1. Narrow-band analysis of nonstationary processes
- Author
-
Peter M. Robinson and Domenico Marinucci
- Subjects
Statistics and Probability ,Analysis of covariance ,long range dependence ,Cointegration ,Primary 62M10 ,secondary 60G18 ,62M15. [Nonstationary processes ,least squares estimation ,narrow-band estimation ,cointegration analysis. AMS 2000 subject classifications] ,Frequency band ,Variance (accounting) ,Stationary sequence ,cointegration analysis ,Space (mathematics) ,Spectral line ,Settore MAT/06 - Probabilita' e Statistica Matematica ,Nonstationary processes, long-range dependence, least squares estimation, narrow-band estimation, cointegration analysis ,62M15 ,Sample size determination ,60G18 ,62M10 ,jel:C1 ,HA Statistics ,Statistical physics ,Statistics, Probability and Uncertainty ,Nonstationary processes ,Mathematics - Abstract
The behaviour of averaged periodograms and cross-periodograms of a broad class of nonstationary processes is studied. The processes include nonstationary ones that are fractional of any order, as well as asymptotically stationary fractional ones. The cross-periodogram can involve two nonstationary processes of possibly different orders, or a nonstationary and an asymptotically stationary one. The averaging takes place either over the whole frequency band, or over one that degenerates slowly to zero frequency as sample size increases. In some cases it is found to make no asymptotic difference, and in particular we indicate how the behaviour of the mean and variance changes across the two-dimensional space of integration orders. The results employ only local-to-zero assumptions on the spectra of the underlying weakly stationary sequences. It is shown how the results can be applied in fractional cointegration with unknown integration orders.
- Published
- 2001