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Testing for a Shift in Mean without Having to Estimate Serial-Correlation Parameters

  • Vogelsang, Timothy J

Tests 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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Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 16 (1998)
Issue (Month): 1 (January)
Pages: 73-80

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Handle: RePEc:bes:jnlbes:v:16:y:1998:i:1:p:73-80
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