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Geographical Macro and Regional Impact Modeling

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Regional Research Frontiers - Vol. 2

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

Abstract

The geographic macro and regional modeling (GMR) framework has been established and continuously improved to better support regional development policy decisions by ex-ante and ex-post scenario analyses. Knowledge-based development oriented policy instruments (R&D subsidies, promotion of knowledge networks, human capital development, entrepreneurship policies or instruments promoting more intensive public-private collaborations in innovation) are in the focus of the GMR-approach. An important feature of this approach is that it incorporates geographic effects (e.g., agglomeration, interregional trade, migration) while both macro (national) and regional impacts of policies are simulated. In this book chapter I provide a concise description of the GMR policy impact analysis method while it will also be related to current theoretical investigations in regional economics as well as to alternative economic impact modeling practices.

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Notes

  1. 1.

    The HERMIN model (ESRI 2002), the ECOMOD model (Bayar 2007) or the QUEST III model (Ratto et al. 2009) are good examples of macroeconomic modeling while the REMI model (Treyz et al. 1992) is a well-known representative of regional modeling.

  2. 2.

    An additional reason for place-based (or region-specific) policies is politics, particularly in an ethnically and/or culturally diverse economy. The EU meets this criterion. It is also the reason why Canada has very specific region-based objectives, as does Switzerland.

  3. 3.

    SCGE models extend the more conventional CGE (Computable General Equilibrium) approach with geographic effects such as agglomeration, interregional migration and transport costs. An SCGE model is formulated as a set of (sub-national) regions where regions are not independent but connected by linkages like transportation and migration. The short run equilibrium of the model is reached when supply and demand equals in each market in each of the regions. However this does not necessarily mean that this equilibrium is stable because differences in factor prices might induce interregional migration. Equilibrium becomes stable in the long run when no motivation for further factor migration is present.

  4. 4.

    DSGE stands for Dynamic Stochastic General Equilibrium modeling. These models are dynamic because they explicitly take into account intertemporal decisions of economic actors; they are stochastic as the structural relationship and variables of the model can be hit by different shocks driving the economy away from the equilibrium path; they are general equilibrium as they assume market clearing (even if markets are not perfect).

References

  • Baldwin R, Martin P (2004) Agglomeration and regional growth. In: Handbook of regional and urban economics, vol 4. Elsevier, Amsterdam, pp 2671–2711

    Google Scholar 

  • Barca F (2009) An agenda for a reformed cohesion policy: a place-based approach to meeting European Union challenges and expectations. Independent report prepared at the request of the European Commissioner for Regional Policy, Danuta Hübner, European Commission, Brussels

    Google Scholar 

  • Bayar A (2007) Simulation of R&D investment scenarios and calibration of the impact on a set of multi-country models. European Commission DG JRC. Institute for Prospective Technological Studies (IPTS)

    Google Scholar 

  • Brandsma A, Kancs A (2015) RHOMOLO: a dynamic general equilibrium modelling approach to the evaluation of the European Union’s R&D policies. Reg Stud 49:1340–1359

    Article  Google Scholar 

  • Capello R (2007) A forecasting territorial model of regional growth: the MASST model. Ann Reg Sci 41:753–787

    Article  Google Scholar 

  • D’Costa S, Garcilazo E, Oliveira Martins J (2013) The impact of structural and macroeconomic factors on regional growth. OECD regional development working papers 2013/11

    Google Scholar 

  • ESRI (2002) An examination of the ex-post macroeconomic impacts of CSF 1994–1999 on objective 1 countries and regions. http://ec.europa.eu/regional_policy/sources/docgener/evaluation/doc/obj1/macro_modelling.pdf

  • Farole T, Rodriguez-Pose A, Storper M (2011) Cohesion policy in the European Union: growth, geography, institutions. J Common Mark Stud 49:1089–1111

    Article  Google Scholar 

  • Fujita M, Krugman P, Venables A (1999) The spatial economy. MIT Press, Cambridge, MA

    Google Scholar 

  • Hagen T, Mohl P (2009) Econometric evaluation of EU cohesion policy—a survey. Discussion paper no 09-052. Center for European Economic Research, Mannheim

    Google Scholar 

  • Krugman P (1991a) Increasing returns and economic geography. J Polit Econ 99:483–499

    Article  Google Scholar 

  • Krugman P (1991b) Geography and trade. MIT Press, Cambridge, MA

    Google Scholar 

  • McCann P, Ortega-Argilés R (2015) Smart specialisation, regional growth and applications to European Union cohesion policy. Reg Stud 49:1291–1302

    Article  Google Scholar 

  • OECD (2009) How regions grow. Organisation for Economic Growth and Development, Paris

    Google Scholar 

  • Ratto M, Roeger W, In’t Veld J (2009) QUEST III: an estimated open-economy DSGE model of the euro area with fiscal and monetary policy. Econ Model 26:222–233

    Article  Google Scholar 

  • Romer P (1990) Endogenous technological change. J Polit Econ 98:S71–S102

    Article  Google Scholar 

  • Treyz G, Rickman D, Shao G (1992) The REMI economic-demographic forecasting and simulation model. Int Reg Sci Rev 14:221–253

    Article  Google Scholar 

  • Varga A (2006) The spatial dimension of innovation and growth: empirical research methodology and policy analysis. Eur Plan Stud 9:1171–1186

    Article  Google Scholar 

  • Varga A (2007) GMR-Hungary: a complex macro-regional model for the analysis of development policy impacts on the Hungarian economy. Hungarian National Development Office

    Google Scholar 

  • Varga A (2015) Place-based, spatially blind, or both? Challenges in estimating the impacts of modern development policies: the case of the GMR policy impact modeling approach. Int Reg Sci Rev. doi:10.1177/0160017615571587

  • Varga A, Baypinar M (2016) Economic impact assessment of alternative European Neighborhood Policy (ENP) options with the application of the GMR-Turkey model. Ann Reg Sci 56:153–176

    Article  Google Scholar 

  • Varga A, Horváth M (2015) Regional knowledge production function analysis. In: Karlsson C, Anderson M, Norman T (eds) Handbook of research methods and applications in economic geography. Edward Elgar, Cheltenham, pp 513–537

    Google Scholar 

  • Varga A, Járosi P, Sebestyén T, Baypinar M (2013) Deliverable 6.2: detailed policy impact model. Sharing KnowledgE Assets: InteRregionally Cohesive NeigHborhoods (SEARCH) EU FP7 Project. http://www.ub.edu/searchproject/wp-content/uploads/2013/12/SEARCH-Deliverable-6.2.pdf

  • Varga A, Járosi P, Sebestyén T, Szerb L (2015) Extension and application of the GMR-Eurozone model towards the CEE regions for impact assessment of smart specialisation policies. GRINCOH FP 7 project deliverable

    Google Scholar 

  • Varga A, Schalk HJ (2004) Knowledge spillovers, agglomeration and macroeconomic growth. An empirical approach. Reg Stud 38:977–989

    Article  Google Scholar 

  • World Bank (2009) World development report 2009: reshaping economic geography. World Bank, Washington, DC

    Google Scholar 

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Authors and Affiliations

  1. Faculty of Business and Economics, University of Pécs, Pécs, Hungary

    Attila Varga

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  1. Attila Varga
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Correspondence to Attila Varga .

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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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Varga, A. (2017). Geographical Macro and Regional Impact Modeling. 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_3

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