Bayesian VARs with Large Panels
Marta Bánbura, Domenico Giannone, Lucrezia Reichlin
Abstract
Marta Bánbura, 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. JEL Classification: C11,C13,C33,C53
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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. JEL Classification: C11,C13,C33,C53
Key concepts: Bayesian vector autoregression, Vector autoregression, Bayesian probability, Econometrics, Shock (circulatory), Autoregressive model, Monetary policy, Economics