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Investigating heteroscedasticity using the over-dispersion parameter in a travel cost model

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  • Arwin Pang

    (National Chung Hsing University)

Abstract

This study attempts to discuss the heteroscedasticity in a travel cost model by introducing a parameterized over-dispersion parameter. The Poisson and the negative binomial models are included in the study. The data set is from the National Survey of Fishing, Hunting, and Wildlife-Associated Recreation that was sponsored by the U.S. Fish & Wildlife Service (USFWS) in 2006. The results indicate that the negative binomial model that takes heteroscedasticity into consideration is better than the Poisson model and the other negative binomial model that treats the over-dispersion parameter as a constant. Education and travel cost are found to have negative and significant effects on the over-dispersion parameter.

Suggested Citation

  • Arwin Pang, 2022. "Investigating heteroscedasticity using the over-dispersion parameter in a travel cost model," Letters in Spatial and Resource Sciences, Springer, vol. 15(3), pages 507-516, December.
    • Handle: RePEc:spr:lsprsc:v:15:y:2022:i:3:d:10.1007_s12076-022-00308-6
    DOI: 10.1007/s12076-022-00308-6
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    References listed on IDEAS

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    1. Creel, Michael D. & Loomis, John B., 1992. "Modeling hunting demand in the presence of a bag limit, with tests of alternative specifications," Journal of Environmental Economics and Management, Elsevier, vol. 22(2), pages 99-113, March.
    2. Daniel M. Hellerstein, 1991. "Using Count Data Models in Travel Cost Analysis with Aggregate Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 73(3), pages 860-866.
    3. Jeffrey T. LaFrance, 1990. "Incomplete Demand Systems And Semilogarithmic Demand Models," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 34(2), pages 118-131, August.
    4. Jeffrey T. LaFrance & W. Michael Hanemann, 1989. "The Dual Structure of Incomplete Demand Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 262-274.
    5. Grogger, J T & Carson, Richard T, 1991. "Models for Truncated Counts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(3), pages 225-238, July-Sept.
    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. Cameron, Trudy Ann & Englin, Jeffrey, 1997. "Respondent Experience and Contingent Valuation of Environmental Goods," Journal of Environmental Economics and Management, Elsevier, vol. 33(3), pages 296-313, July.
    8. Jeffrey Englin & Peter Boxall & David Watson, 1998. "Modeling Recreation Demand in a Poisson System of Equations: An Analysis of the Impact of International Exchange Rates," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(2), pages 255-263.
    9. Steven T. Yen & Wiktor L. Adamowicz, 1993. "Statistical Properties of Welfare Measures from Count-Data Models of Recreation Demand," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 15(2), pages 203-215.
    10. von Haefen, Roger H., 2002. "A Complete Characterization Of The Linear, Log-Linear, And Semi-Log Incomplete Demand System Models," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 27(2), pages 1-39, December.
    11. Michael D. Creel & John B. Loomis, 1990. "Theoretical and Empirical Advantages of Truncated Count Data Estimators for Analysis of Deer Hunting in California," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 72(2), pages 434-441.
    12. 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.
    13. Creel, Michael D & Loomis, John B, 1991. "Confidence Intervals for Welfare Measures with Application to a Problem of Truncated Counts," The Review of Economics and Statistics, MIT Press, vol. 73(2), pages 370-373, May.
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    More about this item

    Keywords

    Travel cost model; Heteroscedasticity;

    JEL classification:

    • Q26 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Recreational Aspects of Natural Resources

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