Data · dataset · 2009
Estimating Legislators' Preferred Points
Listed in Harvard Dataverse
This paper shows that agnostic spatial models that simultaneously attempt to estimate legislators’ preferred points and ideological locations for the proposals on which they vote, such as the well-known NOMINATE model of Poole and Rosenthal, are not identified.
Description
The problem arises because the agnostic estimators inherit the granularity of the voting data and, so, cannot recapture the underlying continuous parameter space.
I propose an alternative estimator that achieves identification by modeling the agenda.
Links
Where it is published
- Dataverse dataset page dataverse.harvard.edu/dataset.xhtml?persistentId=doi%3A10.7910%2FDVN%2FPJBYPC ↗
landing page · from Harvard Dataverse
- DOI doi.org/10.7910/dvn/pjbypc ↗
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
- Political geography 76%
Provenance · 1 source records, 7 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Harvard Dataverse | doi:10.7910/DVN/PJBYPC | 14 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:field:440606 | enrichment · Harvard Dataverse | taxonomy-embedding@1.1.0 | title+keywords+description (76%) |
| 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 |