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We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...
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The estimation of large vector autoregressions with stochastic volatility using standard methods is computationally … on a common stochastic volatility factor, we derive the posterior densities for the parameters of the resulting BVAR with … common stochastic volatility (BVAR-CSV). Under the chosen prior, the conditional posterior of the VAR coefficients features a …
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