Clustering Space-Time Series: A Flexible STAR Approach
Edoardo Otranto () and
Working Paper CRENoS from Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia
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)
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-geo and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:cns:cnscwp:201707
Access Statistics for this paper
More papers in Working Paper CRENoS from Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia Contact information at EDIRC.
Bibliographic data for series maintained by CRENoS ().