Detection of the Industrial Business Cycle using SETAR models
AbstractWe consider a threshold time series model in order to take into account some stylized facts of the industrial business cycle such as asymmetries in the phase of the cycle. Our aim is to point out some thresholds under (over) which a signal of turning point could be given. First, we introduce the various threshold models and we discuss both their statistical theoretical and empirical properties. Specifically, we review the classical techniques to estimate the number of regimes, the threshold, the delay and the parameters of the model. Then, we apply these models to the euro area industrial production index to detect, through a dynamic simulation approach, the dates of peaks and thoughs in business cycle.
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Date of creation: 2005
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Publication status: Published, Journal of Business Cycle Measurement and Analysis, 2005, 2, 353-371
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Economic cycle – Turning point detection Threshold model – Euro area IPI;
Other versions of this item:
- Laurent Ferrara & Dominique Guégan, 2005. "Detection of the Industrial Business Cycle using SETAR Models," Journal of Business Cycle Measurement and Analysis, OECD Publishing,CIRET, vol. 2005(3), pages 353-371.
- Ferrara, Laurent & Guégan, Dominique, 2005. "Detection of the industrial business cycle using SETAR models," MPRA Paper 4389, University Library of Munich, Germany.
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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