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Spectral Density Bandwidth Choice: Source of Nonmonotonic Power for Tests of a Mean Shift in a Time Series

  • Crainiceanu, Ciprian

    (Cornell U)

  • Vogelsang, Timothy

    (Cornell U)

Data dependent bandwidth choices for zero frequency spectral density estimators of a time series are shown to be an important source of nonmonotonic power when testing for a shift in mean. It is shown that if the spectral density is estimated under the null hypothesis of a stable mean using a data dependent bandwidth (with or without prewhitening), non-monotonic power appears naturally for some popular tests including the CUSUM test. On the other hand, under some fixed bandwidth choices, power is monotonic. Empirical examples and simulations illustrate these power properties. Theoretical explanations for the power results are provided.

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Paper provided by Cornell University, Center for Analytic Economics in its series Working Papers with number 01-14.

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Date of creation: Feb 2001
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Handle: RePEc:ecl:corcae:01-14
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  1. Kiefer, Nicholas M. & Vogelsang, Timothy J., 2005. "A New Asymptotic Theory for Heteroskedasticity-Autocorrelation Robust Tests," Working Papers 05-08, Cornell University, Center for Analytic Economics.
  2. Vogelsang, Timothy J., 1998. "Sources of nonmonotonic power when testing for a shift in mean of a dynamic time series," Journal of Econometrics, Elsevier, vol. 88(2), pages 283-299, November.
  3. Perron, Pierre, 1990. "Testing for a Unit Root in a Time Series with a Changing Mean," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 153-62, April.
  4. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
  5. Vogelsang, Timothy J, 1998. "Testing for a Shift in Mean without Having to Estimate Serial-Correlation Parameters," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(1), pages 73-80, January.
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