Spectral Regression For Cointegrated Time Series With Long‐Memory Innovations

D. Marinucci

Journal of Time Series Analysis, 2000, vol. 21, issue 6, 685-705

Abstract: Spectral regression is considered for cointegrated time series with long‐memory innovations. The estimates we advocate are shown to be consistent when cointegrating relationships among stationary variables are investigated, while ordinary least squares are inconsistent due to correlation between the regressors and the cointegrating residuals; in the presence of unit roots, these estimates share the same asymptotic distribution as ordinary least squares. As a corollary of the main result, we provide a functional central limit theorem for quadratic forms in non‐stationary fractionally integrated processes.

Date: 2000
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jtsera:v:21:y:2000:i:6:p:685-705

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