Evaluating Real-Time VAR Forecasts with an Informative Democratic Prior
33 Pages Posted: 10 Jun 2010
Date Written: May 19, 2010
Abstract
This paper proposes Bayesian forecasting in a vector autoregression using a democratic prior. This prior is chosen to match the predictions of survey respondents. In particular, the unconditional mean for each series in the vector autoregression is centered around long-horizon survey forecasts. Heavy shrinkage toward the democratic prior is found to give good real-time predictions of a range of macroeconomic variables, as these survey projections are good at quickly capturing endpoint-shifts.
Suggested Citation: Suggested Citation
Do you have negative results from your research you’d like to share?
Recommended Papers
-
A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series
By James H. Stock and Mark W. Watson
-
By Marco Aiolfi, Carlos Capistrán, ...
-
Evaluation and Combination of Conditional Quantile Forecasts
-
Optimal Forecast Combinations Under General Loss Functions and Forecast Error Distributions
By Graham Elliott and Allan Timmermann
-
Unit Root Tests are Useful for Selecting Forecasting Models
By Francis X. Diebold and Lutz Kilian
-
Forecast Pooling for Short Time Series of Macroeconomic Variables