Error Bounds and Asymptotic Expansions for Toeplitz Product Functionals of Unbounded Spectra
AbstractThis paper establishes error orders for integral limit approximations to traces of powers to the pth order) of products of Toeplitz matrices. Such products arise frequently in the analysis of stationary time series and in the development of asymptotic expansions. The elements of the matrices are Fourier transforms of functions which we allow to be bounded, unbounded, or even to vanish on [-pi,pi], thereby including important cases such as the spectral functions of fractional processes. Error rates are also given in the case in which the matrix product involves inverse matrices. The rates are sharp up to an arbitrarily small epsilon > 0. The results improve on the o(1) rates obtained in earlier work for analogous products. For the p = 1 case, an explicit second order asymptotic expansion is found for a quadratic functional of the autocovariance sequences of stationary long memory time series. The order of magnitude of the second term in this expansion is shown to depend on the long memory parameters. It is demonstrated that the pole in the first order approximation is removed by the second order term, which provides a substantially improved approximation to the original functional.
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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 1374.
Length: 22 pages
Date of creation: May 2002
Date of revision:
Publication status: Published in Journal of Time Series Analysis (2004), 25(5): 733-753
Note: CFP 1141.
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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA
Other versions of this item:
- Offer Lieberman & Peter C. B. Phillips, 2004. "Error bounds and asymptotic expansions for toeplitz product functionals of unbounded spectra," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 733-753, 09.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
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- Ioannis Kasparis & Peter C.B. Phillips & Tassos Magdalinos, 2012.
"Non-linearity Induced Weak Instrumentation,"
Cowles Foundation Discussion Papers
1872, Cowles Foundation for Research in Economics, Yale University.
- Ginovyan, Mamikon S. & Sahakyan, Artur A., 2013. "On the trace approximations of products of Toeplitz matrices," Statistics & Probability Letters, Elsevier, vol. 83(3), pages 753-760.
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