Spectral density and spectral distribution inference for long memory time series via fixed-b asymptotics

Tucker McElroy () and Dimitris N. Politis

Journal of Econometrics, 2014, vol. 182, issue 1, 211-225

Abstract: This paper studies taper-based estimates of the spectral density utilizing a fixed bandwidth ratio asymptotic framework, and makes several theoretical contributions: (i) we treat multiple frequencies jointly, (ii) we allow for long-range dependence or anti-persistence at differing frequencies, (iii) we allow for tapers that are only piecewise smooth or discontinuous, including flat-top and truncation tapers, (iv) we study higher-order accuracy through the limit distribution’s Laplace Transform, (v) we develop a taper-based estimation theory for the spectral distribution, and show how confidence bands can be constructed. Simulation results produce quantiles and document the finite-sample size properties of the estimators, and a few empirical applications demonstrate the utility of the new methods.

Keywords: Cyclical long memory; Kernel spectral estimator; Long range dependence; Spectral confidence bands (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (6)

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Related works:
Working Paper: Spectral Density and Spectral Distribution Inference for Long Memory Time Series via Fixed-b Asymptotics (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:182:y:2014:i:1:p:211-225

DOI: 10.1016/j.jeconom.2014.04.019

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