bsvars

Efficient algorithms for Bayesian estimation of Structural Vector Autoregressive (SVAR) models via Markov chain Monte Carlo methods. A wide range of SVAR models is considered, including homo- and heteroskedastic specifications and those with non-normal structural shocks. The heteroskedastic SVAR model setup is similar as in Woźniak & Droumaguet (2015) doi:10.13140/RG.2.2.19492.55687 and Lütkepohl & Woźniak (2020) doi:10.1016/j.jedc.2020.103862. The sampler of the structural matrix follows Waggoner & Zha (2003) doi:10.1016/S0165-1889(02)00168-9, whereas that for autoregressive parameters follows Chan, Koop, Yu (2022) . The specification of Markov switching heteroskedasticity is inspired by Song & Woźniak (2021) doi:10.1093/acrefore/9780190625979.013.174, and that of Stochastic Volatility model by Kastner & Frühwirth-Schnatter (2014) doi:10.1016/j.csda.2013.01.002.