{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/bayesian-inference-for-structural-vector","title":"Bayesian Inference for Structural Vector Autoregressions Identified by Markov-Switching Heteroskedasticity","arxiv_id":"1811.08167","date":"2018-11-20","proceeding":null,"authors":[],"abstract":"In this study, Bayesian inference is developed for structural vector\nautoregressive models in which the structural parameters are identified via\nMarkov-switching heteroskedasticity. In such a model, restrictions that are\njust-identifying in the homoskedastic case, become over-identifying and can be\ntested. A set of parametric restrictions is derived under which the structural\nmatrix is globally or partially identified and a Savage-Dickey density ratio is\nused to assess the validity of the identification conditions. The latter is\nfacilitated by analytical derivations that make the computations fast and\nnumerical standard errors small. As an empirical example, monetary models are\ncompared using heteroskedasticity as an additional device for identification.\nThe empirical results support models with money in the interest rate reaction\nfunction.","url_abs":"http://arxiv.org/abs/1811.08167v1","url_pdf":"http://arxiv.org/pdf/1811.08167v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"bayesian-inference-for-structural-vector","repo_url":"https://github.com/donotdespair/SVAR-MSH-ID","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"bayesian-inference","task_name":"Bayesian Inference"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}