 A Bayesian Analysis of Income Distribution ImageAtsushi Ishida SAGE Open, 2018, vol. 8, issue 2, 2158244018774106 Abstract: The purpose of this study is to investigate people’s image of income distribution and its difference by social position from data collected during a 2015 Japanese survey (SSP 2015) by applying Bayesian statistical analytical models. The income distribution image denotes the perceived and estimated income distribution of the individual and is supposed to be a basis of subjective belief on the features of society, including societal average income. In this study, the latent income distribution images were estimated from the observed variable of average income image. Furthermore, differences in income distribution image by social position were analyzed using Bayesian hierarchical models. The differences in income distribution image by age cohort and household income class were examined in terms of the mean (expected value) and the Gini inequality coefficient of the distribution image. It was found that although the distribution image tends to underestimate the average income level and overestimate inequality, the income distribution image could be an incomplete reflection of the income distribution characteristics of the reference group. Keywords: income distribution; social cognition; inequality; reference group; Bayesian hierarchical model (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:8:y:2018:i:2:p:2158244018774106 Access Statistics for this article More articles in SAGE Open |
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