Search Results

Showing results 1 to 1 of approximately 1.

(refine search)
SORT BY: PREVIOUS / NEXT
Author:Böck, Maximilian 

Working Paper
BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R

This document introduces the R library BGVAR to estimate Bayesian global vector autoregressions (GVAR) with shrinkage priors and stochastic volatility. The Bayesian treatment of GVARs allows us to include large information sets by mitigating issues related to overfitting. This improves inference and often leads to better out-of-sample forecasts. Computational efficiency is achieved by using C++ to considerably speed up time-consuming functions. To maximize usability, the package includes numerous functions for carrying out structural inference and forecasting. These include generalized and ...
Globalization Institute Working Papers , Paper 395

FILTER BY Bank

FILTER BY Content Type

FILTER BY Author

FILTER BY Jel Classification

C30 1 items

C50 1 items

C87 1 items

F40 1 items

FILTER BY Keywords

PREVIOUS / NEXT