Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/172244
Authors: 
Diebold, Francis X.
Schorfheide, Frank
Shin, Minchul
Year of Publication: 
2017
Series/Report no.: 
CFS Working Paper Series 577
Abstract: 
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 background, we explore whether incorporating stochastic volatility improves DSGE forecasts (point, interval, and density). 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.
Subjects: 
Dynamic Stochastic General Equilibrium Model
Prediction
Stochastic Volatility
JEL: 
E17
E27
E37
E47
Persistent Identifier of the first edition: 
Document Type: 
Working Paper
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