Discriminating mean and variance shifts
AbstractA two-stage procedure based on impulse saturation is suggested to distinguish mean and variance shifts. The resulting zero-mean innovation test statistic has a non standard distribution, with a nuisance parameter. Hence, simulation-based critical values are provided for some cases of interest. Monte Carlo evidence reveals the test has good power properties to discriminate mean and variance shifts identified through the impulse saturation break test.
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Bibliographic InfoPaper provided by Faculdade de Economia e Gestão, Universidade Católica Portuguesa (Porto) in its series Working Papers de Economia (Economics Working Papers) with number 14.
Length: 8 pages
Date of creation: Aug 2007
Date of revision:
breaks; mean shift; variance shift; impulse saturation; nuisance parameter;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-10-06 (All new papers)
- NEP-ECM-2007-10-06 (Econometrics)
- NEP-ETS-2007-10-06 (Econometric Time Series)
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