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Treatment Of Incomplete And Missing Covariate Information In A Bayesian Generalized Linear Model Of Marine Recreational Angler'S Choice Of Fishing Site

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  • Graybeal, Dale K.

Abstract

Economic surveys often report income via a categorical variable, and income and wage information is often missing altogether for a large fraction of the sample. The Bayesian inferential framework allows one to specify and estimate models for incomplete and missing covariate information. Here multiple choice models of recreational anglers' choice of fishing site are estimated and alternative specifications for incomplete and missing income and wage data are compared.

Suggested Citation

  • Graybeal, Dale K., 2002. "Treatment Of Incomplete And Missing Covariate Information In A Bayesian Generalized Linear Model Of Marine Recreational Angler'S Choice Of Fishing Site," 2002 Annual meeting, July 28-31, Long Beach, CA 19849, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    • Handle: RePEc:ags:aaea02:19849
    DOI: 10.22004/ag.econ.19849
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    References listed on IDEAS

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    1. Morey, Edward R. & Waldman, Donald M., 1998. "Measurement Error in Recreation Demand Models: The Joint Estimation of Participation, Site Choice, and Site Characteristics," Journal of Environmental Economics and Management, Elsevier, vol. 35(3), pages 262-276, May.
    2. Jackman, Simon, 2000. "Estimation and Inference Are Missing Data Problems: Unifying Social Science Statistics via Bayesian Simulation," Political Analysis, Cambridge University Press, vol. 8(4), pages 307-332, July.
    3. Pelloni, Gianluigi, 1996. "De Finetti, Friedman, and the methodology of positive economics," Journal of Econometrics, Elsevier, vol. 75(1), pages 33-50, November.
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