points of primary election candidates and constituents, we examine the link between the ideological leanings of primary electorates and the ideological orientation of US congressional candidates. We use district-level data from the Cooperative Congressional Election Study and ideal point estimates for congressional primary election candidates to examine the role of primary electorate ideology in the selection of party nominees. We find that more extreme Republicans are more likely to win their party’s primary and that Republican and Democratic candidates are responsive to different electoral constituencies.

scholarly journals Can you bury ideology? An empirical analysis of the ideal points of the Ministers of Brazil’s Supremo Tribunal Federal

2017 ◽  
Vol 17 (68) ◽  
pp. 43-59
Author(s):  
Alexander Hudson ◽  
Ivar Alberto Hartmann
Keyword(s):  
Empirical Analysis ◽  
Representative Sample ◽  
Ideal Point ◽  
Interesting Case ◽  
Judicial Behavior ◽  
Four Dimensions ◽  
Point Estimates ◽  
Ideal Points ◽  
The Ideal

Brazil's Supremo Tribunal Federal (STF) is an especially interesting case for scholars with an interest in judicial behavior. The justices of the STF rule in tens of thousands of cases per year, in a great variety of legal disputes. The ideological breakdown of the STF remains puzzling. Observers of the STF find that a single left-right dimension is entirely inadequate to describe the voting coalitions that form in the court. In this paper, we utilize a new dataset covering a representative sample of all cases decided by the STF between 1992 and 2013. The first important finding is that the voting patterns of the STF show that at least four dimensions are necessary to describe the justices' ideal points. We then estimate ideal points for 23 justices on each of four dimensions, and associate these dimensions with the dominant areas of law with which the STF deals. Finally, we seek to use these ideal point estimates to compare the votes of the justices in key cases with their broader voting pattern.

Closing the Deal: Negotiating Civil Rights Legislation

2009 ◽  
Vol 103 (4) ◽  
pp. 588-606 ◽  
Author(s):  
GYUNG-HO JEONG ◽  
GARY J. MILLER ◽  
ITAI SENED
Keyword(s):  
Civil Rights ◽  
Winning Coalition ◽  
Ideal Point ◽  
Negotiation Process ◽  
Coalition Building ◽  
Uncovered Set ◽  
Point Estimates ◽  
Building Process ◽  
First Choice ◽  
The U.S

Our investigation of the Senate politics of four major civil rights acts indicates that they did not result from winning coalitions bulldozing helpless minorities, nor did they result from some unpredictable chaotic process. These critical bills were the result of a flexible, multidimensional coalition-building process that proceeded by offering amendments carefully constructed to split off pivotal members of the winning coalition. Ideal point estimates of U.S. senators reveal that this coalitional negotiation process led to outcomes at some distance from the first choice of the winning coalition, testimony to significant compromise, both in early proposals and in refinements. This negotiation process resulted in outcomes apparently constrained by the boundaries of the uncovered set (McKelvey 1986; Miller 1980). “Closing the deal” in the U.S. Senate meant finding an outcome that could withstand robust attacks on pivotal coalition members—and that meant finding an outcome in the uncovered set.

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