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Identifier to cite or link to this item: https://hdl.handle.net/10086/16258

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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
informative prior pdf's
MCMC
stock return variance
Abstract
We propose a Bayesian procedure to estimate heteroscedastic variances of the regression error term, when the form of heteroscedasticity is unknown. We use prior information that is elicited from the well-known Eicker -White Heteroscedasticity Consistent Variance- Covariance Matrix Estimator, and then use Markov Chain Monte Carlo algorithm to simulate posterior pdf's of the unknown heteroscedastic variances. In addition to numerical examples, we present an empirical investigation of the stock prices of Japanese pharmaceutical and biomedical companies.
Description
October 2007; Revised February 2008 -- Cover
February 23, 2008 -- Title page
Publisher
Institute of Economic Research, Hitotsubashi University
Issued Date
2008-02
Language
English(eng)
Resource Type
technical report
Version Type
VoR
Is Part OfRelation -
Related Title
Hi-Stat Discussion paper series, No. 221
ReplacesRelation -
Related Identifier
HDL
  http://hdl.handle.net/10086/15107
Relation
Related Title
This is a revised version of http://hdl.handle.net/10086/15107.
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
Edition
Revised Version: February 2008
Appears in Collections
Hi-Stat Discussion paper series
URL
https://hdl.handle.net/10086/16258