コバヤシ　ゲンヤ   KOBAYASHI GENYA   小林　弦矢    所属   明治大学  商学部    職種   専任教授
言語種別	英語
発行・発表の年月	2020/05
形態種別	学術雑誌
査読	査読あり
標題	Estimation and inference for area-wise spatial income distributions from grouped data
執筆形態	共著(筆頭者以外)
掲載誌名	Computational Statistics & Data Analysis
掲載区分	国外
出版社・発行元	Elsevier BV
巻・号・頁	145,pp.106904-106904
著者・共著者	Shonosuke Sugasawa, Genya Kobayashi, Yuki Kawakubo
概要	Estimating income distributions plays an important role in the measurement of inequality and poverty over space. The existing literature on income distributions predominantly focuses on estimating an income distribution for a country or a region separately and the simultaneous estimation of multiple income distributions has not been discussed in spite of its practical importance. To overcome the difficulty, effective methods are proposed for the simultaneous estimation and inference for area-wise spatial income distributions taking account of geographical information from grouped data. An efficient Bayesian approach to estimation and inference for area-wise latent parameters are developed, which gives area-wise summary measures of income distributions such as mean incomes and Gini indices, not only for sampled areas but also for areas without any samples thanks to the latent spatial state-space structure.
DOI	10.1016/j.csda.2019.106904
ISSN	0167-9473