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Modeling Recreation Site Choice: Do Hypothetical Choices Reflect Actual Behavior?

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  • Haener, Michel K.
  • Boxall, Peter C.
  • Adamowicz, Wiktor L.

Abstract

This study examines the ability of revealed preference (RP), site-specific stated preference (SP), transferred SP, and various joint RP-SP models to predict aggregate and individual recreation site choice behavior in a holdout sample. For two statistical comparisons, the site-specific RP model provided the most accurate predictions of individual choices. However, the transferred SP model, applied directly or estimated jointly with the RP data, performed best in three aggregate and one individual prediction tests and second best in the other individual prediction comparisons. In every test examined the transferred SP models outperformed the site-specific SP models. This result is traced to the method used to collect the hypothetical choice data (mail out vs. in-person settings) and illustrates the importance of data quality in accuracy of behavioral prediction. These findings suggest that data from well designed and conducted SP surveys from one site can be combined with site-specific RP data from another site to generate improved models of recreation site choice.

Suggested Citation

  • Haener, Michel K. & Boxall, Peter C. & Adamowicz, Wiktor L., 2000. "Modeling Recreation Site Choice: Do Hypothetical Choices Reflect Actual Behavior?," Staff Paper Series 24124, University of Alberta, Department of Resource Economics and Environmental Sociology.
  • Handle: RePEc:ags:ualbsp:24124
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    Cited by:

    1. Daniel Mccollum & Kevin Boyle, 2005. "The Effect of Respondent Experience/Knowledge in the Elicitation of Contingent Values: An Investigation of Convergent Validity, Procedural Invariance and Reliability," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 30(1), pages 23-33, January.
    2. von Haefen, Roger H. & Phaneuf, Daniel J., 2008. "Identifying demand parameters in the presence of unobservables: A combined revealed and stated preference approach," Journal of Environmental Economics and Management, Elsevier, vol. 56(1), pages 19-32, July.
    3. Norwood, F. Bailey & Lusk, Jayson L. & Brorsen, B. Wade, 2004. "Model Selection for Discrete Dependent Variables: Better Statistics for Better Steaks," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 29(03), December.
    4. Lusk, Jayson L. & Norwood, F. Bailey & Brorsen, B. Wade, 2004. "Forecasting Limited Dependent Variables: Better Statistics For Better Steaks," 2004 Annual Meeting, February 14-18, 2004, Tulsa, Oklahoma 34612, Southern Agricultural Economics Association.
    5. Dmitriy Volinskiy & Wiktor Adamowicz & Michele Veeman, 2011. "Predicting versus testing: a conditional cross‐forecasting accuracy measure for hypothetical bias," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 55(3), pages 429-450, July.
    6. 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.
    7. Joan Mogas & Pere Riera, 2003. "Validación del experimento de elección en la transferencia de beneficios," Hacienda Pública Española, IEF, vol. 165(2), pages 79-95, June.
    8. Birol, Ekin & Kontoleon, Andreas & Smale, Melinda, 2006. "Combining revealed and stated preference methods to assess the private value of agrobiodiversity in Hungarian home gardens:," EPTD discussion papers 156, International Food Policy Research Institute (IFPRI).
    9. John C. Whitehead, 2004. "Environmental Risk and Averting Behavior: Predictive Validity of Revealed and Stated Preference Data," Working Papers 04-13, Department of Economics, Appalachian State University.
    10. Eom, Young-Sook & Larson, Douglas M., 2006. "Improving environmental valuation estimates through consistent use of revealed and stated preference information," Journal of Environmental Economics and Management, Elsevier, vol. 52(1), pages 501-516, July.
    11. Kragt, Marit Ellen & Roebeling, Peter C. & Ruijs, Arjan, 2009. "Effects of Great Barrier Reef degradation on recreational reef-trip demand: a contingent behaviour approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 53(2), June.
    12. Oviedo, José L. & Caparrós, Alejandro & Ruiz-Gauna, Itziar & Campos, Pablo, 2016. "Testing convergent validity in choice experiments: Application to public recreation in Spanish stone pine and cork oak forests," Journal of Forest Economics, Elsevier, vol. 25(C), pages 130-148.
    13. Gallardo, Rosa Karina, 2011. "Choice Experiments’ Findings: A Tool for Fruit Agribusiness Managers’ Decision Making," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association (IFAMA), vol. 14(3).
    14. Wuyang Hu, 2008. "Modeling discrete choices with augmented perception hurdles," Agricultural Economics, International Association of Agricultural Economists, vol. 39(2), pages 257-267, September.
    15. Barton, David N., 2002. "The transferability of benefit transfer: contingent valuation of water quality improvements in Costa Rica," Ecological Economics, Elsevier, vol. 42(1-2), pages 147-164, August.
    16. Phumsith Mahasuweerachai, 2013. "Do Parents Benefit from School Health Risk Reduction?," Applied Economics Journal, Kasetsart University, Faculty of Economics, Center for Applied Economic Research, vol. 20(2), pages 75-95, December.
    17. Schmitz, Kim & Schmitz, P. Michael & Wronka, Tobias C., 2003. "Bewertung von Landschaftsfunktionen mit Choice Experiments," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 52(8).
    18. M. K. Haener & P. C. Boxall & W. L. Adamowicz & D. H. Kuhnke, 2004. "Aggregation Bias in Recreation Site Choice Models: Resolving the Resolution Problem," Land Economics, University of Wisconsin Press, vol. 80(4).
    19. Landry, Craig E. & Liu, Haiyong, 2009. "A semi-parametric estimator for revealed and stated preference data--An application to recreational beach visitation," Journal of Environmental Economics and Management, Elsevier, vol. 57(2), pages 205-218, March.
    20. Bennett, Michael & Provencher, Bill & Bishop, Richard, 2004. "Experience, Expectations and Hindsight: Evidence of a Cognitive Wedge in Stated Preference Retrospectives," Staff Paper Series 468, University of Wisconsin, Agricultural and Applied Economics.
    21. repec:kap:enreec:v:68:y:2017:i:4:d:10.1007_s10640-016-0060-0 is not listed on IDEAS
    22. Pascal Haegeli & Wolfgang Haider & Margo Longland & Ben Beardmore, 2010. "Amateur decision-making in avalanche terrain with and without a decision aid: a stated choice survey," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 52(1), pages 185-209, January.
    23. Cheng, Li & Lupi, Frank, 2016. "Combining Revealed and Stated Preference Methods for Valuing Water Quality Changes to Great Lakes Beaches," 2016 Annual Meeting, July 31-August 2, 2016, Boston, Massachusetts 235746, Agricultural and Applied Economics Association.
    24. Yan, Jiong & Barkmann, Jan & Marggraf, Rainer, 2007. "Chinese tourist preferences for nature based destinations: a choice experiment analysis," DARE Discussion Papers 0706, Georg-August University of Göttingen, Department of Agricultural Economics and Rural Development (DARE).

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