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Multivariate count data regression models with individual panel data from an on-site sample

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  • Egan, Kevin
  • Herriges, Joseph

Abstract

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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Bibliographic Info

Article provided by Elsevier in its journal Journal of Environmental Economics and Management.

Volume (Year): 52 (2006)
Issue (Month): 2 (September)
Pages: 567-581

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Handle: RePEc:eee:jeeman:v:52:y:2006:i:2:p:567-581

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Web page: http://www.elsevier.com/locate/inca/622870

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References

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  1. Christopher D. Azevedo & Joseph A. Herriges & Catherine L. Kling, 2003. "Combining Revealed and Stated Preferences: Consistency Tests and Their Interpretations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(3), pages 525-537.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. Whitehead, John C. & Haab, Timothy C. & Huang, Ju-Chin, 2000. "Measuring recreation benefits of quality improvements with revealed and stated behavior data," Resource and Energy Economics, Elsevier, vol. 22(4), pages 339-354, October.
  8. 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.
  9. Murat K. Munkin & Pravin K. Trivedi, 1999. "Simulated maximum likelihood estimation of multivariate mixed-Poisson regression models, with application," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 29-48.
  10. 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.
  11. W. Douglass Shaw, 2002. "Testing the Validity of Contingent Behavior Trip Responses," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(2), pages 401-414.
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Citations

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Cited by:
  1. Morgan, O. Ashton & Huth, William L., 2011. "Using revealed and stated preference data to estimate the scope and access benefits associated with cave diving," Resource and Energy Economics, Elsevier, vol. 33(1), pages 107-118, January.
  2. 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.
  3. Koichi Kuriyama & James Hilger & Michael Hanemann, 2013. "A Random Parameter Model with Onsite Sampling for Recreation Site Choice: An Application to Southern California Shoreline Sportfishing," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 56(4), pages 481-497, December.
  4. Allison Davis & Klaus Moeltner, 2009. "Valuing the Prevention of an Infestation: The Threat of the New Zealand Mud Snail in Northern Nevada," Working Papers 09-001, University of Nevada, Reno, Department of Economics & University of Nevada, Reno , Department of Resource Economics.
  5. Simões, Paula & Barata, Eduardo & Cruz, Luís, 2013. "Joint estimation using revealed and stated preference data: An application using a national forest," Journal of Forest Economics, Elsevier, vol. 19(3), pages 249-266.
  6. Beaumais, Olivier & Appéré, Gildas, 2010. "Recreational shellfish harvesting and health risks: A pseudo-panel approach combining revealed and stated preference data with correction for on-site sampling," Ecological Economics, Elsevier, vol. 69(12), pages 2315-2322, October.
  7. O. Ashton Morgan & D. Matthew Massey & William L. Huth, 2009. "Demand for Diving on Large Ship Artificial Reefs," Working Papers 09-09, Department of Economics, Appalachian State University.
  8. O. Ashton Morgan & Gregory S. Martin & William L. Huth, 2009. "Oyster Demand Adjustments to Counter-Information and Source Treatments in Response to Vibrio vulnificus," Working Papers 09-08, Department of Economics, Appalachian State University.
  9. O. Ashton Morgan & John C. Whitehead & William L. Huth & Gregory S. Martin & Richard Sjolander, 2013. "A Split-Sample Revealed and Stated Preference Demand Model to Examine Homogenous Subgroup Consumer Behavior Responses to Information and Food Safety Technology Treatments," Working Papers 13-06, Department of Economics, Appalachian State University.
  10. O. Ashton Morgan & John C. Whitehead & William L. Huth & Gregory S. Martin & Richard Sjolander, 2013. "Accounting for Heterogeneity in Behavioral Responses to Health-Risk Information Treatments," Working Papers 13-05, Department of Economics, Appalachian State University.
  11. Sébastien Roussel & Jean-Michel Salles & Léa Tardieu, 2012. "Recreation Demand Analysis of the "Sensitive Natural Areas" (Hérault District, France) : A Travel Cost Appraisal using Count Data Models," Working Papers 12-30, LAMETA, Universtiy of Montpellier, revised Sep 2012.
  12. Paula Simões & Luís Cruz & Eduardo Barata, 2012. "Non-market Recreational Value of a National Forest: Survey Design and Results," GEMF Working Papers 2012-09, GEMF - Faculdade de Economia, Universidade de Coimbra.
  13. Chen, Min & Lupi, Frank, 2013. "Modeling Long Overnight Trips by Chaining Recreation Sites," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150489, Agricultural and Applied Economics Association.
  14. Hoyos, David & Riera, Pere, 2013. "Convergent validity between revealed and stated recreation demand data: Some empirical evidence from the Basque Country, Spain," Journal of Forest Economics, Elsevier, vol. 19(3), pages 234-248.
  15. Isabel Mendes & Isabel Proença, 2009. "Measuring the Social Recreation Per-Day Net Benefit of Wildlife Amenities of a National Park: A Count-Data Travel Cost Approach," Working Papers Department of Economics 2009/35, ISEG - School of Economics and Management, Department of Economics, University of Lisbon.
  16. Ferdous, Nazneen & Eluru, Naveen & Bhat, Chandra R. & Meloni, Italo, 2010. "A multivariate ordered-response model system for adults' weekday activity episode generation by activity purpose and social context," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 922-943, September.
  17. Klaus Moeltner & J. Scott Shonkweiler, 2007. "Intercept and Recall: Examining Avidity Carryover in On-Site Collected Travel Data," Working Papers 07-014, University of Nevada, Reno, Department of Economics & University of Nevada, Reno , Department of Resource Economics.
  18. Hynes, Stephen & Greene, William, 2012. "Panel Travel Cost Count Data Models for On-Site Samples that Incorporate Unobserved Heterogeneity with Respect to the Impact of the Explanatory Variables," Working Papers 148834, Socio-Economic Marine Research Unit, National University of Ireland, Galway.
  19. Ash Morgan & Matt Massey & William Huth, 2007. "Diving Demand for Large Ship Artificial Reefs," NCEE Working Paper Series 200709, National Center for Environmental Economics, U.S. Environmental Protection Agency, revised Dec 2007.

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