{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T19:15:43Z","timestamp":1785870943949,"version":"3.56.0"},"reference-count":30,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T00:00:00Z","timestamp":1771545600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002341","name":"Research Council of Finland","doi-asserted-by":"publisher","award":["347986"],"award-info":[{"award-number":["347986"]}],"id":[{"id":"10.13039\/501100002341","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:title>Summary<\/jats:title>\n                  <jats:p>We complement previous partial global identification results for the non-Gaussian structural vector autoregressive (SVAR) model by showing that in the absence of co-skewness among the strucural shocks, the skewed shocks are identified and in the absence of excess co-kurtosis, the shocks with non-zero excess kurtosis are identified. The former case has the advantage that dependent conditional heteroskedasticity is allowed for. In each case, the remaining shocks are set identified, and these results can be combined to identify both skewed and non-mesokurtic shocks. To capture the non-Gaussian features of the data, versatile error distributions must be specified. We discuss the Bayesian implementation of an SVAR model with skewed t-distributed errors that exhibit dependent stochastic volatility, including the assessment of identification and checking the validity of exogenous instruments potentially used for identification. The methods are illustrated in an empirical application to US monetary policy.<\/jats:p>","DOI":"10.1093\/ectj\/utag002","type":"journal-article","created":{"date-parts":[[2026,2,18]],"date-time":"2026-02-18T12:45:45Z","timestamp":1771418745000},"source":"Crossref","is-referenced-by-count":1,"title":["Identifying structural vector autoregressions via non-Gaussianity of potentially dependent shocks"],"prefix":"10.1093","author":[{"given":"Markku","family":"Lanne","sequence":"first","affiliation":[{"name":"Faculty of Social Sciences, University of Helsinki , Arkadiankatu 7, 00014 Helsinki ,","place":["Finland"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Keyan","family":"Liu","sequence":"additional","affiliation":[{"name":"Economics and Management School, Wuhan University , 299 Bayi Road, 430072 Wuhan ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jani","family":"Luoto","sequence":"additional","affiliation":[{"name":"Faculty of Social Sciences, University of Helsinki , Arkadiankatu 7, 00014 Helsinki ,","place":["Finland"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,2,20]]},"reference":[{"key":"2026042811490747400_bib1","doi-asserted-by":"crossref","DOI":"10.2139\/ssrn.4358059","volume-title":"Bayesian Inference on Fully and Partially Identified Structural Vector Autoregressions","author":"Anttonen","year":"2023"},{"key":"2026042811490747400_bib2","doi-asserted-by":"crossref","first-page":"422","DOI":"10.1002\/jae.3019","article-title":"Statistically identified structural VAR model with potentially skewed and fat-tailed errors","volume":"39","author":"Anttonen","year":"2024","journal-title":"Journal of Applied Econometrics"},{"key":"2026042811490747400_bib3","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.jeconom.2020.12.004","article-title":"Inference in Bayesian proxy-SVARs","volume":"225","author":"Arias","year":"2021","journal-title":"Journal of Econometrics"},{"key":"2026042811490747400_bib4","doi-asserted-by":"crossref","first-page":"1963","DOI":"10.3982\/ECTA12356","article-title":"Sign restrictions, structural vector autoregressions, and useful prior infromation","volume":"83","author":"Baumeister","year":"2015","journal-title":"Econometrica"},{"key":"2026042811490747400_bib6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v076.i01","article-title":"Stan: A probabilistic programming language","volume":"76","author":"Carpenter","year":"2017","journal-title":"Journal of Statistical Software"},{"key":"2026042811490747400_bib7","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1002\/jae.2617","article-title":"Bayesian model comparison for time-varying parameter VARs with stochastic volatility","volume":"33","author":"Chan","year":"2018","journal-title":"Journal of Applied Econometrics"},{"key":"2026042811490747400_bib8","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1080\/07350015.2023.2252039","article-title":"Large order-invariant Bayesian VARs with stochastic volatility","volume":"42","author":"Chan","year":"2024","journal-title":"Journal of Business and Economic Statistics"},{"key":"2026042811490747400_bib9","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/0165-1684(94)90029-9","article-title":"Independent component analysis, A new concept?","volume":"36","author":"Comon","year":"1994","journal-title":"Signal Processing"},{"key":"2026042811490747400_bib10","doi-asserted-by":"crossref","DOI":"10.2139\/ssrn.4469420","volume-title":"Do Monetary Policy Shocks Affect Financial Uncertainty? 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