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Number of Access this item:1,143（2024-04-17 04:30 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/10086/17122

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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 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
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 30, 2009
Publisher
Institute of Economic Research, Hitotsubashi University
Issued Date
2009-03
Language
English(eng)
Resource Type
technical report
Version Type
NA
Is Part OfRelation -
Related Title
Global COE Hi-Stat Discussion Paper Series ; No. 51
Is Replaced ByRelation -
Related Identifier
HDL
  http://hdl.handle.net/10086/18328
Relation
Related Title
This version has been revised. The new version is available at http://hdl.handle.net/10086/18328.
Related Identifier
URI
  http://gcoe.ier.hit-u.ac.jp/english/index.html
Sponsorship
グローバルCOEプログラム = Global COE Program
Appears in Collections
Global COE Hi-Stat Discussion Paper Series
URL
https://hdl.handle.net/10086/17122