Abstract
In this paper, we propose a hybrid version of Dynamic Stochastic General Equilibrium models with an emphasis on parameter invariance and tracking performance at 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 target ratios driven by 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 2019. An extensive recursive validation exercise over the last 35 years, covering 3 recessions, is used to highlight its parameters invariance, tracking and 1- to 3-step ahead forecasting performance, outperforming those of an unconstrained benchmark Vector AutoRegressive model.
Highlights
Dynamic Stochastic General Equilibrium (DSGE) models are generally justified on the grounds that they provide a structural foundation for policy analysis and are widely used for that purpose
All three coefficients are statistically significant, time invariant, and with the expected signs suggested by the economic theory: when the great ratio ln exceeds its target value as defined in Equation (14), the equilibrium corrections are negative for ∆ ln and positive for ∆ ln and ∆ ln (1 − nt /nt )—that is negative for ∆ ln nt
2b pertain to interventions for d.ˆ Shaded regions correspond to NBER recession dates. We note that both policies significantly mitigate the impact of the recession on output and consumption. While such conclusion would require deeper analysis in the context of a more realistic model, including in particular a labor market, we find these results to be promising indications of the added policy dimensions resulting from interventions at the level of the additional state variables that would otherwise be treated as constant structural parameters within a conventional DSGE framework
Summary
Dynamic Stochastic General Equilibrium (DSGE) models are generally justified on the grounds that they provide a structural foundation for policy analysis and are widely used for that purpose. Their tracking failures in times of rapid changes There is a widely recognized need for greater diversification of the macroeconomics toolbox with models that focus on improved recession tracking performance, possibly at the cost of loosening the theoretical straitjacket of DSGE models. We propose a generic procedure to transform DSGE models into hybrid versions thereof in a way that preserves their policy relevance while significantly improving their recession tracking performance. We rely upon an Error Correction Mechanism (ECM), which has repeatedly proved highly successful in modeling agents’ pursuit of moving targets represented by time-varying cointegration relationships
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
