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Spatial and Spatio-temporal Engle-Granger representations, Networks and Common Correlated Effects

Arnab Bhattacharjee (), Jan Ditzen and Sean Holly ()

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

Abstract: 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.

Keywords: Spatio-temporal dynamics; Error Correction Models; Weak and strong cross sectional dependence (search for similar items in EconPapers)
JEL-codes: C21 C22 C23 R3 (search for similar items in EconPapers)
Date: 2020-08-03
New Economics Papers: this item is included in nep-ecm, nep-net, nep-ore and nep-ure
Note: sh247
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