Balanced Growth Approach to Forecasting Recessions
No 6487, Working Paper from Department of Economics, University of Pittsburgh
In this paper, we propose a hybrid alternative to Dynamic Stochastic General Equilibrium models with emphasis on forecasting performance in times of rapid changes (recessions). We interpret hypothetical balanced growth ratios as moving targets for economic agents that rely upon an Error-Correction Mechanism to adjust to changes in an underlying state Vector Autoregressive process. Our proposal is illustrated by an application to a pilot Real Business Cycle model for the US economy from 1948 to 2017. An extensive recursive validation exercise over the last 32 years, covering 3 recessions, is used to highlight the impressive parameters invariance and 1 to 4 steps ahead forecasting performance of our hybrid model.
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