Spatial and Spatio-Temporal Granger Representation, Networks and Common Correlated Effects

Arnab Bhattacharjee, Jan Ditzen, Sean Holly

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review


We provide a way to represent spatial and temporal equilibria in terms of error correction models in a panel setting. This requires potentially two different processes for spatial or network dynamics, both of which can be expressed in terms of spatial weights matrices. The first captures strong cross-sectional dependence, so that a spatial difference, suitably defined, is weakly cross-section dependent (granular) but can be nonstationary. The second is a conventional weights matrix that captures short-run spatio-temporal dynamics as stationary and granular processes. In large samples, cross-section averages serve the first purpose and we propose the mean group, common correlated effects estimator together with multiple testing of cross-correlations to provide the short-run spatial weights. We apply this model to the 324 local authorities of England, and show that our approach is useful for modelling weak and strong cross-section dependence, together with partial adjustments to two long-run equilibrium relationships and short-run spatio-temporal dynamics. This exercise provides new insights on the (spatial) long run relationship between house prices and income in the UK.
Original languageEnglish
Title of host publicationEssays in Honor of M. Hashem Pesaran
Subtitle of host publicationPanel Modeling, Micro Applications, and Econometric Methodology
EditorsAlexander Chudik, Cheng Hsiao, Allan Timmermann
PublisherEmerald Publishing Limited
ISBN (Print) 9781802620665
Publication statusPublished - 18 Jan 2022

Publication series

NameAdvances in Econometrics


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