Abstract #301015


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JSM 2002 Abstract #301015
Activity Number: 310
Type: Contributed
Date/Time: Wednesday, August 14, 2002 : 10:30 AM to 12:20 PM
Sponsor: Business & Economics Statistics Section*
Abstract - #301015
Title: On-line Detection of Turning Points in Business Cycles
Author(s): Eva Andersson*+
Affiliation(s): Goteborg University, Sweden
Address: PO Box 660, Goteborg, , SE-405 30, Sweden
Keywords: Business cycles ; Likelihood ratio ; Monitoring ; Turning point detection ; Regime switching ; Nonparametric regression
Abstract:

In many areas, it is important to detect the turning points in an on-going process. Two examples are detection of turns in business cycles and so-called natural family planning. The setting is prospective (contrary to a retrospective study) and so the methodology of statistical surveillance is suitable. The monitoring systems under study are developed in order to detect a turning point as soon as possible after it has occurred. Generally, a monitoring system is based on an alarm statistic and alarm limits. Monitoring methods based on the full likelihood (with many similarities with HMM-based methods) are compared to a new method, which is completely non-parametric regarding the shape of the turning point. Evaluations are made of features such as knowledge of shape and parameters of the curve. Also, the pros and cons of using prior information regarding the intensity of the turning points are discussed. The methods are made comparable by setting alarm limits which give the same false alarm probability. The performance is evaluated using measures that reflect timelines--for example, the expected delay time to a motivated alarm and the predictive value of an alarm at a specific time


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