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dc.contributor.authorGrabowski, Daniel
dc.contributor.authorStaszewska-Bystrova, Anna
dc.contributor.authorWinker, Peter
dc.date.accessioned2018-03-13T09:08:42Z
dc.date.available2018-03-13T09:08:42Z
dc.date.issued2018-03-08
dc.identifier.urihttp://hdl.handle.net/11089/24232
dc.description.abstractThis Article Investigates The Construction Of Skewness-Adjusted Confidence Intervals And Joint Confidence Bands For Impulse Response Functions From Vector Autoregressive Models. Three Different Implementations Of The Skewness Adjustment Are Investigated. The Methods Are Based On A Bootstrap Algorithm That Adjusts Mean And Skewness Of The Bootstrap Distribution Of The Autoregressive Coefficients Before The Impulse Response Functions Are Computed. Using Extensive Monte Carlo Simulations, The Methods Are Shown To Improve The Coverage Accuracy In Small And Medium Sized Samples And For Unit Root Processes For Both Known And Unknown Lag Orders.pl_PL
dc.publisherFaculty of Economics and Sociologypl_PL
dc.relation.ispartofseriesLodz Economics Working Papers;1;
dc.subjectBootstrappl_PL
dc.subjectconfidence intervalspl_PL
dc.subjectjoint confidence bandspl_PL
dc.subjectvector autoregressionpl_PL
dc.titleSkewness-Adjusted Bootstrap Confidence Intervals and Confidence Bands for Impulse Response Functionspl_PL
dc.typeWorking Paperpl_PL
dc.contributor.authorAffiliationDepartment Of Economics,University Of Giessenpl_PL
dc.contributor.authorAffiliationFaculty of Economics and Sociology, University of Lodzpl_PL
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