Green-patent indicators based on Cooperative Patent Classification Y02 tags increasingly inform research, industrial policy, and climate-oriented investment, yet their construct validity has not been evaluated at corpus scale. We ask whether Y02 classification errors are random measurement noise or systematic, direction-specific bias. We introduce an Error-as-Signal framework in which disagreement between an administrative label and an independent model is treated as evidence of potential measurement error. Screening 9,075,421 USPTO granted patents from 1962-2024 with a fine-tuned domain model identifies 517,772 disagreements. Two independent open-weight large language models then assess whether each flagged invention has a direct climate-mitigation or adaptation function. Cross-model consensus identifies 180,384 administrative Type I errors (False Green) and 29,465 Type II errors (Silent Green). Correcting these errors reduces the measured green-patent population by 25.5%, from 592,387 to 441,468 patents. Misclassification is systematic rather than random. Atypicality predicts Silent Green in an inverted-U pattern, while reflection complexity independently increases under-recognition: controlling for atypicality and filing year, a one-standard-deviation increase is associated with 1.61 times the odds of Silent Green. Structural complexity has the opposite association. Among consensus-attributed errors, the same increase in reflection complexity is associated with 2.45 times the odds that an error is Silent Green rather than False Green. Event tests show no discrete rise in misclassification when green classification became more salient and only limited evidence of increased explicit green framing after the 2013 CPC launch. The evidence is more consistent with bounded classification capacity than with applicant gaming.
This article examines whether environmental taxation induces substantive green innovation or strategic compliance. Using China's 2018 Environmental Fee-to-Tax Reform as a quasi-natural experiment, I study how heavily polluting listed firms adjust their R&D accounting choices and green patenting behavior. I construct an entropy-balanced DID design using firm-level pre-treatment covariates from 2013 to 2017 and analyze Chinese A-share listed firms from 2013 to 2024. The results show that the reform increases R&D expensing while reducing capitalized R&D and the R&D capitalization ratio, suggesting a shift in R&D recognition toward expensing. On the innovation-output side, the reform increases total green patent applications, but the increase is concentrated in green utility model patents rather than green invention patents. The asymmetric patent-quality pattern is robust to PPML, inverse hyperbolic sine transformations, and extensive-margin models. Additional tests show that the results are not driven by MD&A R&D disclosure selection or sample-composition differences. Ownership heterogeneity reveals that SOEs exhibit stronger increases in R&D expensing and utility model patenting, consistent with symbolic compliance, whereas private firms mainly reduce capitalized R&D, consistent with defensive contraction. Overall, the findings suggest that environmental taxation can increase measured green innovation without generating a robust improvement in substantive innovation quality.
Lifan Pang· Frontiers in Environmental E...· 0 citations
Using Patent Application Data from the State Intellectual Property Office of China, we examine the relationship between ESG information disclosure and firms' environmental innovation, using more than 3500 listed firms. Methodologically, we develop a micro‐founded structural model, which maps directly to relevant empirical regressions. The model supports the validity of our identification and design. We find that firms which disclose ESG information average a 15.8% increase in green patent applications and a 21.4% increase in green patent authorizations as compared to non‐disclosers. The effects are stronger for state‐owned enterprises and for larger, more leveraged, and overinvesting firms. The effects are more pronounced when external monitoring is stronger, with higher analyst attention, and in sectors with historically lower pollution, consistent with capital‐market disciplinary pressures and industry norms. In conclusion, the evidence strongly suggests that ESG disclosure is a substantial driver of corporate environmental innovation, which has relevant implications for regulators and financial decision‐makers.
A. Andrikopoulos, P. Michaelides, Guanxia Xie· The Financial Review· 0 citations
This study examines the effect of green public procurement (GPP) on corporate breakthrough green innovation. We construct a novel measure of breakthrough innovation by applying advanced natural language processing models (i.e., SBERT and PatentSBERTa) to the textual similarity of green patent networks. Using a comprehensive panel of Chinese listed firms from 2015 to 2023, we find that GPP significantly catalyses breakthrough green innovation, with the magnitude of the effect increasing with procurement intensity. We identify two primary mechanisms: an external financing channel, where GPP alleviates financial constraints via credit generating effect, and an internal green governance channel, where government demand improves corporate governance through green demand effect. Cross‐sectional tests show the effect is more pronounced in firms receiving higher media attention and in regions with stronger intellectual property rights and stricter environmental regulation. Furthermore, we document significant positive spillovers along both industrial and supply chains. Our results are robust to local projection models, propensity score matching, instrumental variable estimation, omitted variable tests, and double machine learning method. Collectively, these findings highlight the pivotal role of demand‐side policy tools in shaping high‐quality corporate green innovation.
Shaner Chu, Jiamin Zhang· International Journal of Fin...· 0 citations
Patent valuation frameworks typically rely on affirmative indicators such as standard declarations, clause-level mapping, citation activity, product implementation, and licensing history. Yet in litigation, licensing negotiations, and essentiality assessments, valuation outcomes are often shaped by what the record lacks. Missing standard mapping, absent teardown evidence, deployment opacity, or the absence of licensing comparables can materially narrow valuation confidence. This paper formalizes evidentiary absence as a first-class input to patent valuation. Using IN218255, IN240893, Wi-Fi/mmWave SEP examples, and judicial reasoning including Optis $v$ Apple, we develop an absence-aware framework across technical, deployment, and economic evidence layers. The framework introduces ordinal evidence states, absent, semantic proximity, structured evidence, and corroborated evidence, to guide valuation responses ranging from full valuation to constrained range, high uncertainty, or abstention. The approach improves transparency, reproducibility, and auditability in patent value assessment.
Amrutha Moorthy, Raghuram M S· 2026 ITU Kaleidoscope - AI a...· 0 citations
Faced with growing climate change, government policies aimed at fixing market failures have also created significant regulatory and economic uncertainty. This uncertainty influences corporate strategic decisions. Green technological innovation has become a key ability for firms to adapt and compete in a global environment that values sustainability. This study examines how climate policy uncertainty affects corporate green technological innovation. It uses Prospect Theory , Information Asymmetry Theory and data from China’s A-share listed companies between 2013 and 2023. The main explanatory variable, climate policy uncertainty, is built by multiplying a city-level index—based on analyzing mainstream newspaper reports with a deep learning algorithm—by how often green transition keywords appear in firms’ annual reports. The dependent variable, green technological innovation, is measured as the logarithm of a firm’s total yearly green patent applications plus one. The analysis uses a two-way fixed effects model. To address endogeneity, an instrumental variable approach is applied. We use the mayor's remaining years in office and the interaction between the city-level climate physical risk index and industry energy intensity as the instrument for climate policy uncertainty.A mediation model tests two mechanisms: managerial foresight, measured by keyword frequency in annual reports, and analyst coverage, sourced from the CSMAR database. Regional differences are also examined. The results show that: (1) climate policy uncertainty significantly promotes corporate green innovation, with an economic effect of approximately 3.4%. This finding holds across various robustness checks; (2) the positive effect operates through two pathways—stimulating managerial foresight and mitigating information asymmetry; and (3) the effect is stronger for firms in non‑eastern regions of China.
Pengxin Wei, Heng Ma· Proceedings of The Internati...· 0 citations
As China advances its low-carbon transition, understanding how managerial environmental attention is associated with the green technological activity of firms is increasingly important. Using 20,478 firm-year observations for Chinese A-share listed firms from 2016 to 2023, this study examines the associations among disclosed executive green attention, disclosed corporate green transformation orientation, and subsequent green patenting activity. Executive green attention is derived from annual reports, whereas corporate green transformation orientation is derived from annual reports or separately issued responsibility-related reports, depending on availability. Green patent applications are used to capture patent-based environmental innovation activity. The empirical analysis employs firm and year fixed-effects models, firm-clustered bootstrap tests, alternative variable measures, additional industry-by-year and province-by-year fixed effects, and pollution-intensity heterogeneity analyses. The results show that disclosed executive green attention has no statistically significant total or conditional direct association with subsequent green patenting. However, it is positively associated with disclosed corporate green transformation orientation, which is in turn positively associated with green patenting activity. The significant bootstrap coefficient product provides evidence that is consistent with an indirect association through transformation-oriented disclosure, but does not establish causal mediation. The pollution-intensity analysis indicates that the cognition–transformation association is weaker among pollution-intensive firms, while neither the transformation–patenting association nor the overall indirect association differs significantly between the two groups. These findings highlight the relevance of transformation-oriented corporate disclosure to connecting managerial environmental attention with subsequent green patenting, while underscoring the disclosure-based and associational nature of the evidence.