IDEAS home Printed from https://ideas.repec.org/a/spr/anresc/v59y2017i1d10.1007_s00168-017-0829-2.html
   My bibliography  Save this article

Computable urban economic model incorporated with economies of scale for urban agglomeration simulation

Author

Listed:
  • Runsen Zhang

    (Kyoto University
    National Institute for Environmental Studies)

  • Kakuya Matsushima

    (Kyoto University)

  • Kiyoshi Kobayashi

    (Kyoto University)

Abstract

Urban agglomeration has attracted attentions of urban planners, economists, and policymakers. For the sake of urban agglomeration simulation, this paper attempts to develop a computable urban economic (CUE) model incorporated with economies of scale, through the approach of new economic geography. It is assumed that each firm produces a product variant in a monopolistic competition market, and the number of firms is explicit and determined endogenously. The Dixit–Stiglitz type utility function with product variety is adopted into the households’ behavior to reflect consumers’ preference for variety. On the other hand, internal increasing returns to scale and fixed cost are introduced in firms’ behavior to extend the model with economies of scale. The model’s parameter estimations and calibration are conducted on the basis of empirical data from several approved sources for Changzhou in 2008. Numerical computations are implemented by employing the extended CUE model incorporated with economies of scale to explain and examine how the urban agglomeration comes into being. Simulation results show that the extended model incorporated with economies of scale is able to commendably represent the urban agglomeration mechanism, providing a promising simulation tool for urban planning and policymaking.

Suggested Citation

  • Runsen Zhang & Kakuya Matsushima & Kiyoshi Kobayashi, 2017. "Computable urban economic model incorporated with economies of scale for urban agglomeration simulation," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 59(1), pages 231-254, July.
  • Handle: RePEc:spr:anresc:v:59:y:2017:i:1:d:10.1007_s00168-017-0829-2
    DOI: 10.1007/s00168-017-0829-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00168-017-0829-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00168-017-0829-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Anas, Alex & Xu, Rong, 1999. "Congestion, Land Use, and Job Dispersion: A General Equilibrium Model," Journal of Urban Economics, Elsevier, vol. 45(3), pages 451-473, May.
    2. Alex Anas & Yu Liu, 2007. "A Regional Economy, Land Use, And Transportation Model (Relu‐Tran©): Formulation, Algorithm Design, And Testing," Journal of Regional Science, Wiley Blackwell, vol. 47(3), pages 415-455, August.
    3. Dixit, Avinash K & Stiglitz, Joseph E, 1977. "Monopolistic Competition and Optimum Product Diversity," American Economic Review, American Economic Association, vol. 67(3), pages 297-308, June.
    4. John M. Quigley, 1998. "Urban Diversity and Economic Growth," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 127-138, Spring.
    5. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    6. Abdel-Rahman, H. M., 1988. "Product differentiation, monopolistic competition and city size," Regional Science and Urban Economics, Elsevier, vol. 18(1), pages 69-86, February.
    7. Tabuchi, Takatoshi, 1998. "Urban Agglomeration and Dispersion: A Synthesis of Alonso and Krugman," Journal of Urban Economics, Elsevier, vol. 44(3), pages 333-351, November.
    8. Takayuki Ueda & Morito Tsutsumi & Shinichi Muto & Kiyoshi Yamasaki, 2013. "Unified computable urban economic model," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(1), pages 341-362, February.
    9. Anas, Alex & Kim, Ikki, 1996. "General Equilibrium Models of Polycentric Urban Land Use with Endogenous Congestion and Job Agglomeration," Journal of Urban Economics, Elsevier, vol. 40(2), pages 232-256, September.
    10. Runsen Zhang & Kakuya Matsushima & Kiyoshi Kobayashi, 2016. "Land Use, Transport, And Carbon Emissions: A Computable Urban Economic Model For Changzhou, China," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 28(3), pages 162-181, November.
    11. Glazer, Amihai & Gradstein, Mark & Ranjan, Priya, 2003. "Consumption variety and urban agglomeration," Regional Science and Urban Economics, Elsevier, vol. 33(6), pages 653-661, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Runsen & Zhang, Junyi, 2021. "Long-term pathways to deep decarbonization of the transport sector in the post-COVID world," Transport Policy, Elsevier, vol. 110(C), pages 28-36.
    2. Xianzhe Zhang & Yanming Chen & Manchun Li, 2018. "Research on Geospatial Association of the Urban Agglomeration around the South China Sea Based on Marine Traffic Flow," Sustainability, MDPI, vol. 10(9), pages 1-19, September.
    3. Xing, Menglin & Liu, Xiaojun & Luo, Fuzhou, 2023. "How does the development of urban agglomeration affect the electricity efficiency of resource-based cities?—An empirical research based on the fsQCA method," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).

    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. Acocella Nicola & Di Bartolomeo Giovanni, 2013. "Population location, commuting and local public goods: A political economy approach," wp.comunite 0105, Department of Communication, University of Teramo.
    2. Hirte, Georg & Tscharaktschiew, Stefan, 2018. "The impact of anti-congestion policies and the role of labor-supply margins," CEPIE Working Papers 04/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    3. 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.
    4. Georg Hirte & Stefan Tscharaktschiew, 2015. "Why not to choose the most convenient labor supply model? The impact of labor supply modeling on policy evaluation," ERSA conference papers ersa15p303, European Regional Science Association.
    5. Nitzsche, Eric & Tscharaktschiew, Stefan, 2013. "Efficiency of speed limits in cities: A spatial computable general equilibrium assessment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 56(C), pages 23-48.
    6. Stef Proost & Jacques-François Thisse, 2019. "What Can Be Learned from Spatial Economics?," Journal of Economic Literature, American Economic Association, vol. 57(3), pages 575-643, September.
    7. Dröes, Martijn I. & Rietveld, Piet, 2015. "Rail-based public transport and urban spatial structure: The interplay between network design, congestion and urban form," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 421-439.
    8. Combes, Pierre-Philippe, 2000. "Economic Structure and Local Growth: France, 1984-1993," Journal of Urban Economics, Elsevier, vol. 47(3), pages 329-355, May.
    9. Martijn I. Dröes & Piet Rietveld†, 2014. "The Effect of Railway Travel on Urban Spatial Structure," Tinbergen Institute Discussion Papers 14-050/VIII, Tinbergen Institute.
    10. Carl Gaigné & Jacques-François Thisse, 2013. "New Economic Geography and the City," Working Papers SMART 13-02, INRAE UMR SMART.
    11. An-Ming Wang, 2016. "Agglomeration and simplified housing boom," Urban Studies, Urban Studies Journal Limited, vol. 53(5), pages 936-956, April.
    12. Pierre Philippe Combes & Gilles Duranton & Henry G. Overman, 2005. "Agglomeration and the adjustment of the spatial economy§," Papers in Regional Science, Wiley Blackwell, vol. 84(3), pages 311-349, August.
    13. Fujita, Masahisa & Thisse, Jacques-François, 2009. "New Economic Geography: An appraisal on the occasion of Paul Krugman's 2008 Nobel Prize in Economic Sciences," Regional Science and Urban Economics, Elsevier, vol. 39(2), pages 109-119, March.
    14. J.Peter Neary, 2001. "Of Hype and Hyperbolas: Introducing the New Economic Geography," Journal of Economic Literature, American Economic Association, vol. 39(2), pages 536-561, June.
    15. Gali, Jordi, 1995. "Expectations-driven spatial fluctuations," Regional Science and Urban Economics, Elsevier, vol. 25(1), pages 1-19, February.
    16. Roy, Satyaki, 2012. "Spatial Organization Of Production In India: Contesting Themes And Conflicting Evidence," Journal of Regional Development and Planning, Rajarshi Majumder, vol. 1(1), pages 1-16.
    17. Thisse, Jacques-François & Proost, Stef, 2015. "Skilled Cities, Regional Disparities, and Efficient Transport: The state of the art and a research agenda," CEPR Discussion Papers 10790, C.E.P.R. Discussion Papers.
    18. Zeng, Dao-Zhi, 2008. "New economic geography with heterogeneous preferences: An explanation of segregation," Journal of Urban Economics, Elsevier, vol. 63(1), pages 306-324, January.
    19. Tikoudis, Ioannis, 2023. "Revisiting the Pigouvian tax in urban roads: Housing supply restrictions, leaking profits and spatial inequality," Economics of Transportation, Elsevier, vol. 35(C).
    20. Pflüger, Michael & Tabuchi, Takatoshi, 2010. "The size of regions with land use for production," Regional Science and Urban Economics, Elsevier, vol. 40(6), pages 481-489, November.

    More about this item

    JEL classification:

    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General
    • R13 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General Equilibrium and Welfare Economic Analysis of Regional Economies
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure

    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:spr:anresc:v:59:y:2017:i:1:d:10.1007_s00168-017-0829-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.