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Spatial and Spatio-Temporal Error Correction Networks and Common Correlated Effects

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  • Arnab Bhattacharjee
  • Sean Holly
  • Jan Ditzen

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.

Suggested Citation

  • Arnab Bhattacharjee & Sean Holly & Jan Ditzen, 2021. "Spatial and Spatio-Temporal Error Correction Networks and Common Correlated Effects," National Institute of Economic and Social Research (NIESR) Discussion Papers 526, National Institute of Economic and Social Research.
  • Handle: RePEc:nsr:niesrd:526
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    References listed on IDEAS

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    More about this item

    Keywords

    Spatio-temporal dynamics; Error Correction Models; Weak and strong cross sectional dependence;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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