Scientists Find That Only Technological Innovations Consistently Advance Environmental Sustainability
Renewable energy and labour productivity do not always contribute to environmental sustainability. Technological innovation is the only factor that consistently has a positive effect. This is the conclusion reached by an international team of researchers, including Natalia Veselitskaya, Leading Research Fellow at the HSE ISSEK Foresight Centre. The study has been published in Sustainable Development.
To assess the environmental impact of factors such as economic growth, demographic challenges, technological innovation, renewable energy, and labour productivity, the authors employed an unconventional methodology. This enabled a deeper analysis of the structure of economic–environmental relationships in the studied countries and revealed paradoxes that would likely remain hidden under a standard statistical approach.
The team used a combination of wavelet coherence analysis (WCA) and wavelet quantile regression (WQR). WCA makes it possible to observe how the correlation between variables changes over time and across different frequencies (capturing both short- and long-term fluctuations), while WQR shows how the effect varies depending on the state of the ecosystem itself.
The scientists identified a single consistently effective factor—technological innovation. It is the only driver that has unambiguously improved environmental performance, as reflected in the load capacity factor, across all the studied countries and over all time horizons.
Natalia Veselitskaya
'The introduction of environmental technologies helps increase energy efficiency and reduce emissions in all cases studied,' emphasised Veselitskaya. 'This is a key factor in decoupling economic growth from environmental degradation.'
This finding is important for decision-makers, as support for innovation in green technologies yields predictable and consistent results regardless of national characteristics.
Labour productivity proved to be the most controversial factor. Companies, especially in carbon-intensive sectors, tend to use productivity gains to increase total output rather than reduce resource consumption. In a profit-driven economy, production scales up to the point where the benefits of improved efficiency are outweighed by the growth of the overall environmental footprint.
The study also showed that an increase in the use of renewable energy sources often does not lead to the expected positive outcomes. Rather than replacing carbon-based energy, renewables frequently supplement it, resulting in limited environmental benefits.
The publication of this study was prepared as part of the basic research project 'Trends and Factors of Sustainable Science and Technology Development' (HSE ISSEK, 2025).
See also:
Tabular Data Anonymisation Solution for Safe Use in AI Systems Developed at HSE University
The AI and Digital Science Institute at the HSE Faculty of Computer Science has developed a tabular data anonymisation service designed to prepare corporate datasets for use in analytics and AI applications. The solution can identify personal data in structured datasets, apply consistent and reproducible anonymisation rules, and generate the artifacts required for quality control, auditing, and subsequent use of data in secure environments.
Population Lifespan Is Governed by Mathematical Laws
Researchers at HSE University and MSU have established a universal law governing the time to extinction of a population in a random environment. Their analysis of the evolution of branching processes—complex probabilistic systems—shows that, regardless of the initial population size, extinction follows strict mathematical laws. The results have been published in the Journal of Applied Probability.
Sociologists: Conservative Consumers Dominate Russian Middle Class
The Russian middle class cannot be regarded as a homogeneous and uniformly stable social group. Similar income levels often mask significant differences in financial strategies, lifestyles, and levels of economic security. This is the conclusion reached by sociologists at HSE University. The study has been published in Voprosy Ekonomiki.
Neurolinguists Assist in Awake Surgery on 11-Year-Old Patient with Epilepsy
Researchers at the HSE Centre for Language and Brain took part in a rare awake neurosurgical procedure performed on an 11-year-old patient with drug-resistant epilepsy. Working alongside surgeons at the Voyno-Yasenetsky Centre of Specialised Medical Care for Children in Solntsevo, they monitored the resection of a portion of the left temporal lobe, where the epileptic focus had been identified.
Scientists Explain How Emotions Shape Attitudes Toward Digital Governance
Today, interactions between citizens and government increasingly take place through digital governance platforms, including digital public services, AI-powered systems, and algorithmic decision-making tools. Until now, however, these technologies have largely been viewed as technical instruments, with their effectiveness assessed primarily in terms of efficiency and user-friendliness. The authors of a new study propose a broader perspective, arguing that digital governance should also be understood as an emotional experience that directly shapes citizens' trust in public institutions.
Neural Network Maps as a Method for Constructing Mathematical Models
Scientists from HSE University–Nizhny Novgorod and the Institute of Physics Belgrade, Serbia, are jointly exploring the application of machine learning techniques and neural networks to the study of nonlinear dynamics. Natalya Stankevich, Leading Research Fellow at the Laboratory of Topological Methods in Dynamics of the Faculty of Informatics, Mathematics, and Computer Science at HSE University–Nizhny Novgorod, spoke to the HSE News Service about this international project.
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.
Machine Learning Models Can Help Reduce Volatility and Boost Stock Market Returns
The use of machine learning models makes it possible to achieve greater accuracy in predicting risks in the Russian stock market compared to classical econometric approaches. The predictive power of these models increases by 23%, while the average investor’s return can reach up to 13% per annum. These conclusions were drawn by Nikita Lysenok from the Department of Financial Market Infrastructure at the HSE Faculty of Economic Sciences. The paper has been published in Fundamental and Applied Mathematics.
Pocket Money, Personal Interest, and Family Practices: What Shapes Students’ Economic Literacy?
University students' economic literacy depends not only on their field of study but also on their interest in economics, the learning environment, and family financial practices. For example, students who received pocket money irregularly tend to perform better on economic literacy tests than their peers who received financial support on a regular basis. These findings come from a study conducted by HSE University involving more than 1,100 students from five Russian universities. The findings have been published in Cakrawala Pendidikan.
HSE Study Reveals Imbalance in the Generative AI Market
Researchers at HSE University analysed how effectively the global generative artificial intelligence market converts investment into real revenue, concluding that AI is currently developing faster than it is paying off. The results have been published in the journal Foresight and STI Governance.