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Forecasting Output Growth Rates and Median Output Growth Rates: A Hierarchical Bayesian Approach

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Author Info
Tobias, Justin

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Abstract

This paper describes procedures for forecasting countries' output growth rates and medians of a set of output growth rates using Hierarchical Bayesian (HB) models. The purpose of this paper is to show how the gamma-shrinkage forecast of Zellner and Hong (1989) emerges from a hierarchical Bayesian model and to describe how the Gibbs sampler can be used to fit this model to yield possibly improved output growth rate and median output growth rate forecasts. The procedures described in this paper offer two primary methodological contributions to previous work on this topic: (1) the weights associated with widely-used shrinkage forecasts are determined endogenously, and (2) the posterior predictive density of the future median output growth rate is obtained numerically from which optimal point and interval forecasts are calculated. Using IMF data, we find that the HB median output growth rate forecasts outperform forecasts obtained from variety of benchmark models.

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Publisher Info
Paper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number 12023.

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Date of creation: 27 Aug 2004
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Publication status: Published in Journal of Forecasting, 2001, Vol. 20, pp. 297-314.
Handle: RePEc:isu:genres:12023

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  1. Justin L. Tobias & Mingliang Li, 2003. "A finite-sample hierarchical analysis of wage variation across public high schools: evidence from the NLSY and high school and beyond," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(3), pages 315-336. [Downloadable!]
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