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Nonparametric regression and the detection of turning points in the Ifo business climate

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dc.creator Abberger, Klaus
dc.date 2004
dc.date.accessioned 2013-10-16T07:01:57Z
dc.date.available 2013-10-16T07:01:57Z
dc.date.issued 2013-10-16
dc.identifier http://hdl.handle.net/10419/18921
dc.identifier ppn:472778773
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/10419/18921
dc.description Business climate indicators are used to receive early signals for turning points in the general business cycle. Therefore methods for the detection of turning points in time series are required. Estimations of slopes of a smooth component in the data can be calculated with local polynomial regression. A change in the sign of the slope can be interpreted as a turning point. A plug-in method is used for data-based bandwidth choice. Since in practice the identification of turning points at the actual boundary of the time series is of special interest, this situation is discussed in more detail. The nonparametric approach is applied to the Ifo Business Climate to demonstrate the application of the nonparametric approach and to analyze the time lead of the indicator.
dc.language eng
dc.publisher
dc.relation CESifo working papers 1283
dc.rights http://www.econstor.eu/dspace/Nutzungsbedingungen
dc.subject C14
dc.subject C42
dc.subject C22
dc.subject ddc:330
dc.subject Nonparametric regression
dc.subject slope estimation
dc.subject turning points
dc.subject business climate indicators
dc.subject Geschäftsklima
dc.subject Konjunktureller Wendepunkt
dc.subject Zeitreihenanalyse
dc.subject Regression
dc.subject Nichtparametrisches Verfahren
dc.subject Schätzung
dc.subject Deutschland
dc.title Nonparametric regression and the detection of turning points in the Ifo business climate
dc.type doc-type:workingPaper


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