Bayesian hypothesis testing in latent variable models
AbstractHypothesis testing using Bayes factors (BFs) is known not to be well defined under the improper prior. In the context of latent variable models, an additional problem with BFs is that they are difficult to compute. In this paper, a new Bayesian method, based on the decision theory and the EM algorithm, is introduced to test a point hypothesis in latent variable models. The new statistic is a by-product of the Bayesian MCMC output and, hence, easy to compute. It is shown that the new statistic is appropriately defined under improper priors because the method employs a continuous loss function. In addition, it is easy to interpret. The method is illustrated using a one-factor asset pricing model and a stochastic volatility model with jumps.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 166 (2012)
Issue (Month): 2 ()
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Web page: http://www.elsevier.com/locate/jeconom
Bayes factors; Kullback–Leibler divergence; Decision theory; EM algorithm; Markov chain Monte Carlo;
Other versions of this item:
- Yong Li & Jun Yu, 2011. "Bayesian Hypothesis Testing in Latent Variable Models," Working Papers 11-2011, Singapore Management University, School of Economics.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing
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.:
- Poirier, Dale J, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends: A Comment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 381-86, Oct.-Dec..
- So, Mike K P & Li, W K, 1999. "Bayesian Unit-Root Testing in Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 491-96, October.
- Jun Yu, 2004.
"On leverage in a stochastic volatility model,"
Econometric Society 2004 Far Eastern Meetings
497, Econometric Society.
- Tu, Jun & Zhou, Guofu, 2010. "Incorporating Economic Objectives into Bayesian Priors: Portfolio Choice under Parameter Uncertainty," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(04), pages 959-986, August.
- Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.
- Chang, Yoosoon & Isaac Miller, J. & Park, Joon Y., 2009. "Extracting a common stochastic trend: Theory with some applications," Journal of Econometrics, Elsevier, vol. 150(2), pages 231-247, June.
- Shanken, Jay, 1987. "A Bayesian approach to testing portfolio efficiency," Journal of Financial Economics, Elsevier, vol. 19(2), pages 195-215, December.
- Leamer, Edward E, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends: Comment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 371-73, Oct.-Dec..
- Ibrahim, Joseph G. & Zhu, Hongtu & Tang, Niansheng, 2008. "Model Selection Criteria for Missing-Data Problems Using the EM Algorithm," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1648-1658.
- Koop, Gary & Steel, Mark F J, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends: A Comment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 365-70, Oct.-Dec..
- Roll, Richard & Ross, Stephen A, 1980. " An Empirical Investigation of the Arbitrage Pricing Theory," Journal of Finance, American Finance Association, vol. 35(5), pages 1073-1103, December.
- Peter C.B. Phillips, 1990.
"To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends,"
Cowles Foundation Discussion Papers
950, Cowles Foundation for Research in Economics, Yale University.
- Phillips, P C B, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 333-64, Oct.-Dec..
- Gibbons, Michael R & Ross, Stephen A & Shanken, Jay, 1989. "A Test of the Efficiency of a Given Portfolio," Econometrica, Econometric Society, vol. 57(5), pages 1121-52, September.
- John Geweke, 2007. "Bayesian Model Comparison and Validation," American Economic Review, American Economic Association, vol. 97(2), pages 60-64, May.
- Harvey, Campbell R. & Zhou, Guofu, 1990. "Bayesian inference in asset pricing tests," Journal of Financial Economics, Elsevier, vol. 26(2), pages 221-254, August.
- 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.
- Ross, Stephen A., 1976. "The arbitrage theory of capital asset pricing," Journal of Economic Theory, Elsevier, vol. 13(3), pages 341-360, December.
- 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.
- Poirier, Dale J., 1997. "A predictive motivation for loss function specification in parametric hypothesis testing," Economics Letters, Elsevier, vol. 56(1), pages 1-3, September.
- McCulloch, Robert & Rossi, Peter E., 1991. "A bayesian approach to testing the arbitrage pricing theory," Journal of Econometrics, Elsevier, vol. 49(1-2), pages 141-168.
- Doron Avramov & Guofu Zhou, 2010. "Bayesian Portfolio Analysis," Annual Review of Financial Economics, Annual Reviews, vol. 2(1), pages 25-47, December.
- Li, Yong & Chong, Terence Tai-Leung & Zhang, Jie, 2012. "Testing for a unit root in the presence of stochastic volatility and leverage effect," Economic Modelling, Elsevier, vol. 29(5), pages 2035-2038.
- Yong Li & Zeng Tao & Jun Yu, .
"Robust Deviance Information Criterion for Latent Variable Models,"
CoFie-04-2012, Sim Kee Boon Institute for Financial Economics.
- Yong Li & Tao Zeng & Jun Yu, 2012. "Robust Deviance Information Criterion for Latent Variable Models," Working Papers 30-2012, Singapore Management University, School of Economics.
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