| dc.contributor.author | Arteche González, Jesús María  | |
| dc.date.accessioned | 2020-12-14T15:36:41Z | |
| dc.date.available | 2020-12-14T15:36:41Z | |
| dc.date.issued | 2020-10 | |
| dc.identifier.uri | http://hdl.handle.net/10810/48980 | |
| dc.description.abstract | Bootstrap techniques in the frequency domain have been proved to be effective instruments
to approximate the distribution of many statistics of weakly dependent (short
memory) series. However their validity with long memory has not been analysed yet.
This paper proposes a Frequency Domain Local Bootstrap (FDLB) based on resampling
a locally studentised version of the periodogram in a neighbourhood of the frequency of
interest. A bound of the Mallows distance between the distributions of the original and
bootstrap periodograms is offered for stationary and non-stationary long memory series.
This result is in turn used to justify the use of FDLB for some statistics such as the
average periodogram or the Local Whittle (LW) estimator. Finally, the finite sample
behaviour of the FDLB in the LW estimator is analysed in a Monte Carlo, comparing
its performance with rival alternatives. | es_ES |
| dc.description.sponsorship | Research supported by the Spanish Ministry of Science and Innovation and ERDF grants ECO2016-76884-P, ID2019-105183GB-I00 and UPV/EHU Econometrics Research Group (Basque Government grantIT1359-19 | es_ES |
| dc.language.iso | eng | es_ES |
| dc.relation | info:eu-repo/grantAgreement/MCIU/PID2019-105183GB-I00 | |
| dc.relation | info:eu-repo/grantAgreement/MINECO/ECO2016-76884-P | |
| dc.relation.ispartofseries | Biltoki; | |
| dc.rights | info:eu-repo/semantics/openAccess | es_ES |
| dc.title | Frequency Domain Local Bootstrap in long memory time series | es_ES |
| dc.type | info:eu-repo/semantics/workingPaper | es_ES |
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