Bayesian shrinkage estimates and forecasts of individual and total or aggregate outcomes
Bayesian shrinkage à la Stein and others can improve estimation of individual parameters and forecasts of individual future outcomes. In this paper the issue of the impact of shrinkage on the estimation of sums or totals of individual parameters and of individual outcomes is analyzed. Quadratic and "balanced" loss functions will be employed. The latter are a linear combination of "goodness of fit" and "precision of estimation" loss functions. Several examples will be analyzed in detail to illustrate general principles.
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- Zellner, Arnold & Chen, Bin, 2001. "Bayesian Modeling Of Economies And Data Requirements," Macroeconomic Dynamics, Cambridge University Press, vol. 5(05), pages 673-700, November.
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- Tobias, Justin & Zellner, Arnold, 2001. "Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model," Staff General Research Papers Archive 12021, Iowa State University, Department of Economics.
- Zellner, Arnold, 1998. "The finite sample properties of simultaneous equations' estimates and estimators Bayesian and non-Bayesian approaches," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 185-212.
- Dey, Dipak K. & Ghosh, Malay & Strawderman, William E., 1999. "On estimation with balanced loss functions," Statistics & Probability Letters, Elsevier, vol. 45(2), pages 97-101, November. Full references (including those not matched with items on IDEAS)