文章基本信息

标题：Bayesian Estimation of an Asymmetric Employment Adjustment Model
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作者：Akikuni Matsumoto ; Hisayuki Hara ; Kazumitsu Nawata 等
期刊名称：JOURNAL OF THE JAPAN STATISTICAL SOCIETY
印刷版ISSN：1882-2754
电子版ISSN：1348-6365
出版年度：2009
卷号：39
期号：1
页码：29-47
DOI：10.14490/jjss.39.29
出版社：JAPAN STATISTICAL SOCIETY
摘要：In this paper, we analyze the dynamic labor demand structure of large Japanese firms. We propose a new dynamic model which explicitly considers the asymmetric behavior of the firms between decreasing and increasing regimes. The model modifies the ordinary partial adjustment and switching cost models. The model is a Tobit-type model; that is, the employment strategies and desired levels of labor are determined by latent variables. We estimate the model using the data augmentation algorithm, which is a Bayesian simulation method. We apply the model to the panel data constructed from financial reports of large Japanese manufacturing firms. When asymmetric adjustment costs are included in the model, we find that: i) the hiring cost does not become lower even if lay-offs and dismissals are easier, and ii) employment strategies differ among the industrial sectors even if their cost structures are similar.
关键词：Asymmetric labor adjustment;Bayesian estimation;dynamic panel data;Markov chain Monte Carlo method