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An Autoregressive Spectral Density Estimator at Frequency Zero for Nonstationarity Tests

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  • Perron, P.
  • Ng, S.

Abstract

Many unit root and cointegration tests require an estimate of the spectral density function at frequency zero at some process. Kernel estimators based on weighted sums of autocovariances constructed using estimated residuals from an AR(1) regression are commonly used. However, it is known that with substantially correlated errors, the OLS estimate of the AR(1) parameter is severely biased. in this paper, we first show that this least squares bias induces a significant increase in the bias and mean-squared error of kernel-based estimators.

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File URL: http://hdl.handle.net/1866/2112
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Bibliographic Info

Paper provided by Universite de Montreal, Departement de sciences economiques in its series Cahiers de recherche with number 9611.

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Length: 42 pages
Date of creation: 1996
Date of revision:
Handle: RePEc:mtl:montde:9611

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