 Hidden Threshold Models with applications to asymmetric cyclesAndrew Harvey and Jerome Simons Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge Abstract: Threshold models are set up so that there is a switch between regimes for the parameters of an unobserved components model. When Gaussianity is assumed, the model is handled by the Kalman filter. The switching depends on a component crossing a boundary, and, because the component is not observed directly, the error in its estimation leads naturally to a smooth transition mechanism. A prominent example motivating thresholds is that of a cyclical time series characterized by a downturn that is more, or less, rapid than the upturn. The situation is illustrated by fitting a model with three potentially asymmetric cycles, each with its own threshold, to observations on ice volume in Antarctica since 799,000 BCE. The model is able to produce multi-step forecasts with associated prediction intervals. A second example shows how a hidden threshold model is able to deal with the asymmetric cycle in monthly US unemployment. Keywords: Conditionally Gaussian state space model; Kalman filter; nonlinear time series model; regimes; smooth transition autoregressive model; unobserved components (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:2448 Access Statistics for this paper More papers in Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge |
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