Please use this identifier to cite or link to this item: http://hdl.handle.net/10016/4434

 Google™ Scholar. Others By: Velasco, Carlos - Robinson, Peter M.
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 Title: Whittle pseudo-maximum likelihood estimation for nonstationary time series Author(s): Velasco, Carlos [cavelas]Robinson, Peter M. Publisher: American Statistical Association Issued date: Dec-2000 Citation: Journal of the American Statistical Association. 2000, vol. 95, nº 452, p. 1229-1243 URI: http://hdl.handle.net/10016/4434 ISSN: 0162-1459 Abstract: Whittle pseudo-maximum likelihood estimates of parameters for stationary time series have been found to be consistent and asymptotically normal in the presence of long-range dependence. Generalizing the definition of the memory parameter d, we extend these results to include possibly nonstationary (.5 $\leq d <$ 1) or antipersistent (-.5 $< d <$ 0) observations. Using adequate data tapers, we can apply this estimation technique to any degree of nonstationarity d ≥ .5 without a priori knowledge of the memory of the series. We analyze the performance of the estimates on simulated and real data. Review: PeerReviewed Publisher version: http://www.jstor.org/stable/2669763 Keywords: Frequency domain estimationLong-range dependenceNonstationary fractional modelsNonstationary long memory time seriesTapering Rights: © American Statistical Association Appears in Collections: Economists OnlineDE - Artículos de Revistas