Remark on the asymptotic distribution of the OLS estimator in a simple Gaussian unit-root autoregression
This paper considers the asymptotic distribution of the OLS estimator in a simple, Gaussian unit-root AR(1) with fixed, non-zero startup. All asymptotic possibilities are considered. The approach is new, relatively simple, and relies on observing and determining the asymptotic/limiting behavior of the underlying finite sample distribution. It does not rely on inversion of joint moment generating or characteristic functions to derive limiting distributions. The paper introduces small-sigma/parameter-based asymptotic theory and re-examines large-sample asymptotic theory. In addition, combinations of these asymptotic approaches are considered explicitly. The analysis provides a set of very interesting and sometimes surprising results.
Year of publication: |
2006
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Authors: | Vougas, Dimitrios V. |
Published in: |
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 76.2006, 1, p. 27-34
|
Publisher: |
Elsevier |
Keywords: | AR(1) OLS estimator Unit-root process Parameter-based asymptotic theory Small-sigma asymptotic theory Large-sample asymptotic theory |
Saved in:
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