Many investors were discouraged from China exposure in 2021 because of regulatory concerns. Various agencies established new requirements that would affect a wide range of industries in China. However, one area that saw positive support was the emphasis on sustainability and environmental policies.
China’s focus on environmental policies continues to be at the top of its agenda, both at the regulatory agency and fiscal levels. A recent research paper published by NatureThe policy intensity growth in China regarding the environment and sustainability was tracked using both manual and machine-learning analysis. It was found to have trended upwards throughout the time period, reflecting China’s increasing commitment to sustainability.
This is a sign that China has been strengthening its regulations to combat environmental issues through various types of policies, according to the paper’s authors. It is becoming more apparent that different types of policy are being used, which indicates that China is adopting a differentiated strategy for environmental governance.
The data used included an analysis 1,912 Chinese environmental policies between 1978 and 2019. This was the first major analysis of Chinese environmental policy.
Image source: Nature
Researchers found that China’s environmental regulatory support was largely driven by command-and-control policies. These are mandatory policies that have governance standards and requirements. The market-based environment policy pressure on China also increased. This is due to fiscal policies that relate to instruments such as emissions trading and environmental governance.
The final policy measured was public participation environmental policy, which measures public and private sector participation in environmental sustainability and revolves around keywords such as”public participation,” “hearing,” “seek advice,” and “citizens,” among others.
Our dataset is the largest collection of environmental policies that have had their intensity scores calculated by both human experts as well as learning-based models. This explains the alignment between the machine learning algorithms’ results and the manual calculations. This shows that machine learning algorithms can measure intensity with high accuracy compared to manual quantifications, indicating a changing trend in policy intensity.
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