Abstract

In the long history of legislative roll call analyses, there continues to exist a particularly troubling problem: There is no satisfactory method for measuring the relative importance or significance of individual roll calls. A measure of roll call significance would be intersting in and of itself, but many have realized that it could also substantially improve empirical research. The consequence of this situation is that hundreds of researchers risk heteroskedastic disturbances (resulting in inefficient estimates and biased standard errors and test statistics), are unable to appropriately choose the roll calls most suited to their theory (resulting in analyses that may not correctly test their theory), and often use methods that create more problems than they solve (resulting in selection bias, unrealistic weighting schemes, or relatively subjective measures). This article introduces a new method designed to meet these problems. Based on an application of Box-Tiao intervention analysis, the method extracts from observed voting participation scores the “revealed preferences” of legislators as a measure of roll call significance. Applying this method to roll calls from the U.S. Senate demonstrates the success of the method and suggests its utility in applied research.

Highlights

  • In the long h story of legislative roll call analyses, there continues to exist a tro bling problem: There is no satisfactory method for measuring the relative im ortance or significance of individual roll calls

  • Based on an application of Box-Tiao interventi analysis, the method extracts from observed voting participation scores the "rev aled preferences" of legislators as a measure of roll call sidcance

  • Applying this dethod to roll calls from the U.S Senate demonstrates the success of the method /and suggests its utility in applied research. @ 1986 Academic Press, Inc

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Summary

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The significance of roll calls in voting bodies: A model and statistical estimation.

Statistical Estimation
EMPIRICAL ANALYSES estimates of the version of this model chosen for
Standard error
Title and description
Findings
CO No m e

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