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Bayesian Inference in the Seemingly Unrelated Regressions Models

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  • Griffiths, W.E.

Abstract

The objective of this chapter is to provide a practical guide to computer-aided Bayesian inference for a variety of problems that arise in applications of the SUR model. We describe examples of problems, models and algorithms that have been placed within a general framework in the chapter by Geweke et al (this volume); our chapter can be viewed as complimentary to that chapter. The model is described in Section II; the joint, conditional and marginal posterior density functions that result from a noninformative prior are derived. In Section III we describe how to use sample draws of parameters from their posterior densities to estimate posterior quantities of interest; two Gibbs sampling algorithms and a Metropolis-Hastings algorithm are given.

Suggested Citation

  • Griffiths, W.E., 2001. "Bayesian Inference in the Seemingly Unrelated Regressions Models," Department of Economics - Working Papers Series 793, The University of Melbourne.
    • Handle: RePEc:mlb:wpaper:793
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    8. W. E. Griffiths, 1999. "Estimating consumer surplus comments on "using simulation methods for bayesian econometric models: inference development and communication"," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 75-87.
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    1. Hendrik Wolff & Thomas Heckelei & Ron Mittelhammer, 2010. "Imposing Curvature and Monotonicity on Flexible Functional Forms: An Efficient Regional Approach," Computational Economics, Springer;Society for Computational Economics, vol. 36(4), pages 309-339, December.
    2. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265.
    3. Wang, Hao, 2010. "Sparse seemingly unrelated regression modelling: Applications in finance and econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2866-2877, November.
    4. Wolff, Hendrik & Heckelei, Thomas & Mittelhammer, Ronald C., 2004. "Imposing Monotonicity And Curvature On Flexible Functional Forms," 2004 Annual meeting, August 1-4, Denver, CO 20256, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Tiberti, M., 2013. "Production costs of Soft Wheat in Italy," 2013 Second Congress, June 6-7, 2013, Parma, Italy 149898, Italian Association of Agricultural and Applied Economics (AIEAA).
    6. Chiara Scotti, 2006. "A bivariate model of Fed and ECB main policy rates," International Finance Discussion Papers 875, Board of Governors of the Federal Reserve System (U.S.).
    7. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265, April.
    8. Yiannis Kamarianakis, 2006. "Hierarchical Bayesian Modeling For Spatial Time Series: An Alternative Approach To Spatial Sur," Working Papers 0605, University of Crete, Department of Economics.

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