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Applying Ideal Point Estimation Methods to the Council of Ministers
Author(s) -
Sara Hagemann
Publication year - 2007
Publication title -
european union politics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.241
H-Index - 65
eISSN - 1741-2757
pISSN - 1465-1165
DOI - 10.1177/1465116507076433
Subject(s) - nominate , voting , council of ministers , legislation , political science , preference , set (abstract data type) , public administration , legislature , bayesian probability , computer science , public relations , operations research , european union , law , economics , politics , microeconomics , artificial intelligence , engineering , programming language , machine learning , economic policy
This research note addresses an increasingly popular topic in the EU literature, namely the measurement of policy preferences in the Council of Ministers. It aims to provide conclusions on three issues: (1) what data are in fact available from the Council, (2) how preferences are measured in other legislatures, and (3) whether these methods would be suitable for analyses of Council members' preference positions given the available data. Applying the popular scaling method NOMINATE and a Bayesian MCMC model to a data set consisting of all legislation adopted by the Council in 1999—2004, it is found that, although the two methods show similar voting patterns at the general level, the failure to report standard errors by NOMINATE in particular proves to be a severe problem when trying to identify individual governments' policy location. Conversely, the Bayesian approach provides a convincing method for analyses of Council decision records and is easily extended to include more advanced empirical information than merely the governments' decisions to support or oppose a proposal

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