Several factors can affect the validity and reliability of benefit transfers. This paper proposes the existence of meta-valuation function and uses meta-regression analysis to estimate this function. The meta-valuation function controls for systematic effects of differences in sample and site characteristics on the magnitude of error associated with an experimental benefit transfer. Validity measures are derived through various specifications of multi-site and single-site travel cost demand models for hiking on a variety of trails in Colorado. The results show that some characteristics account for a large portion of error in the benefit transfer application. When the meta-regression analysis function is adapted for benefit transfer estimation, it results in more accurate and reliable transfer measures than traditional methods
