Record Details

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

ScholarsArchive at Oregon State University

Field Value
Title Cross-Context Benefit Transfer: A Bayesian Search for Information Pools
Names Moeltner, Klaus (creator)
Rosenberger, Randall S. (creator)
Date Issued 2014-01-22 (iso8601)
Note This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by the author(s) and published by Oxford University Press on behalf of the Agricultural and Applied Economics Association. The published article can be found at: http://ajae.oxfordjournals.org/.
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. We 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 as an example a large meta-data set of willingness-to-pay for diverse outdoor activities across different regions of the U.S., 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.
Genre Article
Topic Meta-analysis
Identifier Moeltner, K., & Rosenberger, R. S. (2014). Cross-context benefit transfer: a Bayesian search for information pools. American Journal of Agricultural Economics, 96(2), 469-488. doi:10.1093/ajae/aat115

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