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Computable General Equilibrium Modelling in Regional Science

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Regional Research Frontiers - Vol. 2

Part of the book series: Advances in Spatial Science ((ADVSPATIAL))

Abstract

Computable General Equilibrium (CGE) modelling has a long and distinguished history in regional science. In the past decade or so, improvements in computation have led to more elaborate and detailed CGE models being developed and used in a range of different policy areas. Against a backdrop of these advances, this chapter seeks to identify and review a number of areas where we see the potential for significant developments in CGE modelling in the years ahead. Specifically, we first consider potential improvements in computation, model specification and methodology, before looking in more detail at three areas where these models are used, or could be used, with a view to identifying avenues where model improvements would be valuable. These three areas are: urban and spatial modelling, model integration with other systems and models, and regional fiscal issues. CGE modelling has a bright future in regional science, but to remain at the forefront of economic research in regional science it must continue to adapt and evolve as, historically it has done, and we hope that the directions identified in this chapter are helpful to the future direction of this field.

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Notes

  1. 1.

    The unconditional mean of the process states that \( E\left(\varepsilon_{t}\right)=0\) and \( E\left(\varepsilon_{t}^{2}\right)=\sigma^{2}\) ln A.

  2. 2.

    We do not mean to imply that there has been no work of this kind (e.g., Nechyba (1996a, b), whose work is discussed above, and Ferguson et al. (2007)) rather that there is considerable potential for further analysis.

  3. 3.

    See e.g.Giesecke and Madden (2006); Hermannsson et al. (2014); Kim et al. (2016).

  4. 4.

    However, Mayeres and Van Regemorter (2008) provide an analysis of this kind for the economies of the EU.

  5. 5.

    Lecca et al. (2015) attempt to do this. However, they identify a major concern here, namely absence of official measures of interregional trade flows.

  6. 6.

    In Scotland this may well happen when the new Fiscal Framework comes up for review in 2020.

  7. 7.

    Giesecke and Madden 2013, suggest a “back of the envelope” approach to enhancing understanding of model results. The approach we have adopted is to use simplified analytical models as appropriate, while using a very flexible modelling framework that allows us to track the source of any model “surprises” (e.g. Lecca et al. 2014).

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Acknowledgements

The authors acknowledge funding from the ESRC under The Constitutional Future of Scotland and the United Kingdom pre and post Referendum Initiative (grant ES/L003325/1) and from ClimateXChange, the Scottish Government-funded Centre of Expertise in Climate Change. The authors are solely responsible for the content of the paper. The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission or Scottish Government. The authors are grateful to the editors for comments on an earlier draft.

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Authors and Affiliations

  1. Fraser of Allander Institute and Department of Economics, Strathclyde Business School, University of Strathclyde, 199 Cathedral Street, Glasgow, G4 0QU, UK

    Grant J. Allan, Peter G. McGregor, Stuart G. McIntyre & J. Kim Swales

  2. European Commission, DG Joint Research Centre, Calle Inca Garcilaso, 3, 41092, Seville, Spain

    Patrizio Lecca

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  1. Grant J. Allan
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  2. Patrizio Lecca
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  3. Peter G. McGregor
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  4. Stuart G. McIntyre
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  5. J. Kim Swales
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Correspondence to Grant J. Allan .

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Editors and Affiliations

  1. Regional Research Institute, West Virginia University, Morgantown, West Virginia, USA

    Randall Jackson

  2. Division of Resource Economics and Management, Faculty Research Associate, Regional Research Institute, West Virginia University, Morgantown, West Virginia, USA

    Peter Schaeffer

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Allan, G.J., Lecca, P., McGregor, P.G., McIntyre, S.G., Kim Swales, J. (2017). Computable General Equilibrium Modelling in Regional Science. In: Jackson, R., Schaeffer, P. (eds) Regional Research Frontiers - Vol. 2. Advances in Spatial Science. Springer, Cham. https://doi.org/10.1007/978-3-319-50590-9_4

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