Real-Time Forecast Evaluation of DSGE Models with Stochastic Volatility

Francis X. Diebold, Frank Schorfheide, Minchul Shin

NBER Working Paper No. 22615
Issued in September 2016
NBER Program(s):Asset Pricing, Economic Fluctuations and Growth, International Finance and Macroeconomics

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.

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Document Object Identifier (DOI): 10.3386/w22615

Published: Francis X. Diebold & Frank Schorfheide & Minchul Shin, 2017. "Real-time forecast evaluation of DSGE models with stochastic volatility," Journal of Econometrics, vol 201(2), pages 322-332. citation courtesy of

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