Multinomial Logit Model of Bayesian Age-Period-Cohort Analysis:Factor Decomposition of Political Issues Using Repeated Cross-Sectional Survey

Abstract

The purpose of this study is to discussthe implementation and importanceabout the multinomial logit model of Bayesian Age-Period-Cohort analysis. Since the design matrix of three factorsdoes not become full rankdue to the identification problem derived fromlinear dependency between age, period and cohort, few studies have useda complex model. In contrast, this paper presents the practical multinomial logit model withefficient sampling by reparameterizationabout the constraints of assuming a random walk for each effect. Furthermore, we compared the estimates ofthe logit model andthe multidimensional modelabout political issuesthat should be considered from multiple perspectives. Using repeated cross-sectional survey in Japanfrom 1973 to 2013, the multinomial logit model was shown to be effectivebecause it was able to obtain a trendthat were not captured in the logit model.