Examining the representativeness heuristic and anchoring effects in China's carbon markets

Abstract

This paper proposes a novel integrated approach incorporating grey relational analysis, corresponding correlation test, with vector autoregression and panel vector autoregression models to examine the representativeness heuristic and anchoring effects in carbon markets. The grey relational analysis and corresponding correlation test measure the representativeness heuristic in eight pilot carbon markets. The vector autoregression and panel vector autoregression models detect the anchoring effects in eight pilot carbon markets and the overall carbon market. The study first explores the representativeness heuristic and anchoring effects in China's carbon markets. Taking the 2014–2021 United Nations Climate Change Conferences (COP20–COP26) as an event, the proposal of China's carbon emissions peak and carbon-natural targets, as well as the establishment of China's national carbon market as three events, the empirical results demonstrate that Hubei, Guangdong, Shenzhen, Beijing, Shanghai, and Chongqing six pilot carbon markets were found to exhibit the representativeness heuristics for the COP21. Hubei, Shenzhen, Beijing, and Chongqing carbon markets were found to exhibit the representativeness heuristics for the proposal of China's carbon emissions peak and carbon-natural targets, and the establishment of China's national carbon market. Anchoring effects were found to exist in Guangdong, Tianjin, and Chongqing carbon markets, while no anchoring effect has been found to exist in the overall carbon market. Investor sentiment is one of the crucial factors affecting carbon prices.