An Autoregressive Spectral Density Estimator at Frequency Zero for Nonstationarity Tests

Pierre Perron and Serena Ng ()

Cahiers de recherche from Centre interuniversitaire de recherche en économie quantitative, CIREQ

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.

Keywords: EVALUATION; ECONOMETRICS; TESTS (search for similar items in EconPapers)
JEL-codes: C10 C13 C19 (search for similar items in EconPapers)
Pages: 42 pages
Date: 1996
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Citations: View citations in EconPapers (7)

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Related works:
Journal Article: AN AUTOREGRESSIVE SPECTRAL DENSITY ESTIMATOR AT FREQUENCY ZERO FOR NONSTATIONARITY TESTS (1998)
Working Paper: An Autoregressive Spectral Density Estimator at Frequency Zero for Nonstationarity Tests (1996)
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Persistent link: https://EconPapers.repec.org/RePEc:mtl:montec:9611

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