TY - JOUR

T1 - The impacts of three dimensions of (dis)similarities on water quality benefit transfer errors

AU - Carolus, Johannes Friedrich

AU - Jacobsen, Jette Bredahl

AU - Olsen, Søren Bøye

PY - 2020

Y1 - 2020

N2 - Benefit Transfer (BT) is often applied when a primary valuation study is considered too costly or time consuming to conduct. It is commonly assumed that BT performance improves with increasing similarity between study and policy sites. However, no common criteria for defining similarity exist, making it difficult to operationalise the concept of similarity in a practical BT context. We propose a structured framework for distinguishing between different degrees of similarity. In particular, we differentiate between three dimensions: physical, population and attribute similarity. While the first two are often used in the literature, attribute similarity is not. To investigate the impact attribute descriptions have on BT, we define it as whether or not the same ecosystem service categories are emphasised in the valuation studies. Using value estimates for water quality improvements obtained from 17 Choice Experiments conducted in Europe, we empirically test unit value transfer performance along a similarity gradient. The results confirm that increasing physical similarities across commodities and sites generally lead to lower transfer errors. However, when using income adjusted value transfer, we surprisingly find the opposite. Finally, we demonstrate that increasing attribute similarity may offset dissimilarities in terms of the site characteristics.

AB - Benefit Transfer (BT) is often applied when a primary valuation study is considered too costly or time consuming to conduct. It is commonly assumed that BT performance improves with increasing similarity between study and policy sites. However, no common criteria for defining similarity exist, making it difficult to operationalise the concept of similarity in a practical BT context. We propose a structured framework for distinguishing between different degrees of similarity. In particular, we differentiate between three dimensions: physical, population and attribute similarity. While the first two are often used in the literature, attribute similarity is not. To investigate the impact attribute descriptions have on BT, we define it as whether or not the same ecosystem service categories are emphasised in the valuation studies. Using value estimates for water quality improvements obtained from 17 Choice Experiments conducted in Europe, we empirically test unit value transfer performance along a similarity gradient. The results confirm that increasing physical similarities across commodities and sites generally lead to lower transfer errors. However, when using income adjusted value transfer, we surprisingly find the opposite. Finally, we demonstrate that increasing attribute similarity may offset dissimilarities in terms of the site characteristics.

KW - Benefit transfer

KW - Similarity

KW - Dissimilarity

KW - Transfer error

KW - Water quality

KW - Choice experiment

KW - Water framework directive

KW - WILLINGNESS-TO-PAY

KW - CHOICE EXPERIMENT

KW - CONTINGENT VALUATION

KW - PREFERENCE HETEROGENEITY

KW - NONMARKET BENEFITS

KW - RIVER RESTORATION

KW - SOCIAL BENEFITS

KW - IMPROVEMENTS

KW - VALIDITY

KW - CONTEXT

U2 - 10.1016/j.wre.2020.100164

DO - 10.1016/j.wre.2020.100164

M3 - Journal article

VL - 32

JO - Water Resources and Economics

JF - Water Resources and Economics

SN - 2212-4284

M1 - 100164

ER -