Package: bsvarSIGNs
Type: Package
Title: Bayesian SVARs with Sign, Zero, and Narrative Restrictions
Version: 3.0
Date: 2026-08-21
Authors@R: c(
    person(given = "Xiaolei", family = "Wang", email = "adamwang15@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0009-0005-6192-9061")),
    person(given = "Tomasz", family = "Woźniak", email = "wozniak.tom@pm.me", role = c("aut"), comment = c(ORCID = "0000-0003-2212-2378")),
    person(given = "Fei", family = "Shang", email = "sfmax2010@gmail.com", role = c("ctb"), comment = c(ORCID = "0000-0003-1908-3275", "Corrected code for forecasting"))
    )
Maintainer: Xiaolei Wang <adamwang15@gmail.com>
Description: Implements state-of-the-art algorithms for the Bayesian analysis of Structural Vector Autoregressions (SVARs) identified by sign, zero, and narrative restrictions. The core model is based on a flexible Vector Autoregression with estimated hyper-parameters of the Minnesota prior and the dummy observation priors as in Giannone, Lenza, Primiceri (2015) <doi:10.1162/REST_a_00483> extended by the COVID-specific heteroskedasticity proposed by Lenza, Primiceri (2022) <doi:10.1002/jae.2895>. The sign restrictions are implemented employing the methods proposed by Rubio-Ramírez, Waggoner & Zha (2010) <doi:10.1111/j.1467-937X.2009.00578.x>, while identification through sign and zero restrictions follows the approach developed by Arias, Rubio-Ramírez, & Waggoner (2018) <doi:10.3982/ECTA14468>. Furthermore, our toolset provides algorithms for identification via sign and narrative restrictions, in line with the methods introduced by Antolín-Díaz and Rubio-Ramírez (2018) <doi:10.1257/aer.20161852>. Users can also estimate a model with sign, zero, and narrative restrictions imposed at once. The package facilitates predictive and structural analyses using impulse responses, forecast error variance and historical decompositions, forecasting and conditional forecasting, as well as analyses of structural shocks and fitted values. All this is complemented by colourful plots, user-friendly summary functions, and comprehensive documentation including the vignette by Wang & Woźniak (2024) <doi:10.48550/arXiv.2501.16711>. The 'bsvarSIGNs' package is aligned regarding objects, workflows, and code structure with the R packages 'bsvars' by Woźniak (2024) <doi:10.32614/CRAN.package.bsvars>, 'bvars' by Liu, Ramirez Hassan, Woźniak (2026) <doi:10.32614/CRAN.package.bvars>, and 'bpvars' by Woźniak (2026) <doi:10.32614/CRAN.package.bpvars>, and they constitute an integrated toolset. It was granted the Di Cook Open-Source Statistical Software Award by the Statistical Society of Australia in 2024.
License: GPL (>= 3)
Imports: Rcpp (>= 1.0.12), RcppProgress, R6, parallel, generics
LinkingTo: Rcpp, RcppArmadillo, RcppProgress, bsvars
Depends: R (>= 4.1.0), RcppArmadillo, bsvars
Suggests: knitr, tinytest
URL: https://bsvars.org/bsvarSIGNs/,
        https://github.com/bsvars/bsvarSIGNs
BugReports: https://github.com/bsvars/bsvarSIGNs/issues
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
Config/roxygen2/version: 8.0.0
RoxygenNote: 7.3.2
NeedsCompilation: yes
Packaged: 2026-08-21 04:53:44 UTC; adam
Author: Xiaolei Wang [aut, cre] (ORCID:
    <https://orcid.org/0009-0005-6192-9061>),
  Tomasz Woźniak [aut] (ORCID: <https://orcid.org/0000-0003-2212-2378>),
  Fei Shang [ctb] (ORCID: <https://orcid.org/0000-0003-1908-3275>,
    Corrected code for forecasting)
Repository: CRAN
Date/Publication: 2026-08-21 08:20:32 UTC
Built: R 4.6.1; x86_64-w64-mingw32; 2026-08-30 18:40:01 UTC; windows
Archs: x64
