Economic theory and forecasting: lessons from the literature

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. For the first, we discuss the importance of using the correct econometric tools when answering the question. For the second, we present examples of theory‐based forecasting that have not proven useful, such as theory‐driven variable selection and some popular DSGE models. For the third set of lessons, we discuss 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.