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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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    File URL: https://mpra.ub.uni-muenchen.de/87203/8/MPRA_paper_87203.pdf
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    References listed on IDEAS

    as
    1. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    2. Justin Doran & Bernard Fingleton, 2014. "Economic shocks and growth: Spatio-temporal perspectives on Europe's economies in a time of crisis," Papers in Regional Science, Wiley Blackwell, vol. 93, pages 137-165, November.
    3. Bernard Fingleton, 2008. "A Generalized Method of Moments Estimator for a Spatial Panel Model with an Endogenous Spatial Lag and Spatial Moving Average Errors," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(1), pages 27-44.
    4. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2014. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 112-138, February.
    5. Nicolas DEBARSY (CERPE De Namur) & Cem ERTUR & James P. LeSAGE, 2010. "Interpreting Dynamic Space-Time Panel Data Models," LEO Working Papers / DR LEO 800, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    6. Parent, Olivier & LeSage, James P., 2011. "A space-time filter for panel data models containing random effects," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 475-490, January.
    7. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2018. "A Time-Space Dynamic Panel Data Model with Spatial Moving Average Errors," MPRA Paper 86371, University Library of Munich, Germany.
    8. repec:spr:portec:v:1:y:2002:i:2:d:10.1007_s10258-002-0009-9 is not listed on IDEAS
    9. Wolfang Polasek & Carlos Llano & Richard Sellner, 2010. "Bayesian Methods for Completing Data in Spatial Models," Review of Economic Analysis, Rimini Centre for Economic Analysis, vol. 2(2), pages 194-214, June.
    10. Stephen Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers CWP09/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Pesaran, M. Hashem, 2015. "Time Series and Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780198759980.
    12. Salima Bouayad-Agha & Lionel VĂ©drine, 2010. "Estimation Strategies for a Spatial Dynamic Panel using GMM. A New Approach to the Convergence Issue of European Regions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(2), pages 205-227.
    13. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
    14. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
    15. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
    16. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

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

    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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