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Title

Minimum distance estimation of stationary and non-stationary ARFIMA processes

AuthorsMayoral, Laura
Issue Date2007
PublisherWiley-Blackwell
CitationEconometrics Journal 10(1): 124-148 (2007)
AbstractA 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. © Royal Economic Society 2007.
URIhttp://hdl.handle.net/10261/58070
DOI10.1111/j.1368-423X.2007.00202.x
Identifiersdoi: 10.1111/j.1368-423X.2007.00202.x
issn: 1368-4221
e-issn: 1368-423X
Appears in Collections:(IAE) Artículos
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