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dc.contributor.authorBock, David
dc.contributor.authorvan Dijk, Dick
dc.contributor.authorFranses, Philip Hans
dc.date.accessioned2011-02-04T13:30:51Z
dc.date.available2011-02-04T13:30:51Z
dc.date.issued2004-01-01
dc.identifier.issn0349-8034
dc.identifier.urihttp://hdl.handle.net/2077/24360
dc.description.abstractIn this paper we develop testing procedures for monitoring the stability of the variance of a time series. While the traditional approach to testing for structural change is retrospective, applying a single test to a historical time series of given length, we consider testing stability in a prospective framework, where the time series are observed online and monitored continuously. The proposed testing procedures have controlled asymptotic size, in that the probability of a false alarm during an infinitely long monitoring period is fixed. A Monte Carlo study is performed to evaluate the test statistics with respect to size and power under different circumstances. We apply our methods to US GDP and its major components in order to investigate when the documented decline in volatility of the US economy during the latter part of the twentieth century could have been detected in real time.sv
dc.format.extent15sv
dc.language.isoengsv
dc.relation.ispartofseriesResearch Reportsv
dc.relation.ispartofseries2004:1sv
dc.subjectStructural changesv
dc.subjectmonitoringsv
dc.subjectvariancesv
dc.subjectstabilitysv
dc.subjectrobustsv
dc.subjectmoving windowsv
dc.subjectcumulative sumsv
dc.titleMonitoring macroeconomic volatilitysv
dc.typeTextsv
dc.type.svepreportsv


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