Whittle Pseudo-Maximum Likelihood Estimation for Nonstationary Time Series - (Now Published in Journal of the American Statistical Association, 95, (2000), Pp.1229-1243.)

35 Pages Posted: 21 Jul 2008

See all articles by Carlos Velasco

Carlos Velasco

Universidad Carlos III de Madrid - Department of Economics

Date Written: May 2000

Abstract

Whittle pseudo-maximum likelihood estimates of parameters for stationary time series have been found to be consistent and asumptotically normal in the presence of long-range dependence. Generalizing the definition of the memory parameter d, we extend these results to include possibly nonstationary (0.5 = d < 1) or antipersistent (-0.5 < d < 0) observations. Using adequate data tapers we can apply this estimation technique to any degree of nonstationarity d = 0.5 without prior knowledge of the memory of the series. We analyse the performance of the estimates on simulated and real data.

JEL Classification: C13, C14

Suggested Citation

Velasco, Carlos, Whittle Pseudo-Maximum Likelihood Estimation for Nonstationary Time Series - (Now Published in Journal of the American Statistical Association, 95, (2000), Pp.1229-1243.) (May 2000). LSE STICERD Research Paper No. EM391. Available at SSRN: https://ssrn.com/abstract=1162584

Carlos Velasco

Universidad Carlos III de Madrid - Department of Economics ( email )

Calle Madrid 126
Getafe, 28903
Spain
+34-91 6249646 (Phone)
+34-91 6249875 (Fax)

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