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dc.contributor.authorHorncastle, William C.R,
dc.contributor.illustrator
dc.date.accessioned2023-05-25T09:00:45Z
dc.date.available2023-05-25T09:00:45Z
dc.date.issued2022-09-07
dc.identifier.citationHorncastle WCR (2022) 'Model based clustering of political finance regimes: developing the regulation of political finance indicator', Electoral Studies, 79, pp.1-12.en_US
dc.identifier.issn0261-3794
dc.identifier.doi10.1016/j.electstud.2022.102524
dc.identifier.urihttp://hdl.handle.net/10547/625872
dc.description.abstractPolitical finance literature lacks a common framework for classifying regulatory systems. As these tools are influential in the identification of generalizable relationships, studies assessing political finance in areas such as corruption, competition, and electoral outcomes, often present case specific findings. Using updated International IDEA data, the application of a Multiple Correspondence Analysis and Model Based Clustering framework presents a variable to measure levels of regulation; the ‘Unregulated’, ‘Partially Regulated’ and ‘Strongly Regulated’ system types; and statistics for assessing the certainty of each country’s classification. Applying this methodology to a 180-country sample represents an improvement on previous studies which, due to data limitations, have often used reductive methods and limited sampling. In closing, the ‘Regulation of Political Finance Indicator’ is introduced via Multinomial Logistic Regression, where analyses from prior literature are revisited. Avenues for further study are provided, which may seek to identify generalizable relationships in the areas described above, while also looking to produce ongoing panel data.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.urlhttps://www.sciencedirect.com/science/article/pii/S0261379422000804en_US
dc.rightsGreen - can archive pre-print and post-print or publisher's version/PDF
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectpolitical financeen_US
dc.subjectSubject Categories::L150 Political Economicsen_US
dc.titleModel based clustering of political finance regimes: developing the regulation of political finance indicatoren_US
dc.typeArticleen_US
dc.contributor.departmentUniversity of Birminghamen_US
dc.identifier.journalElectoral Studiesen_US
dc.date.updated2023-05-25T08:55:05Z
dc.description.notecannot use final pub version, requested AAM from author 25/5/23 researcher does not have AAM, passing metadata only 25/5/23 - would not have been compliant anyway due to time since acceptance
refterms.dateFOA2023-05-25T09:00:46Z


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