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Identifier to cite or link to this item: https://hdl.handle.net/10086/18328

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Title	Bayesian Estimation of Unknown Regression Error Heteroscedasticity
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 Tohoku University
Creator	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 社会科学の高度統計・実証分析拠点構築 = Research Unit for Statistical and Empirical Analysis in Social Sciences
Key Word	Eicker-White HCCM
	orthogonal regressors
	informative prior pdf's
	MCMC
	stock return variance
JEL	C11
JEL	C13
Abstract	We propose a Bayesian procedure to estimate heteroscedastic variances of the regression error term ω, when the form of heteroscedasticity is unknown. The prior information on ω is elicited from the wellknown Eicker–White Heteroscedasticity Consistent Variance–Covariance Matrix Estimator. Markov Chain Monte Carlo algorithm is used to simulate posterior pdf’s of the unknown elements of ω. In addition to the numerical examples, we present an empirical investigation of the stock prices of Japanese pharmaceutical and biomedical companies to demonstrate usefulness of the proposed method.
Description	March 2009 (Revised: April 2009)
Publisher	Institute of Economic Research, Hitotsubashi University
Issued Date	2009-04
Language	English(eng)
Resource Type	technical report
Version Type	VoR
Is Part OfRelation -	Related Title Global COE Hi-Stat Discussion Paper Series ; No. 51
ReplacesRelation -	Related Identifier HDL http://hdl.handle.net/10086/17122
Relation	Related Title This is a revised version of http://hdl.handle.net/10086/17122.
Relation	Related Identifier URI http://gcoe.ier.hit-u.ac.jp/english/index.html
Number of Pages	26
Sponsorship	グローバルCOEプログラム = Global COE Program
Edition	Revised in April 2009
Appears in Collections	Global COE Hi-Stat Discussion Paper Series
URL	https://hdl.handle.net/10086/18328