Data · dataset · 2026
Datasets related to artificial intelligence, pollution abatement, and environmental regulations from 2012 to 2024.
Listed in ScienceDB
This study takes Chinese A-share listed manufacturing companies on the Shanghai and Shenzhen stock exchanges as the research subjects, with the sample period ranging from 2012 to 2024.
Description
The rationale for selecting manufacturing firms as the research subjects is that the manufacturing sector is the primary source of industrial pollution emissions, with its wastewater and waste gas pollutants accounting for the major share of total industrial emissions.
Therefore, studying pollution abatement in manufacturing has significant practical implications. The data sources of this study mainly include the following aspects: financial data and corporate governance data are obtained from the CSMAR database; pollution emission data are obtained from the CSMAR Environmental Database, including emissions of pollutants such as chemical oxygen demand, ammonia nitrogen, total nitrogen, total phosphorus, sulfur dioxide, nitrogen oxides, and soot; environmental penalty data are obtained from the Public Environmental Research Center website and the CSMAR Environmental Regulation Database; environmental investment data are obtained from annual reports of listed companies, manually compiled from the detailed items of "construction in progress" and "administrative expenses"; ISO14001 certification data are obtained from the "Environmental Regulation and Certification Disclosure" sub-database within the CSMAR Environmental Research Database.
Read the rest (2 more)
To ensure the representativeness of the sample and the reliability of the data, the raw data are processed as follows: firms classified as ST, *ST, and PT are excluded, as these firms have abnormal operating conditions and their financial data may be distorted; observations with missing values for core variables are excluded; and all continuous variables are winsorized at the 1st and 99th percentiles to eliminate the interference of extreme outliers on the regression results.
After the above screening and processing, a total of 20,211 firm-year observations are obtained for the period from 2012 to 2024.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.011xs ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Environmental engineering 70%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.011xs | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:4011 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (70%) |
| concepts[field].local:field:computer-science-ai | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |