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• W173366585 abstract "This chapter discusses the problem of evaluating econometric models as a particular case of a general class of problems called decision problems. It discusses what light can be shed by Bayesian decision theory on the evaluation of econometric models. Suppose, the decisions d that might be chosen lie in some decision space D. There is some space Ω of possible alternative circumstances θ and one's opinion over this space is given by the probability density with element p(θ) d θ. If one's utility function is U(d, θ), representing the relative desirability of the decision d if the alternative θ were true, Bayesian decision theory recommends that one should choose that decision d that maximizes the integral ∫Ω U(d, θ) p(θ) d θ. The view that this simple paradigm might play a fundamental role in statistics by providing a theory analogous to price theory in microeconomics has been met with considerable controversy among statisticians. Some statisticians maintain that the inputs, particularly the opinion p(θ)d θ and the utility function U(d, θ), are very difficult to obtain in applied contexts, while others resist the notion of any kind of organizing principle for statistics." @default.
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• W173366585 date "1980-01-01" @default.
• W173366585 modified "2023-09-25" @default.
• W173366585 title "Bayesian Decision Theory and the Simplification of Models" @default.
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• W173366585 doi "https://doi.org/10.1016/b978-0-12-416550-2.50018-2" @default.
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