Estimation in the Linear Decision Model

Walter D. Fisher

No 108, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: Using statistical decision theory with reference to a linear decision model with a quadratic welfare function in the endogenous variables, it is shown that (1) the loss function is different than the usual loss functions implied in prediction models; (2) under the Bayesian assumption that a prior distribution of the unknown parameters exists and under usual data assumptions, the minimum-risk decision implies a certain class of "optimal" estimates of the parameters, which are different from the usual existence; (3) the optimal estimates require some knowledge on the part of the estimating statistician of the decision-maker's welfare function.

Pages: 59 pages
Date: 1961
Note: CFP 174.
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Published in International Economic Review (January 1962), 3(1): 1-29

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