An agent-situation-based model for networked action situations: Cap-and-trade land policies in China

Rong Tan, Changsheng Xiong and Christian Kimmich

Land Use Policy, 2023, vol. 131, issue C

Abstract: Expanding the analysis unit from a single action situation to networks of action situations (NAS) is a theoretical development in response to complex systemic issues. However, the methodology of this emerging field is still in its infancy. This article develops an agent-situation-based model to evaluate the interaction effects of targeted policies by translating a NAS into an agent-based model (ABM). This paper applies this NAS–ABM method to China’s top-down land planning control system to evaluate the performance of two cap-and-trade (CAT) policies, implemented simultaneously, which aim to preserve cultivated land and restrict land expansion for construction. The results show that either CAT policy can improve land allocation efficiency and reduce income gaps in different regions but is not Pareto-improving. Furthermore, if implemented jointly, the two CAT policies expand the income gap between urban and rural areas and are not conducive to protecting soil quality and the environment.

Keywords: Network of action situations; Agent-situation-based model; Cultivated land; Land quota; Policy interaction (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:lauspo:v:131:y:2023:i:c:s0264837723002090

DOI: 10.1016/j.landusepol.2023.106743

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