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On Turning Point Detection in Cyclical Processes
With applications to the monitoring of business cycles

By Eva Andersson
December 2001
Almqvist & Wiksell International
ISBN: 91-22-01932-4
168 pages, illustrated
$57.50 paper original

This Ph.D. thesis is based on four papers. In the first, a surveillance system for cyclical processes is presented and its basic properties are described. The aim is to detect a turning point as soon as possible after it has occurred. In the second, the properties of the non-parametric maximum likelihood ratio method for different shapes of the turning point are investigated. In part three, the effect of methods for seasonal adjustment on the ability to detect a turning point is investigated. Since data on business cycles are often monthly or quarterly, seasonal adjustment is necessary. And lastly, in the fourth, a comparison is made between different ways of specifying the monitoring system.

Statistics; Business
Statistika Institutionen, Göteborgs Universitet, Skriftserie No. 27