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Monthly US business cycle indicators : a new multivariate approach based on a band-pass filter

dc.contributor.authorGómez, Víctorde
dc.contributor.authorMarczak, Martynade
dc.date.accessioned2024-04-08T08:47:56Z
dc.date.available2024-04-08T08:47:56Z
dc.date.created2013-02-13
dc.date.issued2013
dc.description.abstractThis article proposes a new multivariate method to construct business cycle indicators. The method is based on a decomposition into trend-cycle and irregular. To derive the cycle, a multivariate band-pass filter is applied to the estimated trend-cycle. The whole procedure is fully model-based. Using a set of monthly and quarterly US time series, two monthly business cycle indicators are obtained for the US. They are represented by the smoothed cycles of real GDP and the industrial production index. Both indicators are able to reproduce previous recessions very well. Series contributing to the construction of both indicators are allowed to be leading, lagging or coincident relative to the business cycle. Their behavior is assessed by means of the phase angle and the mean phase angle after cycle estimation. The proposed multivariate method can serve as an attractive tool for policy making, in particular due to its good forecasting performance and quite simple setting. The model ensures reliable realtime forecasts even though it does not involve elaborate mechanisms that account for, e.g., changes in volatility.en
dc.identifier.swb378703730
dc.identifier.urihttps://hohpublica.uni-hohenheim.de/handle/123456789/5667
dc.identifier.urnurn:nbn:de:bsz:100-opus-8087
dc.language.isoeng
dc.relation.ispartofseriesFZID discussion papers; 64
dc.rights.licensepubl-ohne-poden
dc.rights.licensepubl-ohne-podde
dc.rights.urihttp://opus.uni-hohenheim.de/doku/lic_ubh.php
dc.subjectBusiness cycleen
dc.subjectMultivariate structural time series modelen
dc.subjectForecastsen
dc.subjectPhase angleen
dc.subject.ddc330
dc.subject.gndKonjunkturzyklusde
dc.subject.gndKonjunkturindikatorde
dc.subject.gndUSAde
dc.titleMonthly US business cycle indicators : a new multivariate approach based on a band-pass filterde
dc.type.dcmiTextde
dc.type.diniWorkingPaperde
local.accessuneingeschränkter Zugriffen
local.accessuneingeschränkter Zugriffde
local.bibliographicCitation.publisherPlaceUniversität Hohenheimde
local.export.bibtex@techreport{Gómez2013, url = {https://hohpublica.uni-hohenheim.de/handle/123456789/5667}, author = {Gómez, Víctor and Marczak, Martyna}, title = {Monthly US business cycle indicators : a new multivariate approach based on a band-pass filter}, year = {2013}, school = {Universität Hohenheim}, series = {FZID discussion papers}, }
local.export.bibtexAuthorGómez, Víctor and Marczak, Martyna
local.export.bibtexKeyGómez2013
local.export.bibtexType@techreport
local.faculty.number3de
local.faculty.number7de
local.institute.number520de
local.institute.number795de
local.opus.number808
local.series.issueNumber64
local.series.titleFZID discussion papers
local.universityUniversität Hohenheimde
local.university.facultyFaculty of Business, Economics and Social Sciencesen
local.university.facultyFakultät Wirtschafts- und Sozialwissenschaftende
local.university.facultyLandesanstaltende
local.university.instituteInstitute for Economicsen
local.university.instituteInstitut für Volkswirtschaftslehrede
local.university.instituteForschungszentrum Innovation und Dienstleistungde

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