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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- 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.
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"Combining Revealed and Stated Preferences: Consistency Tests and Their Interpretations,"
Staff General Research Papers Archive
10173, Iowa State University, Department of Economics.
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- Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
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- John C. Whitehead & Timothy C. Haab & Ju-Chin Huang, 1999. "Measuring Recreation Benefits of Quality Improvements with Revealed and Stated Behavior Data," Working Papers 9902, East Carolina University, Department of Economics.
- Englin, Jeffrey & Shonkwiler, J S, 1995. "Estimating Social Welfare Using Count Data Models: An Application to Long-Run Recreation Demand under Conditions of Endogenous Stratification and Truncation," The Review of Economics and Statistics, MIT Press, vol. 77(1), pages 104-12, February.
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