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Title: Economic theory and forecasting: lessons from the literature

Author(s): Raffaella Giacomini

Publication Date: October 2014

Keyword(s): Bayesian methods, DSGE models and exponential tilting

Programme Area(s): International Macroeconomics

Abstract: Does economic theory help in forecasting key macroeconomic variables? This article aims to provide some insight into the question by drawing lessons from the literature. The definition of "economic theory" includes a broad range of examples, such as accounting identities, disaggregation and spatial restrictions when forecasting aggregate variables, cointegration and forecasting with Dynamic Stochastic General Equilibrium (DSGE) models. We group the lessons into three themes. The first discusses the importance of using the correct econometric tools when answering the question. The second presents examples of theory-based forecasting that have not proven useful, such as theory-driven variable selection and some popular DSGE models. The third set of lessons discusses types of theoretical restrictions that have shown some usefulness in forecasting, such as accounting identities, disaggregation and spatial restrictions, and cointegrating relationships. We conclude by suggesting that economic theory might help in overcoming the widespread instability that affects the forecasting performance of econometric models by guiding the search for stable relationships that could be usefully exploited for forecasting.

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Bibliographic Reference

Giacomini, R. 2014. 'Economic theory and forecasting: lessons from the literature'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=10201