TREATMENT OF INCOMPLETE AND MISSING COVARIATE INFORMATION IN A BAYESIAN GENERALIZED LINEAR MODEL OF MARINE RECREATIONAL ANGLER'S CHOICE OF FISHING SITE

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.


Issue Date:
2002
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/19849
Total Pages:
27
Series Statement:
Selected Paper




 Record created 2017-04-01, last modified 2017-04-26

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