Professional forecasters and real-time forecasting with a DSGE model |
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Institution: | 1. School of Economics, UNSW Business School, Gate 2, High Street, UNSW Sydney, NSW, 2052, Australia;2. Melbourne Institute of Applied Economic and Social Research, University of Melbourne, 3010, Victoria, Australia |
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Abstract: | This paper analyses the real-time forecasting performance of the New Keynesian DSGE model of Galí, Smets and Wouters (2012), estimated on euro area data. It investigates the extent to which the inclusion of forecasts of inflation, GDP growth and unemployment by professional forecasters improve the forecasting performance. We consider two approaches for conditioning on such information. Under the “noise” approach, the mean professional forecasts are assumed to be noisy indicators of the rational expectations forecasts implied by the DSGE model. Under the “news” approach, it is assumed that the forecasts reveal the presence of expected future structural shocks in line with those estimated in the past. The forecasts of the DSGE model are compared with those from a Bayesian VAR model, an AR(1) model, a sample mean and a random walk. |
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Keywords: | Bayesian methods Real-time data Survey of Professional Forecasters Macroeconomic forecasting Euro area |
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