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Forward looking dynamics in spatial CGE modelling

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  • Bröcker, Johannes
  • Korzhenevych, Artem

Abstract

This paper sets up a spatial dynamic CGE framework by combining the optimal growth model of saving and investment under adjustment costs and the spatial CGE model with Dixit–Stiglitz structure in the modern sector. Because of increasing product diversity on the dynamic equilibrium path, the model belongs to the category of semi-endogenous growth models. We overcome the difficulty of existing multiregional models to correctly approximate the infinite horizon equilibrium by employing a theoretically consistent terminal condition. The distinction of goods, factors, firms, and households by location, and the incorporation of trade costs in the model allow to study a variety of issues in regional and transport economics. We describe the model calibration and a tailor-made solution algorithm. The functionality is demonstrated using two illustrative examples.

Suggested Citation

  • Bröcker, Johannes & Korzhenevych, Artem, 2013. "Forward looking dynamics in spatial CGE modelling," Economic Modelling, Elsevier, vol. 31(C), pages 389-400.
  • Handle: RePEc:eee:ecmode:v:31:y:2013:i:c:p:389-400
    DOI: 10.1016/j.econmod.2012.11.031
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    Cited by:

    1. Andries Brandsma & D'Artis Kancs, 2015. "RHOMOLO: A Dynamic General Equilibrium Modelling Approach to the Evaluation of the European Union's R&D Policies," Regional Studies, Taylor & Francis Journals, vol. 49(8), pages 1340-1359, August.
    2. Olga Ivanova & d'Artis Kancs & Mark Thissen, 2019. "EU Economic Modelling System," Papers 1912.07115, arXiv.org.
    3. Elshennawy, Abeer & Robinson, Sherman & Willenbockel, Dirk, 2016. "Climate change and economic growth: An intertemporal general equilibrium analysis for Egypt," Economic Modelling, Elsevier, vol. 52(PB), pages 681-689.
    4. Attila Varga, 2017. "Place-based, Spatially Blind, or Both? Challenges in Estimating the Impacts of Modern Development Policies," International Regional Science Review, , vol. 40(1), pages 12-37, January.
    5. Johannes Bröcker, 2013. "Wider Economic Benefits from Communication-Cost Reductions: An Endogenous Growth Approach," Environment and Planning B, , vol. 40(6), pages 971-986, December.
    6. Attila Varga, 2014. "Challenges in modeling the impacts of modern development policies: The case of the GMR-approach," EcoMod2014 7151, EcoMod.
    7. Ioannis Charalampidis & Panagiotis Karkatsoulis & Pantelis Capros, 2019. "A Regional Economy-Energy-Transport Model of the EU for Assessing Decarbonization in Transport," Energies, MDPI, vol. 12(16), pages 1-27, August.
    8. Varga, Attila, 2020. "A tudástermelési függvénytől a fejlesztéspolitikai hatáselemzésig [From the knowledge production function to development policy-impact modelling]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 537-556.
    9. Olga Ivanova & d'Artis Kancs & Dirk Stelder, 2009. "Modelling Inter-Regional Trade Flows: Data and Methodological Issues in Rhomolo," EERI Research Paper Series EERI RP 2009/31, Economics and Econometrics Research Institute (EERI), Brussels.
    10. Robson, Edward N. & Wijayaratna, Kasun P. & Dixit, Vinayak V., 2018. "A review of computable general equilibrium models for transport and their applications in appraisal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 31-53.
    11. Francesco Di Comite & dArtis Kancs, 2015. "Macro-Economic Models for R&D and Innovation Policies," JRC Working Papers on Corporate R&D and Innovation 2015-03, Joint Research Centre.
    12. Korzhenevych, Artem & Bröcker, Johannes, 2018. "Investment subsidies and regional welfare: A dynamic framework," CEPIE Working Papers 02/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    13. Chen, Zhenhua & Rose, Adam Z. & Prager, Fynnwin & Chatterjee, Samrat, 2017. "Economic consequences of aviation system disruptions: A reduced-form computable general equilibrium analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 207-226.
    14. Vanessa Angst & Chiara Colesanti Senni & Markus Maibach & Martin Peter & Noe Reidt & Renger van Nieuwkoop, 2021. "Economic impacts of decarbonizing the Swiss passenger transport sector," CER-ETH Economics working paper series 21/352, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    15. Wenjie Li & Jialing Dai & Yi Xiao & Shengfa Yang & Chenpeng Song, 2021. "Estimating waterway freight demand at Three Gorges ship lock on Yangtze River by backpropagation neural network modeling," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(3), pages 495-521, September.
    16. Attila Varga & Péter Járosi & Tamás Sebestyén, 2011. "Modeling the growth effects of regional knowledge production: The GMR-Europe model and its applications for EU Framework Program policy impact simulations," ERSA conference papers ersa11p1426, European Regional Science Association.
    17. Ying Jin & Marcial Echenique & Anthony Hargreaves, 2013. "A Recursive Spatial Equilibrium Model for Planning Large-Scale Urban Change," Environment and Planning B, , vol. 40(6), pages 1027-1050, December.
    18. Johannes Bröcker, 2012. "Wider economic benefits from communication cost reductions: an endogenous growth approach," ERSA conference papers ersa12p1165, European Regional Science Association.
    19. Szerb, László & Varga, Attila & Sebestyén, Tamás & Szabó, Norbert, 2019. "A vállalkozás szerepe a gazdasági növekedésben Magyarországon [The role of entrepreneurship in Hungarys economic growth]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 607-634.
    20. Attila Varga & Péter Járosi & Tamás Sebestyén, 2010. "Geographic Macro and Regional Model for EU Policy Impact Analysis of Intangible Assets and Growth," UPFBE Working Paper Series 2010/4, Faculty of Business and Economics, University Pécs.
    21. repec:elg:eechap:14395_2 is not listed on IDEAS

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    More about this item

    Keywords

    Spatial dynamic CGE modeling; Multiple optimizing agents; Transport costs;
    All these keywords.

    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • R13 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General Equilibrium and Welfare Economic Analysis of Regional Economies

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