Multiple Local Whittle Estimation in Stationary Systems
By Peter M. Robinson. 2008
101 citations recorded by the source corpus.
Moving from univariate to bivariate jointly dependent long memory time series introduces a phase parameter (γ), at the frequency of principal interest, zero; for short memory series γ = 0 automatically. The latter case has also been stressed under long memory, along with the "fractional differencing" case ( ) / 2; 2 1 γ = δ − δ π where 1 2 δ , δ are the memory parameters of the two series. We develop time domain conditions under which these are and are not relevant, and relate the consequent properties of cross-autocovariances to ones of the (possibly bilateral) moving average representation which, with martingale difference innovations of arbitrary dimension, is used in asymptotic theory for local Whittle parameter estimates depending on a single smoothing number. Incorporating also a regression parameter (β) which, when non-zero, indicates cointegration, the consistency proof of these implicitly-defined estimates is nonstandard due to the β estimate converging faster than the others. We also establish joint asymptotic normality of the estimates, and indicate how this outcome can apply in statistical inference on several questions of interest. Issues of implementation are discussed, along with implications of knowing β and of correct or incorrect specification of γ , and possible extensions to higher-dimensional systems and nonstationary series.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/7f7a4effdcb3056bd630cc9864b59acd2b2fc5fe
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In Economics and Econometrics
- Katsumi Shimotsu
- Morten Ørregaard Nielsen
- Peter C. B. Phillips
- L. Gil‐Alana
- Guiglielmo Maria Caporale
- Hiroyuki Kasahara
- Ladislav Kristoufek
- Per Frederiksen
In Finance
- Katsumi Shimotsu
- Morten Ørregaard Nielsen
- Peter C. B. Phillips
- L. Gil‐Alana
- Guiglielmo Maria Caporale
- Per Frederiksen
- Ladislav Kristoufek
- Peter M. Robinson
Citations in the corpus
- Fully modified narrow‐band least squares estimation of weak fractional cointegration (2011, unknown): “The connection between the representations (4) and (6) (or Assumption 1) and the lag weights in the linear process (Assumption 3) is explored in Theorems 1 and 2 of Robinson (2008).”
- Exact local Whittle estimation of fractionally cointegrated systems (2012, methodology): “ Robinson (2008) . In the two-step estimation, quasi-Newton updating was repeated until”