Multivariate Count Data Regression Models with Individual Panel Data from an On-Site Sample
AbstractThe purpose of this paper is to consider the problem of controlling for on-site sampling in the context of a system (or panel) of demand equations. Specifically, in the context of recreation demand, we are concerned with the situation in which survey respondents are asked to provide information not only about the actual trips to a specific site (observed behavior), but also their anticipated trips (either under current conditions or given price and quality changes). A Multivariate Poisson-log normal (MPLN) model and a seemingly unrelated negative binomial (SUNB) model are used to jointly model the observed and contingent behavior data and to correct for on-site sampling.
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Bibliographic InfoPaper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 12573.
Date of creation: 01 Sep 2006
Date of revision:
Publication status: Published in Journal of Environmental Economics and Management, September 2006, vol. 52 no. 2, pp. 567-581
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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:
- Egan, Kevin & Herriges, Joseph, 2006. "Multivariate count data regression models with individual panel data from an on-site sample," Journal of Environmental Economics and Management, Elsevier, vol. 52(2), pages 567-581, September.
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.:
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