Record Details

Replication data for: Integrating Voting Theory and Roll-Call Analysis: A Framework

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title Replication data for: Integrating Voting Theory and Roll-Call Analysis: A Framework
 
Identifier https://doi.org/10.7910/DVN/GP9QJD
 
Creator Joshua D. Clinton
Adam Meirowitz
 
Publisher Harvard Dataverse
 
Description

Replication data and code forthcoming


Scholars of legislative studies typically use ideal point estimates from scaling procedures to test theories of legislative politics. We contend that theory and methods may be better integrated by directly incorporating \textit{maintained} and \textit{to be tested hypotheses} in the statistical model used to estimate legislator preferences. In this view of theory and estimation, formal modelling (1) provides auxiliary assumptions th
at serve as constraints in the estimation process, and (2) generates testable predictions. The estimation and hypothesis testing procedure uses roll call data to evaluate the validity of theoretically derived \textit{to be tested hypotheses} in a world where \textit{maintained hypotheses} are presumed true. We articulate the approach using the language of statistical inference (both frequentist and Bayesian). The approach is demonstrated in analyses of the well-studied Powell amendment to the federal aid to education bill in the 84th House and the Compromise of 1790 in the 1st House
 
Date 2003