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Commonly used priors for Vector Autoregressions (VARs) induce shrinkage on the autoregressive coefficients. Introducing shrinkage on the error covariance matrix is sometimes done but, in the vast majority of cases, without considering the network structure of the shocks and by placing the prior...
Persistent link: https://www.econbiz.de/10015395756
We propose a blended approach which combines identification via heteroskedasticity with the widely used methods of sign restrictions, narrative restrictions, and external instruments.Since heteroskedasticity in the reduced form can be exploited to point identify a set of orthogonal shocks, its...
Persistent link: https://www.econbiz.de/10014356078
Commonly used priors for Vector Autoregressions (VARs) induce shrinkage on the autoregressive coefficients. Introducing shrinkage on the error covariance matrix is sometimes done but, in the vast majority of cases, without considering the network structure of the shocks and by placing the prior...
Persistent link: https://www.econbiz.de/10015407590
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There is a wide literature on the dynamic adjustment of employment and its relationship with the business cycle. Our aim is to propose a statistical model that offers a congruent representation of post-war UK labour market. We use a cointegrated vector autoregressive Markov-switching model where...
Persistent link: https://www.econbiz.de/10014133300
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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...
Persistent link: https://www.econbiz.de/10011389735
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