A COMPARISON OF MULTINOMIAL LOGISTIC AND MULTINOMIAL CONDITIONAL LOGISTIC REGRESSION MODELS IN ASSESSING EUROPEAN UNION MEMBERSHIP
Abstract
Multinomial logistic (ML) and multinomial conditional logistic (MCL) regression models are used for modeling the relationships between a polytomous response variable and a set of explanatory variables. In this study, key factors affecting the European Union (EU) membership process are determined using ML and MCL models. We compare the ML and MCL models and argue that MCL is more preferable than the more complex ML model. Then for each candidate or potential candidate country, the probability of the accession time for the EU membership is predicted. The findings indicate that human development index, gdp per capita, exports of goods and services are important factors in determining which of the countries will join the EU
and when they will do so. Furthermore, the probabilities of the accession time for both candidate and potential candidate countries are predicted as more than six years.
Keywords
References
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Details
Primary Language
English
Subjects
Mathematical Sciences
Journal Section
Research Article
Publication Date
December 1, 2009
Submission Date
January 29, 2010
Acceptance Date
-
Published in Issue
Year 2009 Volume: 4 Number: 2