Prediction Using Several Macroeconomic Models

Gianni Amisano and John Geweke
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John Geweke: University of Washington

The Review of Economics and Statistics, 2017, vol. 99, issue 5, 912–925

Abstract: We establish methods that improve the predictions of macroeconometric models—dynamic factor models, dynamic stochastic general equilibrium models, and vector autoregressions—using a quarterly U.S. data set. We measure prediction quality with one-step-ahead probability densities assigned in real time. Two steps lead to substantial improvements: (a) the use of full Bayesian predictive distributions rather than conditioning on the posterior mode for parameters and (b) the use of an equally weighted pool.

Date: 2017
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Working Paper: Prediction using several macroeconomic models (2013)
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