When Regulation Meets the Market: Synergistic Effects of Waste Sorting Policy and Emissions Trading Scheme on Carbon Emission Efficiency in Urban China

Data Description：
This dataset contains annual panel data for 283 prefecture-level and above cities in China (2000–2022), including policy start years, processed data, code files, and figures. It is used to study the synergistic effects of the Waste Sorting Policy (WSP) and the Emissions Trading Scheme (ETS) on Carbon Emission Efficiency (CEE).

Files：
byear_ETS.dta — ETS start years from official government sources.
byear_WSP.dta — WSP start years from official government sources.
DATA.xlsx — Main data and variable definitions.
DATA1.dta — Stata-processed version of DATA.xlsx.
data1235.dta — Final dataset with ETS/WSP years and controls.
do_WSP+ETS.do — Stata code for data processing, variable construction, model estimation, and robustness checks.
Figure_1 — Spatial distribution of WSP and ETS pilot cities (ArcGIS).
Figure_2 — Parallel Trend Test results from the code file.
Figure_3 — Spatial and temporal dynamics of CEE in China, 2000–2022, along with the distribution of Carbon Emission Intensity (CEI). CEE and CEI are logarithmically related. CEI is not analyzed in this paper and is shown here only for reference.

Data Sources and Processing：
Carbon emissions: ODIAC 2022 (1 km × 1 km resolution), covering fossil fuel combustion, cement production, and gas flaring. Aggregated by city boundaries following Du et al. (2021) and Fang et al. (2022a).
Socioeconomic/environmental data: China City Statistical Yearbook, China Environmental Statistical Yearbook, and CNRDS database.
Policy data: WSP and ETS years identified from official documents of the National Development and Reform Commission and the Ministry of Housing and Urban–Rural Development.
Processing: Missing years interpolated; monetary variables deflated; some variables log-transformed.

Main Hypothesis and Findings：
Hypothesis: Joint WSP–ETS implementation produces greater CEE gains than either policy alone.
Findings: Significant synergy, strongest when ETS precedes WSP; driven by greater science/education investment and industrial optimization; effects largest in more developed, populous, and education-rich cities.

Uses：
Applicable for econometric analysis, urban policy evaluation, and low-carbon transition research.