Frisén, Marianne2011-02-222011-02-221994-01-010349-8034http://hdl.handle.net/2077/24610Methods 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.42engEarly warningmonitoringindex of leading indicatorsbusiness cycleturning-pointoptimallikelihood rationonparametricunimodal regressionmonotonic regressionText