Resumen de An agent-situation-based model for networked action situations: Cap-and-trade land policies in China
Rong Tan, Changsheng Xiong, Christian Kimmich
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.
