Statistical surveillance of business cycles

dc.contributor.author	Frisén, Marianne
dc.date.accessioned	2011-02-22T14:14:16Z
dc.date.available	2011-02-22T14:14:16Z
dc.date.issued	1994-01-01
dc.identifier.issn	0349-8034
dc.identifier.uri	http://hdl.handle.net/2077/24610
dc.description.abstract	Methods for timely detection of turning-points in business cycles are discussed from a statistical point of view. The theory on optimal surveillance is used to characterize different approaches advocated in literature. This theory is also used to derive a new method for nonparametric detection of turning-points. It utilizes the characteristics of monotonic and unimodal regression. Estimation of parameters m a more or less stable model is thus avoided. Different new ways to evaluate methods are used and discussed. The principles are illustrated by data from Sweden and the USA.	sv
dc.format.extent	42	sv
dc.language.iso	eng	sv
dc.publisher	University of Gothenburg	sv
dc.relation.ispartofseries	Research Report	sv
dc.relation.ispartofseries	1994:1	sv
dc.subject	Early warning	sv
dc.subject	monitoring	sv
dc.subject	index of leading indicators	sv
dc.subject	business cycle	sv
dc.subject	turning-point	sv
dc.subject	optimal	sv
dc.subject	likelihood ratio	sv
dc.subject	nonparametric	sv
dc.subject	unimodal regression	sv
dc.subject	monotonic regression	sv
dc.title	Statistical surveillance of business cycles	sv
dc.type	Text	sv
dc.type.svep	report	sv