Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/283163 
Erscheinungsjahr: 
2023
Schriftenreihe/Nr.: 
Hannover Economic Papers (HEP) No. 712
Verlag: 
Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, Hannover
Zusammenfassung: 
In this paper, we introduce the concept of fractional integration for spatial autoregressive models. We show that the range of the dependence can be spatially extended or diminished by introducing a further fractional integration parameter to spatial autoregressive moving average models (SARMA). This new model is called the spatial autoregressive fractionally integrated moving average model, briefly sp-ARFIMA. We show the relation to time-series ARFIMA models and also to (higher-order) spatial autoregressive models. Moreover, an estimation procedure based on the maximum-likelihood principle is introduced and analysed in a series of simulation studies. Eventually, the use of the model is illustrated by an empirical example of atmospheric fine particles, so-called aerosol optical thickness, which is important in weather, climate and environmental science.
Schlagwörter: 
Spatial ARFIMA
spatial fractional integration
long-range dependence
aerosol optical depth
JEL: 
C22
C23
Dokumentart: 
Working Paper

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