Nonparametric Regression and the Detection of Turning Points in the Ifo Business Climate
Klaus Abberger
No 1283, CESifo Working Paper Series from CESifo
Abstract:
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.
Keywords: Nonparametric regression; slope estimation; turning points; business climate indicators (search for similar items in EconPapers)
Date: 2004
New Economics Papers: this item is included in nep-ecm and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)
Downloads: (external link)
https://www.cesifo.org/DocDL/cesifo1_wp1283.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_1283
Access Statistics for this paper
More papers in CESifo Working Paper Series from CESifo Contact information at EDIRC.
Bibliographic data for series maintained by Klaus Wohlrabe ().