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An Evolutionary Game Analysis on the Choice of Urban Housing Purchase Restriction Policy

In: Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate

Author

Listed:
  • Guancen Wu

    (Shanghai University)

  • Shanshan Xi

    (Shanghai University)

  • Huan Chen

    (Shanghai University)

Abstract

High-growth housing prices have prompted the city’s local government to continue to introduce a series of housing purchase policies aimed at regulating market demand. This paper explores the evolution of the decision-making process of the central city and the sub-central city from the perspective of evolutionary game theory, obtains the evolution law and behavior evolution of the two cities according to the replicated dynamic equation, and analyzes the influencing factors of the policy of housing purchase restriction in different types of cities. The results show that different types of city property purchase restrictions on the execution closely relates to the purchase discount policy benefits, spillover effect, the purchase of the implementation of the purchase cost, restriction of increased social welfare, unlimited increase in social risk, economic gains without restriction, value-added benefits of mutual restriction between cities, and the risk of collective irrationality caused by the mutual restriction between cities. Finally, some corresponding recommendations of urban housing purchase restriction have been put forward for the local government to formulate reasonable housing control polices.

Suggested Citation

  • Guancen Wu & Shanshan Xi & Huan Chen, 2021. "An Evolutionary Game Analysis on the Choice of Urban Housing Purchase Restriction Policy," Springer Books, in: Fenjie Long & Sheng Zheng & Yuzhe Wu & Gangying Yang & Yan Yang (ed.), Proceedings of the 23rd International Symposium on Advancement of Construction Management and Real Estate, pages 476-492, Springer.
    • Handle: RePEc:spr:sprchp:978-981-15-3977-0_36
    DOI: 10.1007/978-981-15-3977-0_36
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