1

Paper

Heterogeneity in Supreme Court Decision-Making: How Case-Level Factors Alter Preference-Based Behavior Bartels, Brandon Uploaded 07-19-2005 Keywords Supreme Court decision-making multilevel modeling heterogeneity Abstract Many theoretical perspectives of Supreme Court decision-making, most notably the attitudinal model, assume that justices’ policy preferences exhibit a uniform impact on their decisions across a wide variety of situations. I argue that there exists meaningful heterogeneity in the impact of policy preferences that can be explained theoretically and tested empirically. Adopting social psychological insights from theories of the attitude-behavior relationship, I develop a theoretical framework specifying the mechanisms--attitude strength and accountability--that explain variation in the preference-behavior relationship for justices. Case-level factors associated with each mechanism are hypothesized to moderate the impact of preferences. To test the hypotheses, I use a multilevel (hierarchical) modeling framework and conceive of Supreme Court voting data from the 1994-2002 terms as a two-level hierarchy: justices’ choices nested within cases. Estimates from a random coefficient model indicate that case-level variables associated with both attitude strength and accountability systematically explain variation in the preference-behavior relationship. Using an average partial effects post-estimation procedure, I present in-depth substantive interpretations of the results that highlight the compelling ways in which these case-level factors alter the nature of preference-based behavior. In addition to providing important substantive conclusions about Supreme Court decision-making, the paper also illustrates how a multilevel modeling framework is well-qualified to test heterogeneity-related hypotheses in social and behaviorial processes.

2

Paper

Bridging Institutions and Time: Creating Comparable Preference Estimates for Presidents, Senators, Representatives and Justices, 1950-2002 Bailey, Michael Uploaded 07-19-2005 Keywords ideal point estimation Supreme Court Congress Abstract Difficulty in comparing preferences across time and institutional contexts hinders the empirical testing of many important theories in political science. In this paper, I characterize these difficulties and provide a measurement approach that relies on inter-temporal and inter-institutional ``bridge'' observations and Bayesian Markov chain simulation methods. I generate preference estimates for Presidents, Senators, Representatives and Supreme Court Justices that are comparable across time and across institutions. Such preference estimates are indispensable in a variety of important research projects, including research on statutory interpretation, executive influence on the Supreme Court and Senate influence on court appointments.

3

Paper

Public Opinion and Senate Confirmation of Supreme Court Nominees Kastellec, Jonathan Lax, Jeffrey Phillips, Justin Uploaded 08-22-2008 Keywords Supreme Court nominations public opinion multilevel models poststratification Abstract We study the relationship between state-level public opinion and the roll call votes of senators on Supreme Court nominees. Applying recent advances in multilevel modeling, we use national polls on nine recent Supreme Court nominees to produce state-of-the-art estimates of public support for the confirmation of each nominee in all 50 states. We show that greater public support strongly increases the probability that a senator will vote to approve a nominee, even after controlling for standard predictors of roll call voting. We also find that the impact of opinion varies with context: it has a greater effect on opposition party senators, on ideologically opposed senators, and for generally weak nominees. These results establish a systematic and powerful link between constituency opinion and voting on Supreme Court nominees.

4

Paper

Conservative Vote Probabilities: An Easier Method for the Analysis of Roll Call Data Fowler, Anthony Hall, Andrew B. Uploaded 08-08-2012 Keywords Roll Call Ideology Congress Supreme Court State Legislatures Non-parametric Abstract We propose a new roll-call scaling method based on OLS which is easier to implement and understand than previous methods and also produces directly interpretable estimates. This measure, Conservative Vote Probability (CVP), indicates the probability that an individual legislator votes "conservatively" relative to the median legislator. CVP is a flexible non-parametric statistical technique that requires no complicated assumptions but still produces legislator scalings that correlate with previous roll call methods at extremely high levels. In this paper we introduce the methodology behind CVP and offer several substantive examples to demonstrate its e efficacy as an easier, more accessible alternative to previous roll call methods.

5

Paper

Noncommutative harmonic analysis of voting in small committees Lawson, Brian Orrison, Michael Uminsky, David Uploaded 07-13-2003 Keywords spectral analysis noncommutative harmoinc analysis voting analysis supreme court Abstract This paper introduces a new method, noncommutative harmonic analysis, as a tool for political scientists. The method is based on recent results in mathematics which systematically identify coalitions in voting data. The first section shows how this new approach, noncommutative harmonic analysis is a generalization of classical spectral analysis. The second section shows how noncommutative harmonic analysis is applied to a hypothetical example. The third section uses noncommutative harmonic analysis to analyze coalitions on the Supreme Court. The final section suggests ideas for extending the approach presented here to the study of voting in legislatures and preferences over candidates in multicandidate mass elections.

6

Paper

Designing Tests of the Supreme Court and the Separation of Powers Sala, Brian R. Spriggs II, James F. Uploaded 09-13-2002 Keywords spatial voting theory strategic behavior Supreme Court Abstract While "rational choice" models of Supreme Court decision making have enhanced our appreciation for the separation of powers built into the Madisonian Constitutional design, convincing empirical support for a separation-of-powers (SOP) constraint on justices' behavior has been elusive. We apply a standard spatial voting model to identify circumstances in which "Attitudinalist" and SOP predictions about justices' behavior diverge. Our reconsideration of the theory indicates that prior efforts to test quantitatively the two models have been biased by having included cases for which the two models' predictions do not differ. While our more focused test offers a fairer test of the SOP constraint, the results strongly reject the SOP model. Nonetheless, our analysis provides leverage on this issue by: (1) delineating and executing necessary research design protocols for crafting a critical test of the SOP model; and (2) rejecting the two exogenously fixed alternative SOP model and suggesting avenues for future research.

7

Paper

Delaying Justice(s): A Duration Analysis of Supreme Court Nominations Shipan, Charles R. Shannon, Megan L. Uploaded 07-16-2001 Keywords Hazard Model Spatial Model Supreme Court Nominations Abstract Presidents have great success when nominating justices to the Supreme Court, with confirmation being the norm and rejection being the rare exception. In this paper we show that while the end result of the confirmation process is that the nominee taking a seat on the Court, there is a great deal of variance in the amount of time it takes the Senate to approve the nominee. To derive a theoretical explanation of this underlying dynamic in the confirmation process, we draw on a spatial model of presidential nominations to the Court. We then use a hazard rate model to test this explanation, using data on all Supreme Court nominations and confirmations since the end of the Civil War. The hazard model is superior to alternative models such as probit, where information on right-censored nominations in our data would be lost. More specifically, the Cox proportional hazards model is a better fit for our data as compared to the Weibull, exponential, and log-logistic hazard models. Our paper thus makes two key contributions. First, it identifies the political factors that influence Supreme Court confirmations and the duration of the confirmation process. Second, it demonstrates the ways in which the nomination process affects the confirmation process.

8

Paper

Signals, Models, and Congressional Overrides of the Supreme Court Zorn, Christopher Hettinger, Virginia Uploaded 04-05-1999 Keywords event history models split-population duration models Congress Supreme Court statutory decisions overrides Abstract Sparked by interest in game-theoretic representations of the separation of powers, empirical work examining congressional overrides of Supreme Court statutory decisions has burgeoned in recent years. Much of this work has been hampered, however, by the relative rarity of such events; as has long been noted, congressional attention to the Court is limited, and most Court decisions represent the last word on statutory interpretation. With this fact foremost in our minds, we examine empirically a number of theories regarding such reversals. We apply a split-population duration model to the survival of Supreme Court statutory interpretation decisions. This approach allows us to separate the factors which lead to the event itself (i.e., the presence or absence of an override in a particular case) from those which influence the timing of the event. We find that case-specific factors relating to the salience of a case are an important influence in the incidence of overrides, while Congress- and Court-specific political influences dominate the timing at which those overrides occur. By separating the incidence and timing of overrides, our results yield a more accurate and nuanced understanding of this aspect of the separation of powers system.