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On Courts and Pocketbooks

Macroeconomic Judicial Behavior across Methods of Judicial Selection

Published online by Cambridge University Press:  21 October 2022

Douglas Rice*
Affiliation:
University of Mississippi
*
Contact the author at drrice@olemiss.edu.
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Abstract

Scholars studying judicial behavior have identified a host of factors theoretically and empirically connected to judicial decision making. One recent theory identifies economic conditions—which have implications for the decisions of voters and politicians—as influencing the voting behavior of US Supreme Court justices. Yet the US Supreme Court is a unique judicial institution addressing limited—though indisputably important—economic cases every year. State courts, on the other hand, address a multitude of issues every year with economic ramifications. Building on the rich body of literature examining state courts of last resort, I analyze whether judges, across a variety of methods for judicial selection and retention, respond to temporary changes in the state of the economy. Results indicate that the responses of state supreme court judges to changes in the state of the economy are conditional on the electoral vulnerability of the justice. This research thus offers considerable insight into judicial behavior under different selection mechanisms and the conditional influence of the state of the economy.

Information

Type
Research Article
Copyright
© 2014 by the Law and Courts Organized Section of the American Political Science Association. All rights reserved.
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Table 1.Fixed Effects of Logit Models for State Supreme Court Justice Progovernment Votes in Economic Cases

Figure 1

Figure 1.Predicted probabilities of justice vote in favor of state government in economic cases across values of Δunemployment. Plots of the 95% confidence intervals for the probability of a government vote across change in employment rates, with other variables held constant at their mean values. Each “months” model represents the difference between the unemployment rate at time t and at time t − x months, where x takes on values of 1, 2, 3, 6, or 12. Negative values of Δunemployment represent improved economic conditions, as the unemployment rate has decreased.

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Table 2.Fixed Effects of Logit Model of Progovernment Votes with Separate Measures of Retention Systems

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Figure 2.Predicted probabilities of justice vote in favor of state government in economic cases across values of Δunemployment. Plots of the 95% confidence intervals for the probability of a government vote across change in unemployment rates, with other variables held constant at their mean values. Negative values of Δunemployment represent improved economic conditions, as the unemployment rate has decreased.

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Figure 3.Predicted probabilities of justice vote in favor of state government in economic cases across national economic indicators. Plots of the 95% confidence intervals for the probability of a government vote across change in the national unemployment rate (first column) and inflation (second column), with other variables held constant at their mean values. Models in the first row represent the difference between the given indicator at time t and at time t − 1 month, and models in the second row represent the difference between the given indicator at time t and at time t − 3. Negative values for change in unemployment, and positive values for change in inflation, represent improved economic conditions.