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Forecasting Urban Land-Use Demand Using a Metropolitan Input-Output Model

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  • Myung-Jin Jun

    (Department of Urban and Regional Planning, Chung-Ang University, Ansung, Kyunggido, South Korea)

Abstract

The purpose of this paper is to develop an urban land-use-demand forecast model using a metropolitan input–output model and gravity-type spatial interaction models. The feasibility of the proposed model is tested with actual data from the Seoul metropolitan area by estimating the effects of urban-growth-control policy on urban economy, employment, population, and land-use demand. Three main features are highlighted: (1) the proposed model can estimate and project urban land-use demand on a firm theoretical foundation because land-use demand is determined by the interindustrial and interspatial relations of production, income formation, and consumption through metropolitan input–output multipliers; (2) the proposed model has practical advantages over other urban land-use models in terms of operational cost because it is relatively easy to operate within the input–output framework and it has fewer requirements of data and parameter calibration; and (3) the proposed model has the capability to incorporate changes in attractiveness, accessibility, land availability, and other policy variables in projecting and estimating urban land-use demand, which is an important feature for policy evaluation. The simulation results prove the feasibility of the proposed model as an urban-policy evaluation tool, which provides significant implications to urban policy analysts. The simulation results indicate that a growth-control policy decreases output and employment for the overall urban economy. The model results also show that a city with a growth-control policy is negatively impacted with regards to output, employment, population, and residential and nonresidential land-use demand, whereas the surrounding cities receive positive spillover effects due to the land-use regulation.

Suggested Citation

  • Myung-Jin Jun, 2005. "Forecasting Urban Land-Use Demand Using a Metropolitan Input-Output Model," Environment and Planning A, , vol. 37(7), pages 1311-1328, July.
    • Handle: RePEc:sae:envira:v:37:y:2005:i:7:p:1311-1328
    DOI: 10.1068/a3723
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    References listed on IDEAS

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    1. Myung-Jin Jun, 2004. "A metropolitan input-output model: Multisectoral and multispatial relations of production, income formation, and consumption," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 38(1), pages 131-147, March.
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    5. Landis, John D., 1994. "The California Urban Futures Model: A New Generation of Metropolitan Simulation Models," University of California Transportation Center, Working Papers qt9pb6g3g6, University of California Transportation Center.
    6. Deal, Brian & Schunk, Daniel, 2003. "Spatial Dynamic Modeling and Urban Land Use Transformation:," Sonderforschungsbereich 504 Publications 03-22, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    7. Deal, Brian & Schunk, Daniel, 2003. "Spatial dynamic modeling and urban land use transformation : an ecological simulation approach to assessing the costs of urban sprawl," Papers 03-22, Sonderforschungsbreich 504.
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    Cited by:

    1. Yajun Ma & Ping Zhang & Kaixu Zhao & Yong Zhou & Sidong Zhao, 2022. "A Dynamic Performance and Differentiation Management Policy for Urban Construction Land Use Change in Gansu, China," Land, MDPI, vol. 11(6), pages 1-31, June.
    2. Myung-Jin Jun, 2012. "The effects of Seoul’s greenbelt on the spatial distribution of population and employment, and on the real estate market," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 49(3), pages 619-642, December.
    3. Ana Viñuela & Esteban Fernández Vázquez, 2012. "From the periphery to the core: direct and indirect effects of the migration of labour," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 32(1), pages 1-18, March.
    4. Xia, Chang & Zhang, Anqi & Wang, Haijun & Liu, Jiafeng, 2020. "Delineating early warning zones in rapidly growing metropolitan areas by integrating a multiscale urban growth model with biogeography-based optimization," Land Use Policy, Elsevier, vol. 90(C).
    5. Myung-Jin Jun, 2012. "The Economic Costs and Transport Benefits of Seoul’s Industrial Land Use Controls," Urban Studies, Urban Studies Journal Limited, vol. 49(8), pages 1791-1810, June.
    6. Ke Wang & Li Wang & Jianjun Zhang, 2024. "Towards a Comprehensive Framework for Regional Transportation Land Demand Forecasting: Empirical Study from Yangtze River Economic Belt, China," Land, MDPI, vol. 13(6), pages 1-22, June.
    7. Myung‐Jin Jun, 2009. "Economic Impacts Of Seoul'S Job Decentralization: A Metropolitan Input–Output Analysis," Journal of Regional Science, Wiley Blackwell, vol. 49(2), pages 311-327, May.
    8. Biao Zhang & Dian Shao & Zhonghu Zhang, 2022. "Spatio-Temporal Evolution Dynamic, Effect and Governance Policy of Construction Land Use in Urban Agglomeration: Case Study of Yangtze River Delta, China," Sustainability, MDPI, vol. 14(10), pages 1-36, May.
    9. Eda Ustaoglu & Filipe Batista e Silva & Carlo Lavalle, 2020. "Quantifying and modelling industrial and commercial land-use demand in France," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(1), pages 519-549, January.

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