Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/172244 
Erscheinungsjahr: 
2017
Schriftenreihe/Nr.: 
CFS Working Paper Series No. 577
Verlag: 
Goethe University Frankfurt, Center for Financial Studies (CFS), Frankfurt a. M.
Zusammenfassung: 
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.
Schlagwörter: 
Dynamic Stochastic General Equilibrium Model
Prediction
Stochastic Volatility
JEL: 
E17
E27
E37
E47
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

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