Replication Data for "Carbon Emissions Trading and High-Quality Agricultural Development in China: Evidence from Double Machine Learning and Staggered Adoption"
Yonghui Li
🤖 gxceed AI 要約
日本語
本データは、中国の炭素排出権取引（ETS）が農業の高品質発展に与える影響を、二重機械学習と段階的採用手法を用いて評価した研究の再現パッケージです。2007〜2020年の30省パネルデータを分析し、ETSが農業の質的向上に寄与することを示しています。メカニズム分析や地域異質性も検討。
English
This replication package supports a study evaluating the impact of China's carbon emissions trading system (ETS) on high-quality agricultural development using double machine learning and staggered adoption. Analyzing a panel of 30 Chinese provinces from 2007-2020, it finds that ETS promotes agricultural quality improvement, with mechanism and heterogeneity analyses.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
中国のETSは日本でも注目される制度。本論文は農業セクターへの波及効果を定量評価しており、日本のGX政策（排出権取引やカーボンプライシング）の農業への影響を検討する際の参考となる。
In the global GX context
This paper provides causal evidence on the spillover effects of China's ETS to agriculture, relevant for global carbon pricing discussions. The double machine learning method offers a rigorous evaluation approach that can be applied to other policy contexts.
👥 読者別の含意
🔬研究者:A robust causal inference example combining carbon pricing evaluation with double machine learning, applicable to other policy impact studies.
🏢実務担当者:Insights into how carbon pricing can influence agricultural development, useful for corporate sustainability strategies in agri-food supply chains.
🏛政策担当者:Evidence that ETS can have positive spillovers to non-target sectors like agriculture, informing broader carbon pricing design.
📄 Abstract（原文）
This record contains the data, figures, tables, and replication materials supporting the study “Carbon Emissions Trading and High-Quality Agricultural Development in China: Evidence from Double Machine Learning and Staggered Adoption.” The materials include the analysis-ready balanced panel of 30 Chinese province-level units observed annually from 2007 to 2020, comprising 420 province–year observations; variable definitions and source documentation; treatment timing and cross-fitting fold assignments; MATLAB analysis code; and all numerical values underlying the reported tables and figures. The archive further includes all outputs used in the empirical analysis, including cross-fitted predictions, baseline and robustness regression results, event-study estimates, synthetic-control-weighted estimates, permutation test results, mechanism (channel) estimates, and regional heterogeneity estimates. The corresponding figures and tables have been fully revised and updated to ensure consistency with the final estimation results and are included in reproducible form. The analytical panel contains no missing values. Missing observations in the underlying statistical series were interpolated prior to the construction of analytical variables. Original records obtained from statistical yearbooks and third-party databases are not redistributed due to licensing and access restrictions imposed by the data providers. Complete source information is documented within the archive. A development copy of the replication package is available at: https://github.com/tianmv168/carbon-trading-agricultural-development-china
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.5281/zenodo.21620614first seen 2026-07-29 05:01:21 · last seen 2026-07-29 05:01:25
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