Data · dataset · 2009
Replication data for: Agenda Constrained Legislator Ideal Points and the Spatial Voting Model
Listed in Harvard Dataverse
Replication data and code forthcoming 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. (2003), 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 1st US House (1789-1791)
Links
Where it is published
- Dataverse dataset page dataverse.harvard.edu/dataset.xhtml?persistentId=doi%3A10.7910%2FDVN%2FTT2OOM ↗
landing page · from Harvard Dataverse
- DOI doi.org/10.7910/dvn/tt2oom ↗
DOI / persistent id · from Harvard Dataverse
Catalogue records · 1
- Dataverse API dataverse.harvard.edu/api/datasets/:persistentId/?persistentId=doi%3A10.7910%2FDVN%2… ↗
metadata API · from Harvard Dataverse
Topics
- Inferred from text
- Simulation 75% · Statistics 73%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Harvard Dataverse | doi:10.7910/DVN/TT2OOM | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4905 | enrichment · Harvard Dataverse | taxonomy-embedding@1.1.0 | title+keywords+description (73%) |
| concepts[method].local:method:simulation | enrichment · Harvard Dataverse | keyword-concept-rules@1.0.0 | title+description (75%) |
| created_date | source · Harvard Dataverse | connector:dataverse@1.0.0 | |
| description | source · Harvard Dataverse | connector:dataverse@1.0.0 | /description |
| publication_date | source · Harvard Dataverse | connector:dataverse@1.0.0 | |
| title | source · Harvard Dataverse | connector:dataverse@1.0.0 | /name |
| updated_date | source · Harvard Dataverse | connector:dataverse@1.0.0 | |
| version_label | source · Harvard Dataverse | connector:dataverse@1.0.0 |