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dc.contributor.authorAndreou, Elenaen
dc.contributor.authorGhysels, Ericen
dc.contributor.authorKourtellos, Androsen
dc.contributor.editorClements, Michael P.en
dc.contributor.editorHendry, David F.en
dc.coverage.spatialOxforden
dc.creatorAndreou, Elenaen
dc.creatorGhysels, Ericen
dc.creatorKourtellos, Androsen
dc.date.accessioned2019-05-03T05:21:46Z
dc.date.available2019-05-03T05:21:46Z
dc.date.issued2012
dc.identifier.isbn978-0-19-994032-5
dc.identifier.isbn978-0-19-539864-9
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/47088
dc.description.abstractThis article, which presents a regression framework that relates the quarterly macro variable (such as GDP growth) to higher-frequency variables in a relatively simple, parsimonious way, is organized as follows. Section 2 covers mixed data sampling (MIDAS) regressions. Section 3 covers so-called nowcasting, and the Kalman filter and its relationship with MIDAS regressions. The final section discusses volatility models using mixed frequencies. © 2011 by Oxford University Press. All rights reserved.en
dc.language.isoengen
dc.publisherOxford University Pressen
dc.subjectMIDAS regressionsen
dc.subjectKalman filteren
dc.subjectMacroeconomic variablesen
dc.subjectMixed data samplingen
dc.subjectNowcastingen
dc.subjectVolatility modelsen
dc.titleForecasting with Mixed-Frequency Dataen
dc.typeinfo:eu-repo/semantics/bookChapter
dc.author.facultyΣχολή Οικονομικών Επιστημών και Διοίκησης / Faculty of Economics and Management
dc.author.departmentΤμήμα Οικονομικών / Department of Economics
dc.type.uhtypeBook Chapteren
dc.contributor.orcidKourtellos, Andros [0000-0001-9662-0420]
dc.gnosis.orcid0000-0001-9662-0420


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