Empirical Results on the Size Distribution of Business Cycle Phases

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dc.contributor.author Di Guilmi, Corrado en_US
dc.contributor.author Gaffeo, Edoardo en_US
dc.contributor.author Gallegati, Mauro en_US
dc.contributor.editor en_US
dc.date.accessioned 2010-05-28T09:42:02Z
dc.date.available 2010-05-28T09:42:02Z
dc.date.issued 2004 en_US
dc.identifier 2008004086 en_US
dc.identifier.citation Di Guilmi Corrado, Gaffeo Edoardo, and Gallegati Mauro 2004, 'Empirical Results on the Size Distribution of Business Cycle Phases', Elsevier Science BV, vol. 333, pp. 325-334. en_US
dc.identifier.issn 0378-4371 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/8247
dc.description.abstract We study the size distribution of business cycles phases, that is expansions and contractions, for a sample of 16 industrialized countries over 120 years. We find that the best-fitting distribution for both expansions and contractions is Weibull, meaning that business cycles possess a characteristic scale. Furthermore, we discuss how parameters? estimates can be used to make inference on the probability a typical episode ends, that is on what economists call turning points. en_US
dc.language en_US
dc.publisher Elsevier Science BV en_US
dc.relation.isbasedon http://dx.doi.org/10.1016/j.physa.2003.10.022 en_US
dc.title Empirical Results on the Size Distribution of Business Cycle Phases en_US
dc.parent Physica A: Statistical Mechanics and its Applications en_US
dc.journal.volume 333 en_US
dc.journal.number en_US
dc.publocation The Netherlands en_US
dc.identifier.startpage 325 en_US
dc.identifier.endpage 334 en_US
dc.cauo.name University of Technology, Sydney en_US
dc.conference Verified OK en_US
dc.for 010500 en_US
dc.personcode 105951 en_US
dc.personcode 0000049708 en_US
dc.personcode 0000018259 en_US
dc.percentage 100 en_US
dc.classification.name Mathematical Physics en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords Author Keywords: Business cycles; Weibull distribution; Predictability en_US

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