Pré-Publication, Document De Travail Année : 2017

Estimating long memory in panel random-coefficient AR(1) data

Résumé

It is well-known that random-coefficient AR(1) process can have long memory depending on the index β of the tail distribution function of the random coefficient, if it is a regularly varying function at unity. We discuss estimation of β from panel data comprising N random-coefficient AR(1) series, each of length T. The estimator of β is constructed as a version of the tail index estimator of Goldie and Smith (1987) applied to sample lag 1 autocorrelations of individual time series. Its asymptotic normality is derived under certain conditions on N, T and some parameters of our statistical model. Based on this result, we construct a statistical procedure to test if the panel random-coefficient AR(1) data exhibit long memory. A simulation study illustrates finite-sample performance of the introduced estimator and testing procedure.

Fichier principal
Vignette du fichier
hal2019.pdf (595.95 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence
Loading...

Dates et versions

hal-01622201 , version 1 (25-10-2017)
hal-01622201 , version 2 (29-10-2018)
hal-01622201 , version 3 (13-09-2019)

Licence

Identifiants

Citer

Remigijus Leipus, Anne Philippe, Vytaute Pilipauskaite, Donatas Surgailis. Estimating long memory in panel random-coefficient AR(1) data. 2017. ⟨hal-01622201v3⟩
202 Consultations
665 Téléchargements

Altmetric

Partager

  • More