Mean and Autocovariance Function Estimation Near the Boundary of Stationarity
AbstractWe analyze the applicability of standard normal asymptotic theory for linear process models near the boundary of stationarity. The concept of stationarity is refined, allowing for sample size dependence in the array and paying special attention to the rate at which the boundary unit root case is approached using a localizing coefficient around unity. The primary focus of the present paper is on estimation of the 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. An asymptotic result on the estimation of the localizing coefficient is also presented. To assist in the development of the limit theory in the present case, a suitable asymptotic theory for the behavior of quadratic forms in the vicinity of the boundary of stationarity is provided.
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Bibliographic InfoPaper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1690.
Length: 34 pages
Date of creation: Jan 2009
Date of revision:
Publication status: Published in Journal of Econometrics (August 2012), 169(2): 166-178
Note: CFP 1363
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Postal: Yale University, Box 208281, New Haven, CT 06520-8281 USA
Phone: (203) 432-3702
Fax: (203) 432-6167
Web page: http://cowles.econ.yale.edu/
More information through EDIRC
Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA
Other versions of this item:
- Giraitis, Liudas & Phillips, Peter C.B., 2012. "Mean and autocovariance function estimation near the boundary of stationarity," Journal of Econometrics, Elsevier, vol. 169(2), pages 166-178.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Liudas Giraitis & Peter C.B. Phillips, 2004.
"Uniform Limit Theory for Stationary Autoregression,"
Cowles Foundation Discussion Papers
1475, Cowles Foundation for Research in Economics, Yale University.
- 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.
- L Giraitis & P C B Phillips, . "Uniform limit theory for stationary autoregression," Discussion Papers 05/23, Department of Economics, University of York.
- 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.
- Peter C.B. Phillips & Tassos Magdalinos, 2004.
"Limit Theory for Moderate Deviations from a Unit Root,"
Cowles Foundation Discussion Papers
1471, Cowles Foundation for Research in Economics, Yale University.
- 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.
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