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TOWARD A FRAMEWORK FOR EVALUATING AGRICULTURAL ECONOMICS RESEARCH *
Author(s) -
Lindner Robert K.
Publication year - 1987
Publication title -
australian journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.683
H-Index - 49
eISSN - 1467-8489
pISSN - 0004-9395
DOI - 10.1111/j.1467-8489.1987.tb00668.x
Subject(s) - bayesian probability , agriculture , measure (data warehouse) , value (mathematics) , value of information , information economics , management science , economics , econometrics , regional science , computer science , actuarial science , sociology , microeconomics , geography , mathematical economics , data mining , artificial intelligence , machine learning , archaeology
Agricultural economists need to evaluate their own research priorities. The main difficulty in doing so is to value the types of information generated by economic research. Bayesian decision theory provides a framework for valuing information, and the results of selected studies using this methodology are collated. Most of the other determinants of research priorities can be encapsulated in a target return ratio measure. How such a framework might be used is illustrated by three 'hypotheticals'.