Estimating Demand Systems when Outcomes Are Correlated Count
AbstractWe develop a Bayesian posterior simulator for fitting a high dimensional system of ordinal or count outcome equations, illustrating its use by modeling the multiple site recreation demands of individual agents to a set of twenty-nine Iowa lakes. The model flexibly adjusts to match observed frequencies in trip outcomes, permits a flexible correlation pattern among the visited sites, and the posterior simulator for fitting this model is relatively easy to implement. We also describe how the model can be used to conduct counterfactual experiments, including predicting behavioral changes and describing welfare implications resulting from shifts in demographic and site characteristics.
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Bibliographic InfoPaper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 12934.
Date of creation: 14 May 2008
Date of revision:
Publication status: Published in Journal of Econometrics 2008, vol. 147 no. 2, pp. 282-298
Contact details of provider:
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
More information through EDIRC
recreation demand; Demand systems; counts; Bayesian analysis;
Other versions of this item:
- Herriges, Joseph A. & Phaneuf, Daniel J. & Tobias, Justin L., 2008. "Estimating demand systems when outcomes are correlated counts," Journal of Econometrics, Elsevier, vol. 147(2), pages 282-298, December.
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
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