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We show that sequential Monte Carlo (SMC) estimators can accurately estimate MS\u2010VAR posteriors. Relative to multi\u2010step, model\u2010specific MCMC routines, SMC has the advantages of generality, parallelizability, and freedom from reliance on particular analytical relationships between prior and likelihood. We use SMC's flexibility to demonstrate that model selection among MS\u2010VARs can be highly sensitive to the choice of prior.<\/jats:p>","DOI":"10.1002\/jae.2582","type":"journal-article","created":{"date-parts":[[2017,8,8]],"date-time":"2017-08-08T04:32:22Z","timestamp":1502166742000},"page":"126-140","source":"Crossref","is-referenced-by-count":11,"title":["A sequential Monte Carlo approach to inference in multiple\u2010equation Markov\u2010switching models"],"prefix":"10.1002","volume":"33","author":[{"given":"Mark","family":"Bognanni","sequence":"first","affiliation":[{"name":"Economic Research Department Federal Reserve Bank of Cleveland  Cleveland OH USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Edward","family":"Herbst","sequence":"additional","affiliation":[{"name":"Board of Governors of the Federal Reserve System  Washington"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2017,8,7]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"crossref","unstructured":"Amdahl G. 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