Testing for a Shift in Mean without Having to Estimate Serial-Correlation Parameters
AbstractTests for detecting a shift in the mean of univariate time series that do not require estimation of serial-correlation parameters are proposed. The statistics are valid whether the errors are stationary or have a unit root. The date of the shift may be known or unknown. The statics are based on a simple transformation of the data and are functions of partial sums of the data. These so-called partial sum statistics are shown to be asymptotically invariant to serial-correlation parameters. The statistics are shown to have good size and power properties asymptotically and in finite samples.
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Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 16 (1998)
Issue (Month): 1 (January)
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