Detection of Turning Points in Business Cycles:
Methods for continuously monitoring business cycles are compared. A turn in a leading index can be used to predict a turn in the business cycle. Three likelihood based methods for turning point detection are compared in detail by using the theory of statistical surveillance and by simulations. One o...
Gespeichert in:
| 1. Verfasser: | |
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| Weitere Verfasser: | , |
| Format: | Elektronisch Buchkapitel |
| Sprache: | English |
| Veröffentlicht: |
Paris
OECD Publishing
2004
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| Schlagworte: | |
| Online-Zugang: | DE-384 DE-473 DE-824 DE-29 DE-739 DE-355 DE-20 DE-1028 DE-1049 DE-521 DE-861 DE-898 DE-92 DE-91 DE-573 DE-19 Volltext |
| Zusammenfassung: | Methods for continuously monitoring business cycles are compared. A turn in a leading index can be used to predict a turn in the business cycle. Three likelihood based methods for turning point detection are compared in detail by using the theory of statistical surveillance and by simulations. One of the methods is a parametric likelihood ratio method. Another includes a non-parametric estimation procedure. The third is based on a Hidden Markov Model. Evaluations are made of several features such as knowledge of shape and parameters of the curve, types and probabilities of transitions and smoothing. Results on the expected delay time [of](to) a correct alarm and the predictive value of an alarm are discussed... |
| Beschreibung: | 1 Online-Ressource (16 Seiten) |
| DOI: | 10.1787/jbcma-v2004-art6-en |
Internformat
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| doi_str_mv | 10.1787/jbcma-v2004-art6-en |
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| spelling | Andersson, Eva Verfasser aut Detection of Turning Points in Business Cycles Eva Andersson, David Bock and Marianne Frisén Paris OECD Publishing 2004 1 Online-Ressource (16 Seiten) txt rdacontent c rdamedia cr rdacarrier Methods for continuously monitoring business cycles are compared. A turn in a leading index can be used to predict a turn in the business cycle. Three likelihood based methods for turning point detection are compared in detail by using the theory of statistical surveillance and by simulations. One of the methods is a parametric likelihood ratio method. Another includes a non-parametric estimation procedure. The third is based on a Hidden Markov Model. Evaluations are made of several features such as knowledge of shape and parameters of the curve, types and probabilities of transitions and smoothing. Results on the expected delay time [of](to) a correct alarm and the predictive value of an alarm are discussed... Economics Bock, David ctb Frisén, Marianne ctb https://doi.org/10.1787/jbcma-v2004-art6-en Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Andersson, Eva Detection of Turning Points in Business Cycles Economics |
| title | Detection of Turning Points in Business Cycles |
| title_auth | Detection of Turning Points in Business Cycles |
| title_exact_search | Detection of Turning Points in Business Cycles |
| title_exact_search_txtP | Detection of Turning Points in Business Cycles |
| title_full | Detection of Turning Points in Business Cycles Eva Andersson, David Bock and Marianne Frisén |
| title_fullStr | Detection of Turning Points in Business Cycles Eva Andersson, David Bock and Marianne Frisén |
| title_full_unstemmed | Detection of Turning Points in Business Cycles Eva Andersson, David Bock and Marianne Frisén |
| title_short | Detection of Turning Points in Business Cycles |
| title_sort | detection of turning points in business cycles |
| topic | Economics |
| topic_facet | Economics |
| url | https://doi.org/10.1787/jbcma-v2004-art6-en |
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