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

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  • Crainiceanu, Ciprian

    (Cornell U)

  • Vogelsang, Timothy

    (Cornell U)

Abstract

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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Bibliographic Info

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. Peter C.B. Phillips, 1985. "Time Series Regression with a Unit Root," Cowles Foundation Discussion Papers 740R, Cowles Foundation for Research in Economics, Yale University, revised Feb 1986.
  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. 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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Cited by:
  1. Pierre Perron & Tomoyoshi Yabu, 2005. "Estimating Deterministric Trends with an Integrated or Stationary Noise Component," Boston University - Department of Economics - Working Papers Series WP2005-037, Boston University - Department of Economics.
  2. Dukpa Kim & Pierre Perron, 2006. "Assessing the Relative Power of Structural Break Tests Using a Framework Based on the Approximate Bahadur Slope," Boston University - Department of Economics - Working Papers Series WP2006-063, Boston University - Department of Economics.
  3. Altissimo, Filippo & Corradi, Valentina, 2003. "Strong rules for detecting the number of breaks in a time series," Journal of Econometrics, Elsevier, vol. 117(2), pages 207-244, December.
  4. Deng, Ai & Perron, Pierre, 2008. "A non-local perspective on the power properties of the CUSUM and CUSUM of squares tests for structural change," Journal of Econometrics, Elsevier, vol. 142(1), pages 212-240, January.

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