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

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  • Fingleton, Bernard

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.

Suggested Citation

  • Fingleton, Bernard, 2018. "Exploring Brexit with dynamic spatial panel models : some possible outcomes for employment across the EU regions," MPRA Paper 86553, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:86553
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    References listed on IDEAS

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    Cited by:

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    2. Roberta Capello & Andrea Caragliu, 2021. "Merging macroeconomic and territorial determinants of regional growth: the MASST4 model," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 66(1), pages 19-56, February.
    3. Bernard Fingleton, 2022. "Modifying the linear two-step Windmeijer correction for the presence of spatial error dependence," Journal of Spatial Econometrics, Springer, vol. 3(1), pages 1-18, December.

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    More about this item

    Keywords

    Brexit; Interregional trade; Urban economics theory; Panel data; Spatial lag; Spatio-temporal lag; Dynamic; Spatial moving average; Prediction; Simulation.;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • F10 - International Economics - - Trade - - - General
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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