Note on a new Seasonal Fractionally Integrated Separable Spatial Autoregressive Model

Papa Ousmane Cissé (), Abdou Ka Diongue and Dominique Guegan ()
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Papa Ousmane Cissé: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, LERSTAD - laboratoire d'Etudes et de recherches en Statistiques et Développement - UGB - Université Gaston Berger de Saint-Louis Sénégal
Dominique Guegan: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique

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Abstract: In this paper, we introduce a new model called Fractionally Integrated Separable Spatial Autoregressive processes with Seasonality and denoted Seasonal FISSAR for two-dimensional spatial data. We focus on the class of separable spatial models whose correlation structure can be expressed as a product of correlations. This new modelling allows taking into account the seasonality patterns observed in spatial data. We investigate the properties of this new model providing stationary conditions, some explicit expressions form of the autocovariance function and the spectral density function. We establish the asymptotic behaviour of the spectral density function near the seasonal frequencies and perform some simulations to illustrate the behaviour of the model.

Keywords: seasonality; spatial short memory; seasonal long memory; two-dimensional data; separable process; spatial stationary process; spatial autocovariance (search for similar items in EconPapers)
Date: 2016-02
New Economics Papers: this item is included in nep-ets and nep-ure
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01278126
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Citations: View citations in EconPapers (4)

Published in 2016

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Related works:
Working Paper: Note on a new Seasonal Fractionally Integrated Separable Spatial Autoregressive Model (2016)
Working Paper: Note on a new Seasonal Fractionally Integrated Separable Spatial Autoregressive Model (2016)
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