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AJAE Appendix: Dynamic Random Utility Modeling: A Monte Carlo Analysis

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  • Hicks, Robert L.
  • Schnier, Kurt E.

Abstract

Applied studies of commercial fishing have largely ignored the intertemporal aspects of repeated site choices. For many fisheries, fishermen might choose a dynamically optimal cruise trajectory rather than myopic day-to-day strategies and a model that ignores these considerations will likely lead to biased parameter estimates and poor policy guidance. A dynamic random utility model is developed that utilizes the same information as static site-choice models but is entrenched in the principles of dynamic optimization. Using Monte Carlo analysis, we evaluate the performance of this estimator as compared to the static model for a variety of simulated fishery types. Copyright 2006, Oxford University Press.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Hicks, Robert L. & Schnier, Kurt E., 2006. "AJAE Appendix: Dynamic Random Utility Modeling: A Monte Carlo Analysis," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 88(4), pages 1-23, November.
  • Handle: RePEc:ags:ajaeap:7397
    DOI: 10.22004/ag.econ.7397
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    Cited by:

    1. Carrella, Ernesto & Saul, Steven & Marshall, Kristin & Burgess, Matthew G. & Cabral, Reniel B. & Bailey, Richard M. & Dorsett, Chris & Drexler, Michael & Madsen, Jens Koed & Merkl, Andreas, 2020. "Simple Adaptive Rules Describe Fishing Behaviour Better than Perfect Rationality in the US West Coast Groundfish Fishery," Ecological Economics, Elsevier, vol. 169(C).
    2. William C. Horrace & Kurt E. Schnier, 2010. "Fixed-Effect Estimation of Highly Mobile Production Technologies," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(5), pages 1432-1445.
    3. Paudel, Krishna P. & Caffey, Rex H. & Devkota, Nirmala, 2011. "An Evaluation of Factors Affecting the Choice of Coastal Recreational Activities," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 43(2), pages 167-179, May.
    4. Kim, Yusun & Reeling, Carson & Widmar, Nicole J.O. & Lee, John G., 2023. "Estimating a model of forward-looking behavior with discrete choice experiments: The case of lifetime hunting license demand," Journal of choice modelling, Elsevier, vol. 47(C).
    5. Hicks, Robert L. & Schnier, Kurt E., 2006. "A Spatial Model of Dolphin Avoidance in the Eastern Tropical Pacific Ocean," 2006 Annual meeting, July 23-26, Long Beach, CA 21290, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Stafford, Tess M., 2018. "Accounting for outside options in discrete choice models: An application to commercial fishing effort," Journal of Environmental Economics and Management, Elsevier, vol. 88(C), pages 159-179.
    7. Junjie Zhang & Martin Smith, 2011. "Heterogeneous Response to Marine Reserve Formation: A Sorting Model approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 49(3), pages 311-325, July.
    8. Reeling, Carson & Verdier, Valentin & Lupi, Frank, 2016. "Valuing Natural Resources Allocated by Dynamic Lottery," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235673, Agricultural and Applied Economics Association.
    9. Todd Guilfoos & Priya Thomas & Sonja Kolstoe, 2024. "Estimating habit‐forming and variety‐seeking behavior: Valuation of recreational birdwatching," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(3), pages 1193-1216, May.
    10. Chen, Min & Lupi, Frank, 2009. "Does economic endogeneity of site facilities in recreation demand models lead to statistical endogeneity?," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49449, Agricultural and Applied Economics Association.
    11. Abbott, Joshua K. & Wilen, James E., 2011. "Dissecting the tragedy: A spatial model of behavior in the commons," Journal of Environmental Economics and Management, Elsevier, vol. 62(3), pages 386-401.
    12. Hicks, Robert L. & Schnier, Kurt E., 2010. "Spatial regulations and endogenous consideration sets in fisheries," Resource and Energy Economics, Elsevier, vol. 32(2), pages 117-134, April.
    13. Keita Abe & Christopher M. Anderson & Matthew N. Reimer, 2022. "Catch More to Catch Less: Estimating Timing Choice as Dynamic Bycatch Avoidance Behavior," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 82(4), pages 953-984, August.
    14. Reimer, Matthew N. & Abbott, Joshua K. & Haynie, Alan C., 2022. "Structural behavioral models for rights-based fisheries," Resource and Energy Economics, Elsevier, vol. 68(C).
    15. C. Haynie, Alan & F. Layton, David, 2010. "An expected profit model for monetizing fishing location choices," Journal of Environmental Economics and Management, Elsevier, vol. 59(2), pages 165-176, March.
    16. Shi Zheng & Pei Xu & Zhigang Wang, 2012. "Farmers' adoption of new plant varieties under variety property right protection," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 4(1), pages 124-140, January.
    17. Hicks, Robert L. & Schnier, Kurt E., 2008. "Eco-labeling and dolphin avoidance: A dynamic model of tuna fishing in the Eastern Tropical Pacific," Journal of Environmental Economics and Management, Elsevier, vol. 56(2), pages 103-116, September.
    18. Stafford, Tess, 2012. "Ignoring the Multi-species Aspect of Labor Supply Decisions in Spatially Explicit Bio-economic Fishery Models," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124367, Agricultural and Applied Economics Association.

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