Abstract
AbstractThis article presents a unified approach to correcting for avidity bias due to onsite sampling in estimation of descriptive statistics and recreation demand. We extend the Shaw (1988) correction for avidity bias in demand modeling to the Generalized Negative Binomial model, and we demonstrate the effects of avidity bias on descriptive statistics. Correcting for avidity bias in recreation demand lowers welfare estimates, which are still, however, quite large at $403/household, per trip (2002 USD). Correcting expenditure estimates increases economic impact by 17%, reflecting greater magnitude in spending patterns of less avid users that live further from Cape Hatteras National Seashore.
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