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This study selected listed companies in high-carbon industries in the A-share market of China from 2013 to 2019 as the initial sample. The specific screening process is as follows: Firstly, based on the "China Listed Company Carbon Emission Ranking (2021)" jointly released by the "Caijing" magazine and China Carbon Investment Group, which includes thirteen high-energy consumption and heavily polluting industries such as petrochemicals, chemicals, building materials, steel, non-ferrous metals, papermaking, electricity, aviation, mining, fermentation, textiles, brewing, and pharmaceuticals (Yang et al., 2020), the top 100 A-share companies in terms of carbon emissions on the ranking were identified. Then, according to the industry classification standards of the China Securities Regulatory Commission in 2012, the industries in which these companies are classified were determined. Specifically, 11 industries including electricity, non-metallic mineral products, air transportation, ferrous metal smelting and rolling processing, coal mining and washing, petroleum processing, coking and nuclear fuel processing, and non-ferrous metal smelting and rolling processing were selected as high-carbon industries. To ensure the robustness of the results, ST, *ST companies, and samples with missing variable values were further excluded, resulting in a final sample of 2344 data observations. The data on GEA were manually compiled from the "China Audit Yearbook," while the data on green patent applications by listed companies were sourced from the CNRDS database. Other data were obtained from the CSMAR database. To eliminate the potential impact of outliers on the research results, this study winsorized continuous variables at the 1st and 99th percentiles. Data processing and analysis were conducted using Stata 16 and Excel 2021 software.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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