Real-Time Forecast Evaluation of DSGE Models with Nonlinearities


Recent work has analyzed the forecasting performance of standard dynamic stochastic general equilibrium (DSGE) models, but little attention has been given to DSGE models that incorporate nonlinearities in exogenous driving processes. Against that backgroud, we explore whether incorporating nonlinearities improves DSGE forecasts (point, interval, and density), with emphasis on stochastic volatility. We examine real-time forecast accuracy for key macroeconomic variables including output growth, inflation, and the policy rate. We find that incorporating stochastic volatility in DSGE models of macroeconomic fundamentals markedly improves their density forecasts, just as incorporating stochastic volatility in models of financial asset returns improves their density forecasts.

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@inproceedings{Diebold2015RealTimeFE, title={Real-Time Forecast Evaluation of DSGE Models with Nonlinearities}, author={Francis X. Diebold and Frank Schorfheide and Minchul Shin}, year={2015} }