Cross‐Context Benefit Transfer: A Bayesian Search for Information Pools

20 Pages Posted: 15 Apr 2020

See all articles by Klaus Moeltner

Klaus Moeltner

University of Nevada - Department of Resource Economics

Randall S. Rosenberger

Oregon State University - Department of Forest Resources

Date Written: March 2014

Abstract

Commodity equivalence and population similarity are two widely accepted paradigms for the valid transfer of welfare estimates across resource valuation contexts. We argue that strict adherence to these rules may leave relevant information untapped, and propose a Bayesian model search algorithm that examines the probabilities with which two or more sub‐sets of meta‐data, each corresponding to a different combination of commodity and population, share common value distributions. Using a large meta‐data set of willingness‐to‐pay for diverse outdoor activities across various regions of the United States as an example, we find strong potential for contexts that would not traditionally be considered as transfer candidates to form information pools. Exploiting these commonalities leads to substantial efficiency gains for benefit estimates.

Keywords: Meta-analysis, Bayesian model search, benefit transfer, outdoor recreation

Suggested Citation

Moeltner, Klaus and Rosenberger, Randall S., Cross‐Context Benefit Transfer: A Bayesian Search for Information Pools (March 2014). American Journal of Agricultural Economics, Vol. 96, Issue 2, pp. 469-488, 2014, Available at SSRN: https://ssrn.com/abstract=3573736 or http://dx.doi.org/10.1093/ajae/aat115

Klaus Moeltner (Contact Author)

University of Nevada - Department of Resource Economics ( email )

1664 N. Virginia Street
Reno, NV 89557
United States
(775) 784-4803 (Phone)
(775) 784-1342 (Fax)

Randall S. Rosenberger

Oregon State University - Department of Forest Resources ( email )

Corvallis, OR 97331
United States

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