Ying Gang's dataset supports analysis of digitalization's effect on agricultural carbon decoupling. It contains a balanced panel of 310 province-year observations from 31 Chinese provinces between 2014 and 2023. The data was submitted to the Journal of Environmental Management and published via Harvard Dataverse.
Use Cases
- Analyze the relationship between the digital-intelligence integration index and the Tapio-framework-derived ordered decoupling index.
- Conduct heterogeneity analysis across the 31 Chinese provinces using provincial panel data.
- Apply the KHB-feologit framework to identify mechanisms linking digitalization to carbon decoupling status.
- Examine temporal trends in agricultural carbon decoupling from 2014 to 2023.
Strengths
- 310 province-year observations provide a balanced panel for statistical analysis.
- Covers 31 Chinese provinces over a 10-year period (2014-2023) for longitudinal study.
Limitations
- Limited to 310 total observations, which may constrain complex model training.
- Geographic scope is restricted to China, limiting international generalizability.
- Specific column names and data granularity are not provided in the description.
Provenance
- Source
- Harvard Dataverse, author Ying Gang.
- Collection Method
- Compiled for empirical analysis in a submitted manuscript on agricultural carbon decoupling.
- Time Range
- 2014 to 2023.
- Freshness
- Data covers up to 2023 and was last updated in March 2026.
- Geography
- 31 Chinese provinces (autonomous regions and municipalities).