Bayesian Likelihoods for Moment Condition Models
Bayesian inference in moment condition models is difficult to implement. For these models, a posterior distribution cannot be calculated because the likelihood function has not been fully specified. In this paper, we obtain a class of likelihoods by formal Bayesian calculations that take into account the semiparametric nature of the problem. The likelihoods are derived by integrating out the nuisance parameters with respect to a maximum entropy tilted prior on the space of distribution. The result is a unification that uncovers a mapping between priors and likelihood functions. We show that there exist priors such that the likelihoods are closely connected to Generalized Empirical Likelihood (GEL) methods.
|Date of creation:||Jan 2007|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (949) 824-5788
Web page: http://www.economics.uci.edu/
More information through EDIRC
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.:
- Gary Chamberlain & Guido W. Imbens, 1996.
"Nonparametric Applications of Bayesian Inference,"
Harvard Institute of Economic Research Working Papers
1772, Harvard - Institute of Economic Research.
- Gary Chamberlain & Guido W. Imbens, 1996. "Nonparametric Applications of Bayesian Inference," NBER Technical Working Papers 0200, National Bureau of Economic Research, Inc.
- Imbens, Guido & Chamberlain, Gary, 1996. "Nonparametric Applications of Bayesian Inference," Scholarly Articles 3221493, Harvard University Department of Economics.
- Imbens, Guido W, 1997. "One-Step Estimators for Over-Identified Generalized Method of Moments Models," Review of Economic Studies, Wiley Blackwell, vol. 64(3), pages 359-83, July.
- Tony Lancaster & Sung Jae Jun, 2006.
"Bayesian quantile regression,"
CeMMAP working papers
CWP05/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Whitney Newey & Richard Smith, 2003.
"Higher order properties of GMM and generalised empirical likelihood estimators,"
CeMMAP working papers
CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, 01.
- Hahn, Jinyong, 1997. "Bayesian Bootstrap of the Quantile Regression Estimator: A Large Sample Study," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(4), pages 795-808, November.
- Brown, Bryan W & Newey, Whitney K, 2002. "Generalized Method of Moments, Efficient Bootstrapping, and Improved Inference," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 507-17, October.
- Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
- Kim, Jae-Young, 2002. "Limited information likelihood and Bayesian analysis," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 175-193, March.
- Susanne M. Schennach, 2005. "Bayesian exponentially tilted empirical likelihood," Biometrika, Biometrika Trust, vol. 92(1), pages 31-46, March.
- Ghysels, Eric & Hall, Alastair, 2002. "Interview with Christopher A. Sims," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 448-49, October.
When requesting a correction, please mention this item's handle: RePEc:irv:wpaper:060714. 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: (Jennifer dos Santos)
If references are entirely missing, you can add them using this form.