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Time-varying spectral analysis: theory and applications

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  • D. M. Nachane

    (Indira Gandhi Institute of Development Research)

Abstract

Non-stationary time series are a frequently observed phenomenon in several applied fields, particularly physics, engineering and economics. The conventional way of analysing such series has been via stationarity inducing filters. This can interfere with the intrinsic features of the series and induce distortions in the spectrum. To avert this possibility, it might be a better alternative to proceed directly with the series via the so-called time-varying spectrum. This article outlines the circumstances under which such an approach is possible, drawing attention to the practical applicability of these methods. Several methods are discussed and their relative advantages and drawbacks delineated.

Suggested Citation

  • D. M. Nachane, 2018. "Time-varying spectral analysis: theory and applications," Indian Economic Review, Springer, vol. 53(1), pages 3-27, December.
    • Handle: RePEc:spr:inecre:v:53:y:2018:i:1:d:10.1007_s41775-018-0030-2
    DOI: 10.1007/s41775-018-0030-2
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    More about this item

    Keywords

    Non-stationarity; Mixing conditions; Oscillatory processes; Evolutionary spectrum; ANOVA; Decoupling;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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