Exploring Brexit with dynamic spatial panel models: some possible outcomes for employment across the EU regions

Bernard Fingleton ()

MPRA Paper from University Library of Munich, Germany

Abstract: Starting with a reduced form derived from standard urban economics theory, this paper estimates the possible job-shortfall across UK and EU regions using a time-space dynamic panel data model with a Spatial Moving Average Random Effects (SMA-RE) structure of the disturbances. The paper provides a logical rational for the presence of spatial and temporal dependencies involving the endogenous variable, leading to estimates based on a dynamic spatial Generalized Moments (GM) estimator proposed by Baltagi, Fingleton and Pirotte (2018). Given state-of-the art interregional trade estimates, the simulations are based on a linear predictor which utilizes different regional interdependency matrices according to assumptions about interregional trade post-Brexit.

Keywords: Brexit; Interregional trade; Urban economics theory; Panel data; Spatial lag; Spatio-temporal lag; Dynamic; Spatial moving average; Prediction; Simulation. (search for similar items in EconPapers)
JEL-codes: C23 C33 C53 E27 F10 J21 R12 (search for similar items in EconPapers)
Date: 2018-05-06
New Economics Papers: this item is included in nep-geo, nep-int, nep-lma, nep-mac, nep-opm, nep-ore and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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https://mpra.ub.uni-muenchen.de/86553/1/MPRA_paper_86553.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/87203/8/MPRA_paper_87203.pdf revised version (application/pdf)

Related works:
Journal Article: Exploring Brexit with dynamic spatial panel models: some possible outcomes for employment across the EU regions (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:86553

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