chapter  19
14 Pages

Are benefit transfers using a joint revealed and stated preference model more accurate than revealed and stated preference data alone?: Juan Marcos González-Sepúlveda and John B. Loomis

ByJUAN MARCOS GONZÁLEZ - SEPÚLVEDA AND

Introduction Benefit transfer refers to the application of existing information and knowledge to new contexts. It is the adaptation of economic information derived from a prior “study site” with certain resource and policy conditions and applied to a “policy site” where no data is available. Economists often lack the information for the policy site because of budget constraints, time limitations or low expected resource impacts. In this scenario, and in the need to evaluate the effect that a particular action may have, benefit transfers become a second best approach to consider economic effects that would otherwise not be accounted for (Rosenberger and Loomis 2001). There are two broad types of transfers: value transfers and function transfers. In the first one a single benefit estimate is transferred to the policy site. This measure could be a single point estimate from a similar study site. In recreation, these single values are most often obtained from travel cost models (TCM) and/ or contingent valuation methods (CVM). On the other hand, a function transfer is to derive a benefit or demand function from the study site to be used to predict benefits and/or site visitation by inserting the particular characteristics of the policy site into the estimated function. Single value estimates and visitation estimates for benefit transfers are commonly obtained from different sources. Even when these estimates are obtained from the same data source, they are often not derived consistently in a unified utility theoretic framework. We address this shortcoming by using a consistent joint estimation procedure that makes use of all the information available for the estimation of single values by combining CVM and TCM. The joint estimation procedure permits consistent transfer to predict both recreation demand and seasonal/annual benefits for a policy site. This is of particular interest when the policy site is newly available to the public at which neither past use nor per-trip benefit is known.