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Benefit Transfer from Multiple Contingent Experiments: A Flexible Two‐Step Model Combining Individual Choice Data with Community Characteristics
Author(s) -
Moeltner Klaus,
Johnston Robert J.,
Rosenberger Randall S.,
Duke Joshua M.
Publication year - 2009
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.1111/j.1467-8276.2009.01344.x
Subject(s) - george (robot) , library science , agricultural experiment station , operations research , management , sociology , political science , agriculture , history , archaeology , engineering , economics , art history , computer science
This study proposes a new approach to utilize information from existing choice experiments to predict policy outcomes for a transfer setting. Recognizing the difficulties from pooling raw data from experiments with different designs and sub-populations we first re-estimate all underlying Random Utility Models individually, and then combine them in a second stage process to form a weighted mixture density for the generation of policy-relevant welfare estimates. Using data from recent choice experiments on farmland preservation we illustrate that our strategy is more robust to transfer inaccuracies than single-site approaches. The specification of "intelligent" mixture weights will be a fruitful ground for future research in the area of Benefit Transfer.