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Biodiversity what direct risks does AI pose to the climate and environment?
No full textArtificial intelligence (AI) is increasingly being embedded into the daily functioning of sectors from healthcare to finance, agriculture and environmental management. While it has the potential to support climate action and biodiversity conservation, unmitigated growth in AI use poses significant ethical and direct climate and environmental risks. These direct risks primarily stem from the significant infrastructure needed to build and operate AI systems, including energy and water-intensive data centres and critical mineral extraction. Importantly, the use of AI can also directly cause environmental harm
Five books on the struggle for climate justice
Get PDFAs nations gather for talks at COP30 in Belém, Brazil, Eoin Jackson recommends five books that expose the roots and realities of the struggle for climate justice
Diagnosing the West’s China missteps: systemic gaps that derail business ambitions
No full textFrom cultural misreads to regulatory blind spots, systemic flaws, not isolated errors, account for why so many Western companies stumble in China
Macroeconomic and financial risks transmitted by the European Union Deforestation Regulation: a focus on the coffee value chain in Honduras
Get PDFThe European Union’s Deforestation Regulation (EUDR) poses nature-related transition risks for countries exporting to the EU market. The coffee value chain in Honduras provides an excellent context in which to study this, in view of the country’s extreme economic dependence on this highly relevant sector and the overwhelming reliance on smallholder and household producers. The macroeconomic and financial risks transmitted by the EUDR — especially for climate-vulnerable and commoditydependent economies — remain underexplored. Findings suggest that the overall risks of exclusion for Honduran producers remain extremely high because of the legality and traceability requirements of the EUDR, putting approximately 20% of the country’s exports and 7% of its foreign exchange at risk. The general exposure of banks through loans to the coffee sector, as a share of total lending portfolios, is low. However, at the individual level, some banks are highly exposed to credit risks arising from default, with potential for regional spillovers. Finally, the interaction of nature-related transition and climate risks deserves greater attention, given the potential for both financial and trade-related exclusion
Pediatric studies and labeling additions required by the U.S. FDA for novel drugs approved from 2011 to 2023: a retrospective cohort study
Get PDFBackground The U.S. Food and Drug Administration (FDA) has the authority to require that sponsors conduct pediatric studies for certain new drugs under the Pediatric Research Equity Act (PREA). Here, we evaluate the characteristics and completion of these studies and assess the addition of pediatric-specific evidence generated from these studies into drug labeling. Methods and findings We performed a retrospective cohort study of all novel drugs approved by the FDA from 2011 to 2023 with at least one pediatric study requirement issued under PREA. Study status and outcomes were followed through 31 December 2024. We assessed completion of pediatric studies; addition of pediatric prescribing information to drug labels; and deviations from FDA-projected timelines. Of 552 novel drugs approved by the FDA between 2011 and 2023, 179 (32.4%) were subject to pediatric study requirements under PREA. Thirteen were later discontinued, resulting in a final cohort of 166 drugs and 338 pediatric study requirements. About half (51.8%) of the studies assessed efficacy. Among 222 studies with due dates by 31 December 2024, only 24.3% were completed by the original deadline. Over half (56.8%) received extensions of original timelines, by an average of 2.9 years (SD 2.0). At 10 years after drug approval, while 92.0% of studies were expected to have been completed, 59.5% had been completed. Of the 117 drugs with studies due by 31 December 2024, 54.7% (n = 64) had pediatric labeling updated with results from required studies. The mean time to addition of pediatric approval was 5.7 years (SD 2.6), whereas labeling additions reflecting lack of pediatric safety or benefit took an average of 8.3 years (SD 3.3) (p < 0.001). While 90.4% of drugs were expected to have all pediatric studies completed by 10 years, only 52.8% had any labeling changes reflecting data from the PREA-mandated studies. A limitation of this study is that publicly available FDA data provide limited detail on study design, execution, and reasons for delays, preventing assessment of study rigor and the factors contributing to delayed completion. Conclusions PREA was implemented to advance pediatric drug research and fill a critical gap in pediatric labeling of new drugs. However, our findings reveal frequent delays in study completion and labeling updates, with just over half of labeling additions completed 10 years after drug approval. Strengthening reporting requirements and expanding the FDA’s enforcement authority are essential to ensuring that children receive timely access to safe and effective therapies supported by high-quality evidence
Identification and estimation for matrix time series CP-factor models
No full textWe propose a new method for identifying and estimating the CP-factor models for matrix time series. Unlike the generalized eigenanalysis-based method of Chang et al. (2023) for which the convergence rates of the associated estimators may suffer from small eigengaps as the asymptotic theory is based on some matrix perturbation analysis, the proposed new method enjoys faster convergence rates which are free from any eigengaps. It achieves this by turning the problem into a joint diagonalization of several matrices whose elements are determined by a basis of a linear system, and by choosing the basis carefully to avoid near co-linearity (see Proposition 5 and Section 4.3). Furthermore, unlike Chang et al. (2023) which requires the two factor loading matrices to be full-ranked, the proposed new method can handle rank-deficient factor loading matrices. Illustration with both simulated and real matrix time series data shows the advantages of the proposed new method
ASCOR in practice: use cases and insights
Get PDFASCOR is an investor-led initiative launched to provide comprehensive and comparable assessments on how sovereigns are managing the low-carbon transition as well as the physical risks stemming from climate change. This report outlines use cases for the ASCOR tool, organised by user type: investors and sovereign bond issuers. We explain how these users might harness the ASCOR tool for their respective needs. The potential use cases and practical case studies are gleaned from the TPI Centre’s research and outreach through bilateral meetings, webinars and roundtables with various stakeholders. The report is designed to expand awareness of the practical applications of the ASCOR tool as well as stimulate greater use
Associations between adverse childhood experiences and cardiometabolic health in later adulthood in Colombia
Get PDFBackground Adverse childhood experiences (ACEs) are traumatic events that occur before a child reaches the age of 15 with long-term health consequences, economic costs and intergenerational challenges for society. This study investigated the association between ACEs and cardiometabolic risk (cardiovascular disease (CVD), diabetes, hypertension and obesity) in adulthood. Methods We used data from the Survey on Health, Well-Being and Ageing (SABE)-Colombia (n=18 044 adults aged >65). Exposures were defined as single and cumulative ACEs score. Logistic regression, adjusted for demographics and socioeconomic position, was used to investigate associations. Results 41.3% reported at least one ACE and 4.2% reported four or more. Associations between individual ACEs and outcomes differed by gender. In women, exposure to all ACEs, except childhood migration, was associated with increased odds of CVD, for example, emotional abuse (OR=1.69 (95% CI 1.32 to 2.13)) and poor childhood health status (OR=1.64 (95% CI 1.39 to 1.91)). Among men, these associations were much weaker and often non-statistically significant, except childhood migration that showed increased odds of CVD (OR=1.55 (95% CI 1.09 to 2.15), diabetes (OR=1.55 (95% CI 1.11 to 2.14)) and hypertension (OR=1.40 (95% CI 1.07 to 1.83) in adulthood). A significant association was observed between cumulative ACEs score and odds of CVD, diabetes and hypertension in both men and women. This pattern was not observed for obesity. Conclusion The long-term health consequences of ACEs differ by gender. Longitudinal studies are needed to establish causality and identify mediators. Public health interventions should adopt gender-sensitive, holistic approaches integrating biological, environmental, social and behavioural dimensions, and prioritise early-life interventions to address long-term health inequalities