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Clustering Space-Time Series: A Flexible STAR Approach

Edoardo Otranto () and M. Mucciardi

Working Paper CRENoS from Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia

Abstract: The STAR model is widely used to represent the dynamics of a certain variable recorded at several locations at the same time. Its advantages are often discussed in terms of parsimony with respect to space-time VAR structures because it considers a single coefficient for each time and spatial lag. This hypothesis can be very strong; we add a certain degree of flexibility to the STAR model, providing the possibility for coefficients to vary in groups of locations. The new class of models is compared to the classical STAR and the space-time VAR by simulations and an application.

Keywords: clustering; forecasting; space–time models; spatial weight matrix (search for similar items in EconPapers)
Date: 2017
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-geo and nep-ure
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https://crenos.unica.it/crenos/node/7082
https://crenos.unica.it/crenos/sites/default/files/wp-17-07.pdf (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:cns:cnscwp:201707

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