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Manifesto Coding×Ideal Point Estimation×
OborPolitical SciencePolitical Science
RodinaProcess / pipelineLatent structure
Rok vzniku20012004
TvůrceManifesto Research Group / Comparative Manifesto Project (CMP/MARPOR)Clinton, Jackman & Rivers (Bayesian formulation); Poole & Rosenthal (spatial tradition)
TypQuantitative content analysis of party manifestosLatent-variable spatial model of binary choice data
Původní zdrojBudge, I., Klingemann, H.-D., Volkens, A., Bara, J., & Tanenbaum, E. (2001). Mapping Policy Preferences: Estimates for Parties, Electors, and Governments 1945–1998. Oxford: Oxford University Press. ISBN: 9780199244003Clinton, J., Jackman, S., & Rivers, D. (2004). The Statistical Analysis of Roll Call Data. American Political Science Review, 98(2), 355–370. DOI ↗
Další názvyCMP coding, MARPOR coding, Manifesto content analysis, Party manifesto codingIdeal point model, Item response theory for roll calls, Spatial voting model, Bayesian ideal points
Příbuzné44
ShrnutíManifesto coding is the quantitative content-analysis methodology of the Comparative Manifesto Project (CMP/MARPOR) for measuring parties' policy preferences from their election manifestos. Trained coders break each manifesto into quasi-sentences and assign every unit to one of a fixed set of policy categories. Counting how often each category appears yields salience measures, and combining pro- and anti- categories produces position scores such as the left–right RILE index, giving comparable estimates of party positions across more than fifty democracies since 1945.Ideal point estimation recovers the latent policy positions — ideal points — of political actors from their observed binary choices, most often legislators' yea/nay votes on roll calls. Building on the spatial theory of voting and formalized as a Bayesian item-response model by Clinton, Jackman, and Rivers in 2004, it places each legislator and each bill in a low-dimensional policy space and estimates positions so that the probability a legislator votes yea increases as the bill's 'yea' outcome moves closer to that legislator's ideal point.
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ScholarGatePorovnat metody: Manifesto Coding · Ideal Point Estimation. Získáno 2026-06-24 z https://scholargate.app/cs/compare