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October 6, 2026
International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod Brings Together Scientists from Russia and Serbia
The International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod’ was held at the Nizhny Novgorod House of Scientists from September 23 to 26. The event was organised by HSE University–Nizhny Novgorod and the Nizhny Novgorod House of Scientists, with the participation of Sberbank and the Institute of Physics Belgrade. The symposium was held for the second time: the first conference took place in 2025 and attracted considerable interest from the academic community.
October 5, 2026
‘The Climate Transition Is Not Necessarily a Limitation for Business
Linara Khadimullina works in the field of low-carbon development. In an interview with the Young Scientists of HSE project, she spoke about why nature is not just a beautiful backdrop, her research on the role of sustainable corporate governance in reducing greenhouse gas emissions, and growing plants as a source of inspiration.
October 5, 2026
Africa, Youth, and Civic Dialogue: Public Diplomacy Discussed at HSE University
In late September, HSE University hosted a roundtable discussion titled Civil Society in African Countries and Youth Participation in Public Diplomacy. Representatives of non-governmental organisations from Ghana, Ethiopia, and Russia, along with students from HSE University’s Bachelor’s Programme in Public Administration, discussed how young people without official diplomatic status can influence relations between countries and how the nonprofit sector can remain sustainable amid declining grant funding.

 

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When green is not attractive: energy transition, capital inflows, and environmental outcomes in BRICS economies

SN Business & Economics. 2026. Vol. 6. Article 326.
Nurcan Kilinc, Warong M. M.

Green transitions are widely expected to attract cleaner capital and accelerate decarbonization; however, emerging-economy evidence increasingly challenges this assumption. This study examines the dynamic relationship between energy transition indicators and capital inflows in BRICS+ economies over the period 1996–2022, explicitly testing the “Green Haven” hypothesis under conditions of global uncertainty. Unlike much of the existing BRICS+ literature, which examines the energy–growth, foreign direct investment (FDI)–emissions, or innovation–environment nexus separately, this study jointly analyzes the Green Haven hypothesis, Pollution Haven hypothesis, Hicksian induced innovation mechanism, and uncertainty-driven carbon fallback effect within a unified dynamic framework. Using the Pooled Mean Group–Autoregressive Distributed Lag (PMG-ARDL) framework, the analysis is justified by the mixed integration order of the variables and the need to allow heterogeneous short-run dynamics while estimating common long-run relationships across countries. The results reject the Green Haven hypothesis, showing that renewable energy (RE) expansion does not significantly attract FDI (β = 0.036, p = 0.320). Instead, FDI Granger-causes carbon dioxide (CO₂) emissions, lending support to the Pollution Haven hypothesis. Conversely, the findings provide evidence for Hicksian induced innovation, as environmental degradation stimulates research and development (R&D) investment (β = 2.075, p < 0.01). Paradoxically, large-scale RE deployment appears to crowd out domestic innovation efforts (β = −0.019, p < 0.01). Moreover, global uncertainty shocks are found to reinforce carbon-intensive development trajectories. These results suggest that passive RE expansion is insufficient to enhance financial attractiveness or ensure environmental gains. Effective energy transition strategies require conditional green FDI frameworks, innovation-aligned investment policies, and resilience mechanisms to safeguard decarbonization objectives in emerging economies.

Research target: Economics and Management
Language: English
DOI
Text on another site
Keywords: Foreign Direct Investment (FDI)Pollution Haven Hypothesisenergy transitionBRICS economiesgreen haven hypothesisPMG-ARDL
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