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Data · dataset · 2010

Replication data for: Agenda Constrained Legislator Ideal Points and the Spatial Voting Model

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Existing preference estimation procedures do not incorporate the full structure of the spatial model of voting, as they fail to use the sequential nature of the agenda.

Description

In the maximum likelihood framework, the consequences of this omission may be far-reaching. First, information useful for the identification of the model is neglected.

Specifically, information that identifies the proposal locations is ignored. Second, the dimensionality of the policy space may be incorrectly estimated. Third, preference and proposal location estimates are incorrect and difficult to interpret in terms of the spatial model.

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We also show that the Bayesian simulation approach to ideal point estimation (Clinton et al. 2000; Jackman 2000) may be improved through the use of information about the legislative agenda. This point is illustrated by comparing several preference estimators of the first U.S. House (1789–1791).

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Inferred from text
Simulation 75%
Provenance · 1 source records, 7 field assertions
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Harvard Dataversedoi:10.7910/DVN/AIVBZQ14 d agoJSON v1
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created_datesource · Harvard Dataverseconnector:dataverse@1.0.0
descriptionsource · Harvard Dataverseconnector:dataverse@1.0.0/description
publication_datesource · Harvard Dataverseconnector:dataverse@1.0.0
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