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Marginal likelihood calculation for the Gelfand–Dey and Chib methods

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  • Liu, Chun
  • Liu, Qing
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Abstract

A trade-off exists between the Gelfand and Dey (1994) and Chib (1995) methods to calculate the marginal likelihood in Bayesian estimation. Using the Markov Chain Monte Carlo method, we demonstrate that the performance of the two methods is fairly close.

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File URL: http://www.sciencedirect.com/science/article/pii/S016517651100557X
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Bibliographic Info

Article provided by Elsevier in its journal Economics Letters.

Volume (Year): 115 (2012)
Issue (Month): 2 ()
Pages: 200-203

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Handle: RePEc:eee:ecolet:v:115:y:2012:i:2:p:200-203

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Web page: http://www.elsevier.com/locate/ecolet

Related research

Keywords: Model comparison; Structural break; Heterogeneous autoregressive model; Bayesian estimation;

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  1. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 7(2), pages 174-196, Spring.
  2. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
  3. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2005. "Roughing it Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility," NBER Working Papers 11775, National Bureau of Economic Research, Inc.
  4. Chun Liu & John M Maheu, 2007. "Are there Structural Breaks in Realized Volatility?," Working Papers tecipa-304, University of Toronto, Department of Economics.
  5. John Geweke, 1999. "Using simulation methods for bayesian econometric models: inference, development,and communication," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 1-73.
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