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Identifier to cite or link to this item: https://hdl.handle.net/10086/13575

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Title
Bayesian Estimation of Unknown Heteroscedastic Variances
Creator
Creator Name
Chigira, Hiroaki Chigira, Hiroaki
千木良, 弘朗 千木良, 弘朗
チギラ, ヒロアキ チギラ, ヒロアキ
Affiliation
Affiliation Name
Hitotsubashi University
Creator Name
Shiba, Tsunemasa Shiba, Tsunemasa
斯波, 恒正 斯波, 恒正
シバ, ツネマサ シバ, ツネマサ
Affiliation
Affiliation Name
Hitotsubashi University
Editor
Contributor Name
社会科学における統計分析拠点構築 = Research Unit for Statistical Analysis in Social Sciences
Key Word
Eicker-White HCCM
orthogonal regressors
conditional Bayesian
MCMC
stock return variance estimation
Abstract
We propose a Bayesian procedure to estimate possibly heteroscedastic variances of the regression error term, without assuming any structure on them. What we propose in this paper, may be construed as a Conditional Bayesian procedure that is conditioned upon the HCCM obtained from the OLS estimation of the original regression model. After we obtain the Eicker-White HCCM, we set up a Bayesian model and use an MCMC to simulate posterior pdf's of heteroscedastic variances whose structures are unknown. In addition to the numerical examples, we present an empirical investigation on the stock prices of Japanese pharmaceutical and biomedical companies.
Publisher
Institute of Economic Research, Hitotsubashi University
Issued Date
2006-09
Language
English(eng)
Resource Type
technical report
Version Type
VoR
Is Part OfRelation -
Related Title
Hi-Stat Discussion paper series, No. 185
Relation
Related Identifier
URI
  http://21coe.ier.hit-u.ac.jp/english/index.html
Sponsorship
21世紀COEプログラム = 21st-Century COE Program
Appears in Collections
Hi-Stat Discussion paper series
URL
https://hdl.handle.net/10086/13575