An adaptive agent-based modeling approach for analyzing the influence of transaction costs on emissions trading markets

Abstract

Transaction costs are considered an essential factor that can adversely affect the performance of emissions trading markets. However, most studies are based on a static analyzing framework, making it difficult to simulate real economic situations, in which the dynamic behavior and interaction between firms in an emission trading system are fairly complicated and appear irrational to some extent. Based on an agent-based modeling approach, an artificial sulfur dioxide (SO2) emission trading market is developed to identify the dynamic influence of transaction costs on market efficiency. The simulation results based on empirical data from Jiangsu Province in China reveal that transaction costs have a negligible effect on the market price. However, transaction costs can block a small amount of trading as well as decrease total emission trading amount and market efficiency. Therefore, the policy design of emission trading in China should treat transaction costs carefully.