Advanced Search
MyIDEAS: Login to save this paper or follow this series

Fast Computation of the Deviance Information Criterion for Latent Variable Models

Contents:

Author Info

  • Joshua C.C. Chan
  • Angelia L. Grant

Abstract

The deviance information criterion (DIC) has been widely used for Bayesian model comparison. However, recent studies have cautioned against the use of the DIC for comparing latent variable models. In particular, the DIC calculated using the conditional likelihood (obtained by conditioning on the latent variables) is found to be inappropriate, whereas the DIC computed using the integrated likelihood (obtained by integrating out the latent variables) seems to perform well. In view of this, we propose fast algorithms for computing the DIC based on the integrated likelihood for a variety of highdimensional latent variable models. Through three empirical applications we show that the DICs based on the integrated likelihoods have much smaller numerical standard errors compared to the DICs based on the conditional likelihoods.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2014-01/9_2014_chan_grant.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University in its series CAMA Working Papers with number 2014-09.

as in new window
Length: 24 pages
Date of creation: Jan 2014
Date of revision:
Handle: RePEc:een:camaaa:2014-09

Contact details of provider:
Postal: Crawford Building, Lennox Crossing, Building #132, Canberra ACT 0200
Phone: +61 2 6125 4705
Fax: +61 2 6125 5448
Email:
Web page: http://cama.crawford.anu.edu.au
More information through EDIRC

Related research

Keywords: Bayesian model comparison; state space; factor model; vector autoregression; semiparametric;

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Koop, Gary M & Poirier, Dale J & Tobias, Justin, 2005. "Semiparametric Bayesian Inference in Multiple Equation Models," Staff General Research Papers 12009, Iowa State University, Department of Economics.
  2. Chan, Joshua & Eisenstat, Eric, 2012. "Marginal Likelihood Estimation with the Cross-Entropy Method," MPRA Paper 40051, University Library of Munich, Germany.
  3. Koop, Gary & Korobilis, Dimitris, 2010. "Forecasting Inflation Using Dynamic Model Averaging," SIRE Discussion Papers 2010-113, Scottish Institute for Research in Economics (SIRE).
  4. Haroon Mumtaz & Paolo Surico, 2012. "Evolving International Inflation Dynamics: World And Country-Specific Factors," Journal of the European Economic Association, European Economic Association, vol. 10(4), pages 716-734, 08.
  5. Abanto-Valle, C.A. & Bandyopadhyay, D. & Lachos, V.H. & Enriquez, I., 2010. "Robust Bayesian analysis of heavy-tailed stochastic volatility models using scale mixtures of normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 2883-2898, December.
  6. Chan, Joshua & Koop, Gary & Potter, Simon, 2012. "A New Model Of Trend Inflation," SIRE Discussion Papers 2012-12, Scottish Institute for Research in Economics (SIRE).
  7. Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2007. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9780521671736.
  8. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  9. Eric Eisenstat & Joshua C.C. Chan & Rodney W. Strachan, 2014. "Stochastic Model Specification Search for Time-Varying Parameter VARs," CAMA Working Papers 2014-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  10. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
  11. Luc Bauwens & Jeroen V.K. Rombouts, 2009. "On Marginal Likelihood Computation in Change-point Models," Cahiers de recherche 0942, CIRPEE.
  12. McCausland, William J., 2012. "The HESSIAN method: Highly efficient simulation smoothing, in a nutshell," Journal of Econometrics, Elsevier, vol. 168(2), pages 189-206.
  13. Nardari, Federico & Scruggs, John T., 2007. "Bayesian Analysis of Linear Factor Models with Latent Factors, Multivariate Stochastic Volatility, and APT Pricing Restrictions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(04), pages 857-891, December.
  14. BELMONTE, Miguel A.G. & KOOP, Gary & KOROBILIS, Dimitris, 2011. "Hierarchical shrinkage in time-varying parameter models," CORE Discussion Papers 2011036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  15. Xiao, Ni & Zarnikau, Jay & Damien, Paul, 2007. "Testing functional forms in energy modeling: An application of the Bayesian approach to U.S. electricity demand," Energy Economics, Elsevier, vol. 29(2), pages 158-166, March.
  16. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
  17. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
  18. Brendan Kline & Justin L. Tobias, 2008. "The wages of BMI: Bayesian analysis of a skewed treatment-response model with nonparametric endogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(6), pages 767-793.
  19. Berg, Andreas & Meyer, Renate & Yu, Jun, 2004. "Deviance Information Criterion for Comparing Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 107-20, January.
  20. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika van der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639.
  21. Chen, Xiaoshan & Kontonikas, Alexandros & Montagnoli, Alberto, 2012. "Asset Prices, Credit and the Business Cycle," Stirling Economics Discussion Papers 2012-04, University of Stirling, Division of Economics.
  22. Koop, G. & Poirier, D., 2000. "Bayesian Variants of Some Classical Semiparametric Regression Techniques," Papers 00-01-22, California Irvine - School of Social Sciences.
  23. N. Friel & A. N. Pettitt, 2008. "Marginal likelihood estimation via power posteriors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(3), pages 589-607.
  24. Canova, Fabio, 1993. "Modelling and forecasting exchange rates with a Bayesian time-varying coefficient model," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 233-261.
  25. McCausland, William J. & Miller, Shirley & Pelletier, Denis, 2011. "Simulation smoothing for state-space models: A computational efficiency analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 199-212, January.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Joshua C.C. Chan & Angelia L. Grant, 2014. "Issues in Comparing Stochastic Volatility Models Using the Deviance Information Criterion," CAMA Working Papers 2014-51, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:een:camaaa:2014-09. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Cama Admin).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.