On parameters estimation of the Seasonal FISSAR Model

Papa Ousmane Cissé (), Dominique Guégan () and Abdou Ka Diongue
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Papa Ousmane Cissé: Centre d'Economie de la Sorbonne - Université Paris 1 Panthéon-Sorbonne, LERSTAD - Université Gaston Berger (Sénégal), LMM, IRA - Université Le Mans, https://centredeconomiesorbonne.univ-paris1.fr
Dominique Guégan: Université Paris 1 Panthéon-Sorbonne, Centre d'Economie de la Sorbonne, LabEx ReFi and Ca' Foscari University of Venezia, IPAG Business school, https://cv.archives-ouvertes.fr/dominique-guegan

Documents de travail du Centre d'Economie de la Sorbonne from Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne

Abstract: In this paper, we discuss the methods of estimating the parameters of the Seasonal FISSAR (Fractionally Integrated Separable Spatial Autoregressive with seasonality) model. First we implement the regression method based on the log-periodogram and the classical Whittle method for estimating memory parameters. To estimate the model's parameters simultaneously - innovation parameters and memory parameters- the maximum likelihood method, and the Whittle method based on the MCMC simulation are considered. We are investigated the consistency and the asymptotic normality of the estimators by simulation

Keywords: Seasonal FISSAR; long memory; regression method; Whittle method; MLE method (search for similar items in EconPapers)
JEL-codes: C21 C51 C52 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2018-07
New Economics Papers: this item is included in nep-ecm
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ftp://mse.univ-paris1.fr/pub/mse/CES2018/18018.pdf (application/pdf)

Related works:
Working Paper: On the parameters estimation of the Seasonal FISSAR Model (2018)
Working Paper: On the parameters estimation of the Seasonal FISSAR Model (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:mse:cesdoc:18018

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