 Spectral Analysis and Linear FiltersChapter 6 in Time Series Econometrics, 2016, pp 109-132 from Springer Abstract: Abstract Up to now we have viewed a time series as a time indexed sequence of random variables. The class of ARMA process was seen as an adequate class of models for the analysis of stationary time series. This approach is usually termed as time series analysis in the time domain. Time domain There is, however, an equivalent perspective which views a time series as overlayed waves of different frequencies. This view point is termed in time series analysis as the analysis in the frequency domain. Frequency domain The decomposition of a time series into sinusoids of different frequencies is called the spectral representation. Spectral decomposition The estimation of the importance of the waves at particular frequencies is referred to as spectral or spectrum estimation. Spectrum estimation Priestley (1981) provides an excellent account of these methods. The use of frequency domain methods, in particular spectrum estimation, which originated in the natural sciences was introduced to economics by Granger (1964). Keywords: Spectral Density; Business Cycle; Spectral Window; Spectrum Estimation; Autocovariance Function (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sptchp:978-3-319-32862-1_6 Ordering information: This item can be ordered from DOI: 10.1007/978-3-319-32862-1_6 Access Statistics for this chapter More chapters in Springer Texts in Business and Economics from Springer |
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