Spatial heterogeneity in stated preference valuation: State of the art

This paper reviews the progress made over the past decades in controlling for spatial heterogeneity biases in stated preference non-market valuation. Spatial heterogeneity can invalidate results of regression analyses because of the existence of systematic variations of spatial econometric relationships over space. The validity and reliability of willingness-to-pay estimates can be impacted. It can also reduce the transferability of value estimates across sites by introducing transfer errors. For these reasons, spatial heterogeneity deserves more attention in the stated preference valuation literature. We discuss the current state-of-knowledge and review some of the main issues that have been raised in the literature in relation to spatial heterogeneity in stated preference valuation. Issues related to market extent definition, embedding effect, geographic scale and spatial sorting endogenous effects are covered. A thorough review of the existing literature about distance-decay and substitution effects is provided. We present several techniques that have been used so far –mostly grounded in spatial econometrics and spatial statistics– to control for spatial heterogeneity. Some of the remaining challenges that require further investigation are also highlighted. We stress the need to control for the type of good (use vs. non-use values, public vs. private nature), the type of ecosystem under valuation (e.g. ecological constraints, threshold effects) and the need to avoid data validity, reliability and availability issues. We conclude by suggesting potential avenues for future research in light of recent progress made in related disciplines, the evolution of modern technologies and the availability of new data sources.