Robust Deviance Information Criterion for Latent Variable Models on Macroeconomics and Finance

发布者:系统管理员发布时间:2013-04-02浏览次数:2553

报告题目: Robust Deviance Information Criterion for Latent Variable Models on Macroeconomics and Finance
报 告 人: 李勇
  中国人民大学汗青经济与金融高级研究院副教授、博士生导师
报告时间: 4月7号(周日)上午10:00
报告地点: 九龙湖第一报告厅
相关介绍:
It is shown in this paper that the data augmentation technique undermines the theoretical
underpinnings of the deviance information criterion (DIC), a widely used information
criterion for Bayesian model comparison, although it facilitates parameter estimation for
latent variable models via Markov chain Monte Carlo (MCMC) simulation. Data augmentation
makes the likelihood function non-regular and hence invalidates the standard
asymptotic arguments. A robust form of DIC, denoted as RDIC, is advocated for Bayesian
comparison of latent variable models. RDIC is shown to be a good approximation to DIC
without data augmentation. While the later quantity is difficult to compute, the expectation
? maximization (EM) algorithm facilitates the computation of RDIC when the
MCMC output is available. Moreover, RDIC is robust to nonlinear transformations of
latent variables and distributional representations of model specification. The proposed
approach is applied to several popular models in economics and finance. While DIC is
very sensitive to the nonlinear transformations of latent variables in these models, RDIC
is robust to these transformations. As a result, substantial discrepancy has been found
between DIC and RDIC.
报告人简介:
李勇,1979年生,2003年毕业于东南大学数学系,获硕士学位,后进入香港中文大学攻读博士学位,毕业后到中山大学管理学院工作。期间多次赴新加坡管理大学合作研究,在经济类顶尖刊物Journal of Econometrics、Economics Theory等期刊上发表多篇高水平论文。由于他的杰出成绩,2011年被中国人民大学汗青经济与金融高级研究院(该院主要参照海外标准聘请海外高层次经济研究人才)聘为副教授。
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