Multivariate count data regression models with individual panel data from an on-site sample
The 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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Staff General Research Papers
10173, Iowa State University, Department of Economics.
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- Klaus Moeltner & J. Scott Shonkwiler, 2005. "Correcting for On-Site Sampling in Random Utility Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(2), pages 327-339.
- Laitila, Thomas, 1999. "Estimation of combined site-choice and trip-frequency models of recreational demand using choice-based and on-site samples," Economics Letters, Elsevier, vol. 64(1), pages 17-23, July.
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- Grogger, J T & Carson, Richard T, 1991. "Models for Truncated Counts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(3), pages 225-38, July-Sept.
- Shaw, Daigee, 1988. "On-site samples' regression : Problems of non-negative integers, truncation, and endogenous stratification," Journal of Econometrics, Elsevier, vol. 37(2), pages 211-223, February.
- Jeffrey Englin & Trudy Cameron, 1996. "Augmenting travel cost models with contingent behavior data," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 7(2), pages 133-147, March.
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