Minimum distance estimation of stationary and non-stationary ARFIMA processes

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Econometrics Journal, vol. 10, Issue 1, pg. 124-148, February 2007
http://hdl.handle.net/10230/983
To cite or link this document: http://hdl.handle.net/10230/983
dc.contributor.author Mayoral, Laura
dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
dc.date.issued 2006-01-01
dc.identifier.citation Econometrics Journal, vol. 10, Issue 1, pg. 124-148, February 2007
dc.identifier.uri http://hdl.handle.net/10230/983
dc.description.abstract A new parametric minimum distance time-domain estimator for ARFIMA processes is introduced in this paper. The proposed estimator minimizes the sum of squared correlations of residuals obtained after filtering a series through ARFIMA parameters. The estimator is easy to compute and is consistent and asymptotically normally distributed for fractionally integrated (FI) processes with an integration order d strictly greater than -0.75. Therefore, it can be applied to both stationary and non-stationary processes. Deterministic components are also allowed in the DGP. Furthermore, as a by-product, the estimation procedure provides an immediate check on the adequacy of the specified model. This is so because the criterion function, when evaluated at the estimated values, coincides with the Box-Pierce goodness of fit statistic. Empirical applications and Monte-Carlo simulations supporting the analytical results and showing the good performance of the estimator in finite samples are also provided.
dc.language.iso eng
dc.relation.ispartofseries Economics and Business Working Papers Series; 959
dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.title Minimum distance estimation of stationary and non-stationary ARFIMA processes
dc.type info:eu-repo/semantics/workingPaper
dc.date.modified 2014-06-03T07:14:17Z
dc.subject.keyword Operations Management
dc.subject.keyword fractional integration
dc.subject.keyword nonstationary long-memory time series
dc.subject.keyword minimum distance estimation
dc.rights.accessRights info:eu-repo/semantics/openAccess


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