Real-time forecast evaluation of DSGE models with stochastic volatility

Francis X. Diebold, Frank Schorfheide, Minchul Shin

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)322-332
Number of pages11
JournalJournal of Econometrics
Issue number2
StatePublished - Dec 2017


  • Dynamic stochastic general equilibrium model
  • Prediction
  • Stochastic volatility

ASJC Scopus subject areas

  • Economics and Econometrics


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