Real-Time Density Forecasts from BVARs with Stochastic Volatility

نویسنده

  • Todd E. Clark
چکیده

Central banks and other forecasters are increasingly interested in various aspects of density forecasts. However, recent sharp changes in macroeconomic volatility – such as the Great Moderation and the more recent sharp rise in volatility associated with greater variation in energy prices and the deep global recession – pose significant challenges to density forecasting. Accordingly, this paper examines, with real-time data, density forecasts of U.S. GDP growth, unemployment, inflation, and the federal funds rate from BVAR models with stochastic volatility. The results indicate that adding stochastic volatility to BVARs materially improves the real-time accuracy of density forecasts.

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تاریخ انتشار 2009