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Mean and autocovariance function estimation near the boundary of stationarity

Listed author(s):
  • Giraitis, Liudas
  • Phillips, Peter C.B.

We analyze the applicability of standard normal asymptotic theory for linear process models near the boundary of stationarity. Limit results are given for estimation of the mean, autocovariance and autocorrelation functions within the broad region of stationarity that includes near boundary cases which vary with the sample size. The rate of consistency and the validity of the normal asymptotic approximation for the corresponding estimators is determined both by the sample size n and a parameter measuring the proximity of the model to the unit root boundary.

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File URL: http://www.sciencedirect.com/science/article/pii/S0304407612000309
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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 169 (2012)
Issue (Month): 2 ()
Pages: 166-178

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Handle: RePEc:eee:econom:v:169:y:2012:i:2:p:166-178
DOI: 10.1016/j.jeconom.2012.01.020
Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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  1. Liudas Giraitis & Peter C. B. Phillips, 2006. "Uniform Limit Theory for Stationary Autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(1), pages 51-60, 01.
  2. Phillips, Peter C.B. & Magdalinos, Tassos, 2007. "Limit theory for moderate deviations from a unit root," Journal of Econometrics, Elsevier, vol. 136(1), pages 115-130, January.
  3. Hosking, Jonathan R. M., 1996. "Asymptotic distributions of the sample mean, autocovariances, and autocorrelations of long-memory time series," Journal of Econometrics, Elsevier, vol. 73(1), pages 261-284, July.
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