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Dirichlet Prior For Estimating Unknown Regression Error Heteroskedasticity

Author

Listed:
  • Hiroaki Chigira
  • Tsunemasa Shiba

Abstract

We propose a Bayesian procedure to estimate heteroskedastic variances of the regression error term ?O, when the form of heteroskedasticity is unknown. The prior information on ?O is based on a Dirichlet distribution, and in the Markov Chain Monte Carlo sampling, its proposal density parameters' information is elicited from the well-known Eicker-White Heteroskedasticity Consistent Variance-Covariance Matrix Estimator. We present an emprical example to show that our scheme works.

Suggested Citation

  • Hiroaki Chigira & Tsunemasa Shiba, 2015. "Dirichlet Prior For Estimating Unknown Regression Error Heteroskedasticity," DSSR Discussion Papers 51, Graduate School of Economics and Management, Tohoku University.
    • Handle: RePEc:toh:dssraa:51
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    File URL: http://hdl.handle.net/10097/65026
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    Cited by:

    1. Ruochen Wu & Melvyn Weeks, 2020. "A Semi-Parametric Bayesian Generalized Least Squares Estimator," Papers 2011.10252, arXiv.org, revised Jan 2023.
    2. Doppelhofer, G. & Moe Hansen, O-P. & Weeks, M., 2017. "Determinants of long-term economic growth redux: A Measurement Error Model Averaging (MEMA) approach," Cambridge Working Papers in Economics 1702, Faculty of Economics, University of Cambridge.
    3. Wu, R. & Weeks, M., 2020. "A Semi-Parametric Bayesian Generalized Least Square Estimator," Cambridge Working Papers in Economics 2011, Faculty of Economics, University of Cambridge.
    4. Doppelhofer, Gernot & Hansen, Ole-Petter Moe & Weeks, Melvyn, 2016. "Determinants of long-term economic Growth redux: A Measurement Error Model Averaging (MEMA) approach," Discussion Paper Series in Economics 19/2016, Norwegian School of Economics, Department of Economics.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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