IDEAS home Printed from https://ideas.repec.org/p/ags/semrui/148834.html
   My bibliography  Save this paper

Panel Travel Cost Count Data Models for On-Site Samples that Incorporate Unobserved Heterogeneity with Respect to the Impact of the Explanatory Variables

Author

Listed:
  • Hynes, Stephen
  • Greene, William

Abstract

In this paper, we examine heterogeneity in the trip preferences of recreationists by applying a random parameters negative binomial model and a latent class negative binomial model to a panel data set of beach users at a site on the west coast of Ireland. This is the first such attempt in the literature to account for heterogeneity with respect to the impact of the chosen explanatory variables in contingent behaviour travel cost models of demand where the researcher also must account for the fact that the sample data has been collected on-site. The analysis also develops individual consumer surplus estimates and finds that estimates are systematically affected by both the random parameter and latent class specifications. There is also evidence that accounting for individual heterogeneity improves the statistical fit of the models and provides a more informative description of the drivers of recreationalist trip behaviour.

Suggested Citation

  • 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, National University of Ireland, Galway, Socio-Economic Marine Research Unit.
    • Handle: RePEc:ags:semrui:148834
    DOI: 10.22004/ag.econ.148834
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/148834/files/12-WP-SEMRU-07.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.148834?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. John C. Whitehead & Subhrendu K. Pattanayak & George L. Van Houtven & Brett R. Gelso, 2008. "Combining Revealed And Stated Preference Data To Estimate The Nonmarket Value Of Ecological Services: An Assessment Of The State Of The Science," Journal of Economic Surveys, Wiley Blackwell, vol. 22(5), pages 872-908, December.
    2. Stephen Hynes & Nick Hanley & Riccardo Scarpa, 2008. "Effects on Welfare Measures of Alternative Means of Accounting for Preference Heterogeneity in Recreational Demand Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 1011-1027.
    3. Riccardo Scarpa & Mara Thiene, 2004. "Destination Choice Models for Rock Climbing in the Northeast Alps: A Latent-Class Approach Based on Intensity of Participation," Working Papers 2004.131, Fondazione Eni Enrico Mattei.
    4. W. Douglass Shaw & Peter Feather, 1999. "Possibilities for Including the Opportunity Cost of Time in Recreation Demand Systems," Land Economics, University of Wisconsin Press, vol. 75(4), pages 592-602.
    5. Holmes, Thomas P. & Englin, Jeffrey E., 2010. "Preference Heterogeneity in a Count Data Model of Demand for Off-Highway Vehicle Recreation," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 39(1), pages 1-14, February.
    6. 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.
    7. 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.
    8. Riccardo Scarpa & Mara Thiene & Tiziano Tempesta, 2007. "Latent class count models of total visitation demand: days out hiking in the eastern Alps," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 38(4), pages 447-460, December.
    9. 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 104-112, February.
    10. Daniel Hellerstein & Robert Mendelsohn, 1993. "A Theoretical Foundation for Count Data Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 75(3), pages 604-611.
    11. Kenneth E. Train, 1998. "Recreation Demand Models with Taste Differences over People," Land Economics, University of Wisconsin Press, vol. 74(2), pages 230-239.
    12. Kenneth A. Baerenklau, 2010. "A Latent Class Approach to Modeling Endogenous Spatial Sorting in Zonal Recreation Demand Models," Land Economics, University of Wisconsin Press, vol. 86(4), pages 800-816.
    13. Wedel, M, et al, 1993. "A Latent Class Poisson Regression Model for Heterogeneous Count Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(4), pages 397-411, Oct.-Dec..
    14. 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.
    15. Bhat, Chandra R., 2003. "Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 837-855, November.
    16. Nick Hanley & David Bell & Begona Alvarez-Farizo, 2003. "Valuing the Benefits of Coastal Water Quality Improvements Using Contingent and Real Behaviour," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 24(3), pages 273-285, March.
    17. Christie, Michael & Hanley, Nick & Hynes, Stephen, 2007. "Valuing enhancements to forest recreation using choice experiment and contingent behaviour methods," Journal of Forest Economics, Elsevier, vol. 13(2-3), pages 75-102, August.
    18. Roberto Martinez-Espineira & Joe Amoako-Tuffour, 2005. "Recreation Demand Analysis under Truncation, Overdispersion, and Endogenous Stratification: An Application to Gros Morne National Park," Econometrics 0511007, University Library of Munich, Germany.
    19. Riccardo Scarpa & Mara Thiene, 2005. "Destination Choice Models for Rock Climbing in the Northeastern Alps: A Latent-Class Approach Based on Intensity of Preferences," Land Economics, University of Wisconsin Press, vol. 81(3).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stephen Hynes & William Greene, 2016. "Preference Heterogeneity in Contingent Behaviour Travel Cost Models with On-site Samples: A Random Parameter vs. a Latent Class Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(2), pages 348-367, June.
    2. Stephen Hynes & William Greene, 2013. "A Panel Travel Cost Model Accounting for Endogenous Stratification and Truncation: A Latent Class Approach," Land Economics, University of Wisconsin Press, vol. 89(1), pages 177-192.
    3. Hynes, Stephen & Greene, William, 2011. "Estimating recreation demand with on-site panel data: An application of a latent class truncated and endogenously stratified count data model," Working Papers 135171, National University of Ireland, Galway, Socio-Economic Marine Research Unit.
    4. 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.
    5. Voltaire, Louinord & Koutchade, Obafèmi Philippe, 2020. "Public acceptance of and heterogeneity in behavioral beach trip responses to offshore wind farm development in Catalonia (Spain)," Resource and Energy Economics, Elsevier, vol. 60(C).
    6. Nobel, Anne & Lizin, Sebastien & Witters, Nele & Rineau, Francois & Malina, Robert, 2020. "The impact of wildfires on the recreational value of heathland: A discrete factor approach with adjustment for on-site sampling," Journal of Environmental Economics and Management, Elsevier, vol. 101(C).
    7. Massimo Filippini & William Greene & Adan L. Martinez-Cruz, 2018. "Non-market Value of Winter Outdoor Recreation in the Swiss Alps: The Case of Val Bedretto," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(3), pages 729-754, November.
    8. Katsuhito Nohara, 2014. "Economic Valuation of the Damage to Tourism Benefits by Eastern Japan Great Earthquake Disaster," ERSA conference papers ersa14p1017, European Regional Science Association.
    9. Breen, Benjamin & Curtis, John & Hynes, Stephen, 2017. "Recreational Use of Public Waterways and the Impact of Water Quality," Papers WP552, Economic and Social Research Institute (ESRI).
    10. 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 - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    11. Pattiz, Brian David, 2009. "Count regression models for recreation demand: an application to Clear Lake," ISU General Staff Papers 200901010800002092, Iowa State University, Department of Economics.
    12. Amoako-Tuffour, Joe & Martınez-Espineira, Roberto, 2008. "Leisure and the Opportunity Cost of Travel Time in Recreation Demand Analysis: A Re-Examination," MPRA Paper 8573, University Library of Munich, Germany.
    13. Bowker, James Michael & Starbuck, C. Meghan & English, Donald B.K. & Bergstrom, John C. & Rosenberger, Randall S. & McCollum, Daniel W., 2009. "Estimating the Net Economic Value of National Forest Recreation: An Application of the National Visitor Use Monitoring Database," Faculty Series 59603, University of Georgia, Department of Agricultural and Applied Economics.
    14. Lienhoop, Nele & Ansmann, Till, 2011. "Valuing water level changes in reservoirs using two stated preference approaches: An exploration of validity," Ecological Economics, Elsevier, vol. 70(7), pages 1250-1258, May.
    15. Jee W. Hwang & Chun Kuang & Okmyung Bin, 2019. "Are all Homeowners Willing to Pay for Better Schools? ─ Evidence from a Finite Mixture Model Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 58(4), pages 638-655, May.
    16. Agimass, Fitalew & Lundhede, Thomas & Panduro, Toke Emil & Jacobsen, Jette Bredahl, 2018. "The choice of forest site for recreation: A revealed preference analysis using spatial data," Ecosystem Services, Elsevier, vol. 31(PC), pages 445-454.
    17. Curtis, John & Stanley, Brian, 2015. "Water Quality and Recreational Angling Demand in Ireland," Papers WP521, Economic and Social Research Institute (ESRI).
    18. Katsuhito Nohara & Masaki Narukawa, 2015. "Measuring lost recreational benefits in Fukushima due to harmful rumors using a Poisson-inverse Gaussian regression?," ERSA conference papers ersa15p344, European Regional Science Association.
    19. Angel Bujosa & Antoni Riera & Robert Hicks, 2010. "Combining Discrete and Continuous Representations of Preference Heterogeneity: A Latent Class Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 47(4), pages 477-493, December.
    20. 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, Faculty of Economics, University of Coimbra.

    More about this item

    Keywords

    Environmental Economics and Policy; Research Methods/ Statistical Methods;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:semrui:148834. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/semgaie.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.