On the Predictive Distributions of Outcome Gains in the Presence of an Unidentified Parameter
AbstractIn this article we describe methods for obtaining the predictive distributions of outcome gains in the framework of a standard latent variable selection model. Although most previous work has focused on estimation of mean treatment parameters as the method for characterizing outcome gains from program participation, we show how the entire distributions associated with these gains can be obtained in certain situations. Although the out-of sample outcome gain distributions depend on an unidentified parameter, we use the results of Koop and Poirier to show that learning can take place about this parameter through information contained in the identified parameters via a positive definiteness restriction on the covariance matrix.
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Bibliographic InfoPaper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 12014.
Date of creation: 01 Jan 2003
Date of revision:
Publication status: Published in Journal of Business & Economic Statistics 2003, vol. 21, pp. 258-268
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Postal: Iowa State University, Dept. of Economics, 260 Heady Hall, Ames, IA 50011-1070
Phone: +1 515.294.6741
Fax: +1 515.294.0221
Web page: http://www.econ.iastate.edu
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Other versions of this item:
- Poirier, Dale J & Tobias, Justin L, 2003. "On the Predictive Distributions of Outcome Gains in the Presence of an Unidentified Parameter," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(2), pages 258-68, April.
- Poirier, D.J. & Tobias, J.L., 2001. "On the Predictive Distributions of Outcome Gains in the Presence of an Unidentified Parameter," Papers 00-01-30, California Irvine - School of Social Sciences.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
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