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Local inference for locally stationary time series based on the empirical spectral measure

[journal article]

Dahlhaus, Rainer

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Please use the following Persistent Identifier (PID) to cite this document:http://nbn-resolving.de/urn:nbn:de:0168-ssoar-233498

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Abstract The time varying empirical spectral measure plays a major role in the treatment of inference problems for locally stationary processes. The properties of the empirical spectral measure and related statistics are studied - both when its index function is fixed or dependent on the sample size. In particular we prove a general central limit theorem. Several applications and examples are given including semiparametric Whittle estimation, local least squares estimation and spectral density estimation.
Classification Natural Science and Engineering, Applied Sciences
Free Keywords C220; C140; Empirical spectral measure; Asymptotic normality; Locally stationary processes; Nonstationary time series
Document language English
Publication Year 2009
Page/Pages p. 101-112
Journal Journal of Econometrics, 151 (2009) 2
DOI http://dx.doi.org/10.1016/j.jeconom.2009.03.002
Status Postprint; reviewed
Licence PEER Licence Agreement (applicable only to documents from PEER project)
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