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Data · dataset · 2010

Replication data for: Mixed Logit Models for Multiparty Elections

Listed in Harvard Dataverse

Mixed logit (MXL) is a general discrete choice model thus far unexamined in the study of multicandidate andmultiparty elections.

Description

Mixed logit assumes that the unobserved portions of utility are a mixture of an IID extreme value term and another multivariate distribution selected by the researcher. This general specification allows MXL to avoid imposing the independence of irrelevant alternatives (IIA) property on the choice probabilities.

Further, MXL is a flexible tool for examining heterogeneity in voter behavior through randomcoefficients specifications. MXL is a more general discrete choice model than multinomial probit (MNP) in several respects, and can be applied to a wider variety of questions about voting behavior than MNP. An empirical example using data from the 1987 British General Election demonstrates the utility of MXL in the study of multicandidate and multiparty elections.

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Where it is published

Catalogue records · 1
Provenance · 1 source records, 6 field assertions
SourceKeyLast seenRaw
Harvard Dataversedoi:10.7910/DVN/PCPVWB12 d agoJSON v1
FieldAssertionExtractorEvidence
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publication_datesource · Harvard Dataverseconnector:dataverse@1.0.0
titlesource · Harvard Dataverseconnector:dataverse@1.0.0/name
updated_datesource · Harvard Dataverseconnector:dataverse@1.0.0
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