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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- Tobias, Justin & Zellner, Arnold, 2001.
"Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model,"
Staff General Research Papers
12021, Iowa State University, Department of Economics.
- Zellner, Arnold & Tobias, Justin, 2001. "Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(1), pages 121-40, February.
- repec:cup:cbooks:9780521623940 is not listed on IDEAS
- 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.
- 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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