The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

Spectral Analysis

  • Timothy J. Vogelsang
Reference work entry
DOI: https://doi.org/10.1057/978-1-349-95189-5_1275

Abstract

Spectral analysis is a statistical approach for analysing stationary time series data in which the series is decomposed into cyclical or periodic components indexed by the frequency of repetition. Spectral analysis falls within the frequency domain approach to time series analysis. The spectral density function plays the central role and it summarizes the contributions of cyclical components to the variation of a stationary time series. The spectral density at frequency zero is particularly important because of its direct link to the variance of a time series sample average, that is, the long-run variance.

Keywords

Alias effect ARMA models Autocovariances Autoregressive spectral density estimator Bandwidth Bartlett kernel Bias Cross-spectral densities Cycles Econometric methodology Fixed-b asymptotics Frequency Frequency domain Generalized method of moments Granger causality Heteroskedasticity and autocorrelation covariance matrix estimation Kernel estimators Long-run variance Mean square error Nonparametric estimators Probability Quadratic spectral kernel Spectral analysis Spectral density Spectral density matrix Spectral representation theorem Time domain Time series analysis Truncation lag Variance White noise 

JEL classifications

C10 
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Copyright information

© Macmillan Publishers Ltd. 2018

Authors and Affiliations

  • Timothy J. Vogelsang
    • 1
  1. 1.