A New Approach to Random Utility Modeling using the Dirichlet Multinomial Distribution

In this paper we introduce a new econometricapproach to analyzing recreational site choicedata, the Dirichlet multinomial model. Thismodel, which nests the standard conditionalmultinomial logit model, can accommodateover-dispersed data and may provide moreefficient estimators of coefficients andconsequent welfare measures than the standardconditional logit model, which is so widelyused in the Random Utility Model approach torecreation demand. We illustrate thisDirichlet approach using a data set of rockclimbers in Scotland, and study the impacts onper-trip consumers surplus of alternativemanagement strategies for popular rock climbingsites. Results show that the Dirichletmultinomial approach produces coefficient andwelfare estimates having smaller samplingvariability in this case. We also compareclassical welfare measures with their posteriorequivalents, which allow for welfare changes tobe dis-aggregated.

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