Working Paper: CEPR ID: DP6326
Authors: Marta Babura; Domenico Giannone; Lucrezia Reichlin
Abstract: This paper assesses the performance of Bayesian Vector Autoregression (BVAR) for models of different size. We consider standard specifications in the macroeconomic literature based on, respectively, three and eight variables and compare results with those obtained by larger models containing twenty or over one hundred conjunctural indicators. We first study forecasting accuracy and then perform a structural exercise focused on the effect of a monetary policy shock on the macroeconomy. Results show that BVARs estimated on the basis of hundred variables perform well in forecasting and are suitable for structural analysis.
Keywords: Bayesian VAR; Forecasting; Large Cross-Sections; Monetary VAR
JEL Codes: C11; C13; C33; C53
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Bayesian VARs estimated on the basis of 100 variables (C11) | forecasting performance (C53) |
| Bayesian shrinkage (C11) | curse of dimensionality (C46) |
| monetary policy shock (E39) | impulse response functions (C22) |
| adding more information (Y50) | forecast accuracy (C53) |
| model size increases (C52) | confidence intervals for impulse responses (C22) |
| monetary policy on employment (E52) | persistence (C41) |