Research on Allocation of Urban Land Based on the Fiscal Revenue of Local Governments

Xiaomeng Wang () and Fenjie Long ()
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Xiaomeng Wang: Institute of Real Estate Studies, Tsinghua University
Fenjie Long: Institute of Real Estate Studies, Tsinghua University

Chapter Chapter 23 in Proceedings of the 17th International Symposium on Advancement of Construction Management and Real Estate, 2014, pp 215-224 from Springer

Abstract: Abstract Researches of urban land-use allocation continue to generate increasing attention on how to allocate the available space to several types of land use. Since the creation of tax assignment system in 1994, local governments have been facing both fiscal and political pressure simultaneously. In the Chinese particular system of land supply, income from land sales and relative taxation have become an important source of local revenue and funds for urbanization, which eventually results in the land finance. Against this background, the paper focuses on a method to address land-use allocation issues where the fiscal revenue of local governments is taken into account, which provides an innovation to solve the land-use allocation problems. A model has been designed for the allocation of land-use areas dealing with linear programming as a tool, where the objective is to maximize land financing for local governments. Moreover, the indicators for urban development and sustainability are considered as well: the available amount of land resource, the increasing needs and relative regulations. These are built into the model via constraint equations, marking upper and lower limits to the use of land resources. Finally, feasibility and rationality of the model is discussed combined with the successful application to a case study located in the central region of China.

Keywords: Land use allocation; Quantitative structure; Demand forecast; Linear programming (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-35548-6_23

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DOI: 10.1007/978-3-642-35548-6_23

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