Comparison of Two Alternative Approaches to Modeling Level Shifts in the Presence of Outliers
AbstractWe study alternative models for capturing abrupt structural changes (level shifts) in a times series. The problem is confounded by the presence of transient outliers. We compare the performance of non-Gaussian time-varying parameter models and multiprocess mixture models within a Monte Carlo experimental setup. Our findings suggest that once we incorporate shocks with thick-tailed probability distributions, the superiority of the multiprocess mixture models over the time-varying parameter models, reported in an earlier study, disappears. The behavior of the two models, both in adapting to level shifts and in reacting to transient outliers, is very similar.
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Bibliographic InfoPaper provided by Florida International University, Department of Economics in its series Working Papers with number 0307.
Length: 18 pages
Date of creation: Jul 2003
Date of revision:
Publication status: Published in Communications in Statistics: Simulation and Computation, 33(3):661-671, (2004).
time-varying parameter (TVP) models; non-Gaussian state space models; multiprocess mixture models; level shifts; outliers;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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