Bayesian Estimation of Unknown Regression Error Heteroscedasticity

Hiroaki Chigira and Tsunemasa Shiba

Hi-Stat Discussion Paper Series from Institute of Economic Research, Hitotsubashi University

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- CovarianceMatrix Estimator, and then useMarkov ChainMonte 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.

Keywords: Eicker-White HCCM; orthogonal regressors; informative prior pdf's; MCMC; stock return variance (search for similar items in EconPapers)
Date: 2007-10
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (1)

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http://hi-stat.ier.hit-u.ac.jp/research/discussion/2007/pdf/D07-221.pdf (application/pdf)

Related works:
Working Paper: Bayesian Estimation of Unknown Regression Error Heteroscedasticity (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:hst:hstdps:d07-221

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