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On the Predictive Distributions of Outcome Gains in the Presence of an Unidentified Parameter

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  • Poirier, Dale J
  • Tobias, Justin

Abstract

In 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 Info

Paper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 12014.

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Date of creation: 01 Jan 2003
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Publication status: Published in Journal of Business & Economic Statistics 2003, vol. 21, pp. 258-268
Handle: RePEc:isu:genres:12014

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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
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Web page: http://www.econ.iastate.edu
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Cited by:
  1. Ariun Ishdorj & Helen H. Jensen & Justin Tobias, 2007. "Intra-Household Allocation and Consumption of WIC-Approved Foods: A Bayesian Approach," Center for Agricultural and Rural Development (CARD) Publications 07-wp452, Center for Agricultural and Rural Development (CARD) at Iowa State University.
  2. Muto, Sachio, 2006. "Estimation of the bid rent function with the usage decision model," Journal of Urban Economics, Elsevier, vol. 60(1), pages 33-49, July.
  3. Ishdorj, Ariun & Crepinsek, Mary Kay & Jensen, Helen H., 2012. "Children’s Consumption of Fruits and Vegetables: Do School Environment and Policies Affect Choice in School Meals?," 2012 AAEA/EAAE Food Environment Symposium, May 30-31, Boston, MA 123534, Agricultural and Applied Economics Association.
  4. Munkin, Murat K. & Trivedi, Pravin K., 2008. "Bayesian analysis of the ordered probit model with endogenous selection," Journal of Econometrics, Elsevier, vol. 143(2), pages 334-348, April.
  5. Giorgio Calzolari & Antonino Di Pino, 2014. "Self-Selection and Direct Estimation of Across-Regime Correlation Parameter," Econometrics Working Papers Archive 2014_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  6. Chib, Siddhartha, 2007. "Analysis of treatment response data without the joint distribution of potential outcomes," Journal of Econometrics, Elsevier, vol. 140(2), pages 401-412, October.
  7. Li, Mingliang & Tobias, Justin L., 2011. "Bayesian inference in a correlated random coefficients model: Modeling causal effect heterogeneity with an application to heterogeneous returns to schooling," Journal of Econometrics, Elsevier, vol. 162(2), pages 345-361, June.

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