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- Title
SHRINKAGE ESTIMATION WITH GENERAL LOSS FUNCTIONS: AN APPLICATION OF STOCHASTIC DOMINANCE THEORY.
- Authors
Ashley, Richard
- Abstract
Shrinkage estimation is analyzed using stochastic dominance theory over a broad class of loss functions. (Neither symmetry nor boundedness is imposed.) A recommended shrinkage factor interval is calculated for gaussian, unbiased estimators based on this analysis. Since the minimum MSE estimator is generally found to lie within this interval for t ≥ 1, these results justify the minimum MSE criterion as a desideratum over a wide class of loss functions. Also, the unbiased estimator is found to be dominated by shrunken (biased) estimators over a number of loss function classes. This implies that the unbiased linear projections used to model expectations formation in neoclassical macroeconomic models are stochastically dominated by biased expectations. Finally, practical shrinkage factors are given which are shown to provide modest improvements in expected losses over a wide range of symmetric and asymmetric loss functions.
- Subjects
STOCHASTIC processes; ESTIMATION theory; GAUSSIAN processes
- Publication
International Economic Review, 1990, Vol 31, Issue 2, p301
- ISSN
0020-6598
- Publication type
Article
- DOI
10.2307/2526841