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

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CESifo Working Paper ; No. 1283

Classification and Topics

• Classification: Wirtschaft ; Semiparametric and Nonparametric Methods: General ; Classification Discontinued 2008. See C83. ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
• Subject: Nonparametric regression ; slope estimation ; turning points ; business climate indicators ; Geschäftsklima ; Konjunktureller Wendepunkt ; Zeitreihenanalyse ; Regression ; Nichtparametrisches Verfahren ; Schätzung ; Deutschland

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Abberger, Klaus
• Event: Veröffentlichung
• (who): Center for Economic Studies and ifo Institute (CESifo)
• (where): Munich
• (when): 2004

Further information

• Handle: http://hdl.handle.net/10419/18921
• Last update: 10.03.2025, 11:43 AM CET