IDEAS home Printed from https://ideas.repec.org/a/gai/recdev/r2242.html
   My bibliography  Save this article

Simulated Spatial Model of Russian Urban Development
[Имитационная Пространственная Модель Развития Российских Городов]

Author

Listed:
  • Kirill V. Rostislav

    (Russian Presidential Academy of National Economy and Public Administration)

  • Yury Yu. Ponomarev

    (Russian Presidential Academy of National Economy and Public Administration; Gaidar Institute for Economic Policy)

  • Darya M. Radchenko

    (Russian Presidential Academy of National Economy and Public Administration)

Abstract

The paper presents a spatial simulation model covering 237 cities and towns in 76 subjects of the Russian Federation. The model describes the dynamics of the population and the number of enterprises in the cities, and also makes it possible to make medium-term forecasts with a high degree of accuracy. The work tested hypotheses about the impact on intercity migration and other socio-economic processes that determine the differences between the cities in average wages, the quality of urban environment and other factors, and also considered examples of the application of the model to assess the socio-economic effects of high-speed roads construction (on the example of the Sochi – Tuapse road) and the effects of the closure of city-forming enterprises in several single-industry towns. The article was prepared in the framework of execution of state order by RANEPA.

Suggested Citation

  • Kirill V. Rostislav & Yury Yu. Ponomarev & Darya M. Radchenko, 2022. "Simulated Spatial Model of Russian Urban Development [Имитационная Пространственная Модель Развития Российских Городов]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 5, pages 20-33, May.
    • Handle: RePEc:gai:recdev:r2242
    as

    Download full text from publisher

    File URL: http://www.iep.ru/files/RePEc/gai/recdev/r2242.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Treb Allen & Costas Arkolakis, 2014. "Trade and the Topography of the Spatial Economy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(3), pages 1085-1140.
    2. Marco Raberto & Bulent Ozel & Linda Ponta & Andrea Teglio & Silvano Cincotti, 2019. "From financial instability to green finance: the role of banking and credit market regulation in the Eurace model," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 429-465, March.
    3. Raberto, Marco & Teglio, Andrea & Cincotti, Silvano, 2012. "Debt, deleveraging and business cycles: An agent-based perspective," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-49.
    4. Christophe Deissenberg & Sander van Der Hoog & Herbert Dawid, 2008. "EURACE: A Massively Parallel Agent-Based Model of the European Economy," Working Papers halshs-00339756, HAL.
    5. Mebane Jr., Walter R. & Sekhon, Jasjeet S., 2011. "Genetic Optimization Using Derivatives: The rgenoud Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i11).
    6. Andrea Mazzocchetti & Marco Raberto & Andrea Teglio & Silvano Cincotti, 2018. "Securitization and business cycle: an agent-based perspective," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(6), pages 1091-1121.
    7. Daniel J. Graham, 2007. "Agglomeration, Productivity and Transport Investment," Journal of Transport Economics and Policy, University of Bath, vol. 41(3), pages 317-343, September.
    8. Clémentine Cottineau & Paul Chapron & Romain Reuillon, 2015. "Growing Models from the Bottom Up. an Evaluation-Based Incremental Modelling Method (EBIMM) Applied to the Simulation of Systems of Cities," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(4), pages 1-9.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kirill V. Rostislav & Yury Yu. Ponomarev & Darya M. Radchenko, 2022. "Имитационная Пространственная Модель Развития Российских Городов," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 5, pages 20-33, May.
    2. Bertani, Filippo & Ponta, Linda & Raberto, Marco & Teglio, Andrea & Cincotti, Silvano, 2021. "The complexity of the intangible digital economy: an agent-based model," Journal of Business Research, Elsevier, vol. 129(C), pages 527-540.
    3. Bertani, Filippo & Ponta, Linda & Raberto, Marco & Teglio, Andrea & Cincotti, Silvano, 2019. "An economy under the digital transformation," MPRA Paper 94205, University Library of Munich, Germany.
    4. Filippo Bertani & Marco Raberto & Andrea Teglio, 2020. "The productivity and unemployment effects of the digital transformation: an empirical and modelling assessment," Review of Evolutionary Political Economy, Springer, vol. 1(3), pages 329-355, November.
    5. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2015. "An agent based decentralized matching macroeconomic model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 305-332, October.
    6. Roberto Veneziani & Luca Zamparelli & Michalis Nikiforos & Gennaro Zezza, 2017. "Stock-Flow Consistent Macroeconomic Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1204-1239, December.
    7. Ricetti, Luca & Russo, Alberto & Gallegati, Mauro, 2013. "Unemployment benefits and financial leverage in an agent based macroeconomic model," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 7, pages 1-44.
    8. Silvano Cincotti & Marco Raberto & Andrea Teglio, 2022. "Why do we need agent-based macroeconomics?," Review of Evolutionary Political Economy, Springer, vol. 3(1), pages 5-29, April.
    9. Alessandro Caiani & Ermanno Catullo & Mauro Gallegati, 2018. "The effects of fiscal targets in a monetary union: a multi-country agent-based stock flow consistent model," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(6), pages 1123-1154.
    10. Carlos M. Fernández-Márquez & Matías Fuentes & Juan José Martínez & Francisco J. Vázquez, 2021. "Productivity and unemployment: an ABM approach," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(1), pages 133-151, January.
    11. Nieddu, Marcello & Bertani, Filippo & Ponta, Linda, 2021. "Sustainability transition and digital trasformation: an agent-based perspective," MPRA Paper 106943, University Library of Munich, Germany.
    12. Giovanni Dosi & Andrea Roventini, 2019. "More is different ... and complex! the case for agent-based macroeconomics," Journal of Evolutionary Economics, Springer, vol. 29(1), pages 1-37, March.
    13. Bence Mérõ, 2019. "Novel Modelling of the Operation of the Financial Intermediary System – Agent-based Macro Models," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 18(3), pages 83-113.
    14. Caiani, Alessandro & Russo, Alberto & Gallegati, Mauro, 2016. "Does Inequality Hamper Innovation and Growth?," MPRA Paper 71864, University Library of Munich, Germany.
    15. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 67-116.
    16. Phillip Anthony O’Hara, 2021. "Objectives of the Review of Evolutionary Political Economy’s ‘Manifesto’ and editorial proposals on world problems, complex systems, historico-institutional and corruption issues," Review of Evolutionary Political Economy, Springer, vol. 2(2), pages 359-387, July.
    17. Irene Monasterolo & Nepomuk Dunz & Andrea Mazzocchetti & Régis Gourdel, 2022. "Derisking the low-carbon transition: investors’ reaction to climate policies, decarbonization and distributive effects," Review of Evolutionary Political Economy, Springer, vol. 3(1), pages 31-71, April.
    18. Kirill S. Glavatskiy & Mikhail Prokopenko & Adrian Carro & Paul Ormerod & Michael Harre, 2020. "Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large scale agent-based model," Papers 2004.07571, arXiv.org.
    19. J. Farmer & Cameron Hepburn & Penny Mealy & Alexander Teytelboym, 2015. "A Third Wave in the Economics of Climate Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(2), pages 329-357, October.
    20. Marcello Nieddu & Filippo Bertani & Linda Ponta, 2022. "The sustainability transition and the digital transformation: two challenges for agent-based macroeconomic models," Review of Evolutionary Political Economy, Springer, vol. 3(1), pages 193-226, April.

    More about this item

    Keywords

    simulation model; migration; cities; single-industry towns; infrastructure projects;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population
    • R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gai:recdev:r2242. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Olga Beloborodova (email available below). General contact details of provider: https://edirc.repec.org/data/gaidaru.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.