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S‐Estimation in the Linear Regression Model with Long‐memory Error Terms Under Trend

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  • Philipp Sibbertsen

Abstract

The asymptotic distribution of S‐estimators in the linear regression model with long‐memory error terms is obtained under mild regularity conditions to the regressors which are sufficiently weak to cover, for example, polynomial trends and i.i.d. carriers. It turns out that S‐estimators are asymptotically normal in the case of deterministic regressors with a variance–covariance structure similar to the structure in the i.i.d. case. Also, the rate of convergence for S‐estimators is the same as for the least‐squares estimator (LSE) and the best linear unbiased estimator (BLUE).

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  • Philipp Sibbertsen, 2001. "S‐Estimation in the Linear Regression Model with Long‐memory Error Terms Under Trend," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(3), pages 353-363, May.
    • Handle: RePEc:bla:jtsera:v:22:y:2001:i:3:p:353-363
    DOI: 10.1111/1467-9892.00228
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