Spectral estimation of the multivariate impulse response

Tunnicliffe-Wilson, Granville (2017) Spectral estimation of the multivariate impulse response. Journal of Time Series Analysis, 38 (2). pp. 381-391. ISSN 0143-9782

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One of the applications of cross-spectral estimation of stationary time series, developed some five decades ago, is the estimation of the lagged response of an output series causally dependent on an input series, in the absence of feedback from the output to the input. The direct application of cross-spectral analysis for this purpose is no longer appropriate in the presence of feedback or more general inter-dependence of the series. In that case, vector autoregressive modeling has been used, particularly in the econometric context, to estimate the response of one series to a shock or impulse in the innovations of another series. To achieve the same end, cross-spectral analysis requires the application of spectral factorization, and in this article, we demonstrate this methodology, explaining how it may be used to construct impulse response function estimates and their statistical properties. Our presentation includes an information criterion for choosing the smoothing bandwidth to be used for cross-spectral estimation.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Time Series Analysis
Additional Information:
This is the peer reviewed version of the following article: Tunnicliffe Wilson, G. (2017) Spectral Estimation of the Multivariate Impulse Response. J. Time Ser. Anal., 38: 381–391. doi: 10.1111/jtsa.12226 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/jtsa.12226/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
Uncontrolled Keywords:
?? cross-spectral analysisspectral factorizationimpulse response estimationinformation criterionbandwidthchoiceapplied mathematicsstatistics and probabilitystatistics, probability and uncertainty ??
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Deposited On:
12 Jan 2017 09:34
Last Modified:
15 Jul 2024 16:42