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

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.