This page provides an English interface to the gxceed GX paper corpus. The corpus aggregates papers from 13 open scholarly metadata sources and uses AI-assisted classification to identify signals related to measurement, policy narratives, outcomes, implementation, industrial adoption, and verification.
The goal is not only to discover papers, but to observe how GX research is distributed across research substance, implementation narratives, external expectations, implementation substance, and judgment formation.
Summaries are AI-assisted. Always refer to the original paper for authoritative conclusions.
Showing 461–480 of 803 papers
R. Katoch, Samoon Khan
This study empirically analyzes co-movements and nonlinear dynamics among NFTs, DeFi tokens, and carbon ETFs using wavelet coherence. It finds that correlations intensify during global crises like COVID-19, and carbon ETFs serve as effectiv…
Wenqing Wang, Ling Shao, Sanmang Wu
This paper integrates environmental responsibility with asset pricing by constructing a downstream carbon risk factor (DMC) using the Ghosh input-output model. Adding DMC to the Fama-French five-factor model, it shows that Chinese A-share f…
Manlu Yang, Qing G. Wang
This study examines how China's national ETS expansion to steel, cement, and aluminum affects corporate downside risk. Using a quasi-natural experiment separating MRV onset and public information shock, it finds that early control-year onse…
Derong Yi, Chunyan Li, Tao Wu +4
This paper proposes a low-carbon demand response framework for power-hydrogen integrated energy systems (PH-IESs), including a consumer-based carbon pricing strategy and a demand-side response model for energy aggregators. Distributionally …
Juntao Han, Yibo Han, Yongzhen Wang +4
This study proposes a multi-objective optimization and comparative analysis of wind-solar and wind-solar-gas energy systems under a ladder carbon trading mechanism. It evaluates trade-offs between economic and environmental performance, hig…
Navodana Rodrigo, Srinath Perera, Dilmi Atapattu
This study addresses the lack of carbon trading adoption in the construction industry by leveraging blockchain technology. Using a systematic review of 260 publications, it develops a framework integrating cross-sectoral insights to enhance…
Augustine Senanu Komla Kukah, Xiaohua Jin, Robert Osei-Kyei +1
This study evaluates motivating factors for individuals to participate in carbon trading in the construction industry. Through a survey of Australian industry experts, 13 factors were identified and grouped into attitudes/motivation and awa…
Yan Aditya Pradana, Mohammad Isa Irawan, Imam Mukhlash +1
This study proposes a carbon trading strategy for the European Union Emissions Trading System (EU ETS) using deep stochastic reinforcement learning with risk analysis. It aims to optimize trading decisions under market uncertainty, outperfo…
Rival Pahrijal, Arief Fahmi Lubis, M Ammar Muhtadi
This study analyzes the legality and challenges of carbon trading implementation in Indonesia under Presidential Regulation No. 98/2021. It finds that while the legal framework is formally established, challenges include regulatory fragment…
Peng-peng Yuan, Qingsong Wang
This study uses game theory to analyze how manufacturers can use blockchain to address consumer skepticism about carbon reductions under cap-and-trade policy. It finds that unit abatement is negatively correlated with consumer skepticism an…
Chuanliang Wang, Zhaoxin Liu, Aiping Wang
This paper systematically reviews China's laws and policies on blue carbon sink trading, identifying three core regulatory problems: vague allocation of powers, incomplete transaction rules, and weak accountability. It provides recommendati…
Rahmi Çetin
This systematic literature review synthesizes 32 peer-reviewed articles on CBAM's trade implications. While a minority view CBAM as necessary to prevent carbon leakage, the majority highlight risks of global welfare losses, trade disputes, …
Sukmawati Sukamulya, Veronica Tri Kusuma
This study examines liquidity and market microstructure of tokenized carbon assets (KLIMA, BCT, MCO2) in blockchain-based voluntary carbon markets, using mean-centered MMRM with HAC corrections and a regulation index as moderator. Results s…
Quang Cảnh Trần
This paper introduces a quantum kernel support vector regression (QK-SVR) method for forecasting EU ETS carbon prices. It examines trading resilience during the 2020 crisis and the impact of dynamic Market Stability Reserve (MSR) reforms, d…
Mirzakhalilova Damira, Musaleva Veranika
This study quantitatively assesses the potential financial burden of the EU CBAM on polyethylene exports from Uzbekistan to the EU, using 2020-2024 export data and scenario modeling. Results show additional costs up to €452k per shipment an…
Yuanyuan Wang, Zhuoxuan Yang, Shuyi Hu
Using a staggered DID approach with PSM on Chinese heavy-polluting listed firms from 2010-2024, this study finds that the carbon emission trading pilot boosts green innovation for state-owned enterprises but crowds it out for private firms,…
Dabin Zhang, Jing Zhou, Huanling Hu +1
This paper proposes a novel interval prediction model for carbon prices, integrating quality-driven LUBE (QD-LUBE) with decomposition ensemble. Variational Mode Decomposition (VMD) separates the price series into trend and residual componen…
Zhiyong Zheng, Xue Qiuxia, Tian Jiangwei
This paper examines the impact of carbon emission trading mechanisms on family loan availability from the perspective of family inheritance. It explores the intersection of carbon pricing policies and household finance, with potential impli…
Charles Coverdale
This R package provides unified access to carbon market data from compliance emissions trading systems (EU ETS, UK ETS, RGGI, California Cap-and-Trade) and voluntary registries (Verra, Gold Standard, etc.), including price data from ICAP an…
Liandi Zhang, Shenglin Ma, Yiyao Dai +1
This paper analyzes the impact of China's carbon emission trading pilot policy on energy eco-efficiency using SBM, DID, and spatial econometric models. It finds that the policy significantly improves regional eco-efficiency by reducing poll…
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