Green Energy Patents Boost Company Profitability
For nuclear energy, the increase can be up to 1.6%
An ESG strategy—Environmental, Social, and Corporate Governance—not only helps preserve the environment but can also generate tangible income. Thus, the use of renewable energy sources (RES) and green technologies in the energy sector enhances return on investment and profitability. In contrast, higher CO2 emissions result in lower financial performance. This has been demonstrated in a collaborative study by the HSE Faculty of Economic Sciences and the European University at St. Petersburg. Their findings have been published in Frontiers in Environmental Science.
In recent years, green energy technologies have made significant advancements. Governments and businesses invest hundreds of billions of dollars in developing renewable energy sources (RES), nuclear energy, and electric transportation. In 2020, their share accounted for 40% of all investments in the energy sector, totalling $400 billion. In the European Union, spending on green energy is 3.5 times higher than on traditional energy. Meanwhile, China has reduced investments in the gas and oil sectors by 40% to focus on developing RES. Increasingly, research demonstrates that adopting green technologies can have a positive impact on company profitability.
Elena Makeeva, Associate Professor at the HSE Faculty of Economics, Konstantin Popov, Research Assistant at the HSE Corporate Finance Centre, and Olga Teplova, Research Fellow at the European University at St. Petersburg, have investigated how investments in green energy impact the profitability of energy companies in the BRICS countries. The researchers studied 63 largest firms in the BRICS countries and examined their key financial performance indicators, including return on assets (ROA), return on invested capital (ROIC), and market capitalisation.
CO2 emissions and patents related to three primary types of green energy—renewable energy technologies, combustion technologies with mitigation potential, and nuclear energy technologies—were considered as independent variables. China leads among BRICS member countries in all types of patents, with its share reaching 94% for patents in the field of renewable energy and 89% for patents related to hybrid energy systems.
The model also incorporated the company's revenue and investments, along with the per capita GDP of the company's home country, as controls. The authors constructed several models to establish a connection between investments in green technologies, carbon dioxide emissions, and the return on assets and investments, and market capitalisation of companies.
They have found that higher CO2 emissions significantly reduce company profitability and negatively affect market capitalisation: a 1% increase in carbon dioxide emissions results in nearly a 2% decrease in company profitability. The return on investment decreases even further, by 5% to 7%, along with a decrease in market capitalisation. Conversely, the more 'green energy' patents a company registers, the greater its profitability. The return on assets increases by 0.7% on average, and patents in the field of nuclear energy result in the largest increase of up to 1.6%. The return on investment has been found to increase by 2% to 3%. The researchers note that patents for renewable energy technologies contribute significantly only to ROIC, whereas combustion technologies with mitigation potential and nuclear technologies positively influence all financial performance indicators of companies. The authors also advocate for further advancements in nuclear power technology, since a nuclear power plant is a powerful, stable, and low carbon energy source with a long operational lifespan.
However, it should be noted that investments in green energy typically involve long-term commitments and do not yield immediate financial returns. This study demonstrates that businesses prioritising social and environmental responsibility in their operations can eventually achieve significant profits.
Associate Professor, Faculty of Economics, HSE University
The development of green energy should be a priority for BRICS countries, and investing in infrastructure and improving legislation are crucial factors for an expansion of low-carbon technologies in the electric power industry.
See also:
HSE Researchers Determine Which Internet Users Are More Likely to Fact-Check
Researchers at HSE University examined the strategies employed by Russian internet users to verify unreliable information and the factors that motivate them to do so. The study found that more than half of users who encounter potentially false information online attempt to verify it by locating the original source. The likelihood of fact-checking is influenced by several factors, including age, place of residence, social status, information literacy skills, and the use of AI. The findings have been published in Monitoring of Public Opinion: Economic and Social Changes.
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.