National Economics University (NEU) (Vietnamese: Đại học Kinh tế Quốc dân) is a reputable public research university in Hanoi, Vietnam. Founded in 1956, its history and influence have made it one of the leading universities in Economics, Public Administration and Business Administration in Vietnam.NEU is now chairing a network of more than 40 universities in Vietnam in economics and business administration. It is also a prestigious research and consultation center with its publications and consulting works to the government of Vietnam on policy making and to the business community on business development.Since its establishment, NEU has paid special attention to developing international academic cooperation. It has formed partnership relationship with over 100 institutions and organizations from 30 countries, including Australia, Belgium, Cambodia, Canada, China, France, Germany, Japan, Laos, Netherlands, South Korea, Taiwan, the United Kingdom, and the United States. The university has been involved in research projects in cooperation with large governmental organizations and international financial institutions such as the Japanese International Cooperation Agency (JICA), the Foundation of Vietnam Development Forum (VDF), the National Graduate Institute for Policy Studies (GRIPS), the World Bank (WB), the Asian Development Bank (ADB), the Department for International Development (DFID - UK), and Ausaid (Australia).Many of the university's alumni have a strong track record of success and hold important positions in public and private sectors. The current President of Vietnam, Nguyễn Xuân Phúc, is an alumni.
In this paper, we introduce two self-adaptive subgradient extragradient methods for solving non-monotone variational inequalities involving non-Lipschitz mappings in real Hilbert space. Under weaker conditions than the existing conditions, we investigate and present strong convergence theorems of the proposed algorithms. Our results extend and improve the studied results in the literature. Finally, we give an application to image restoration and some numerical experiments to demonstrate the efficiency of our proposed algorithms.
This paper examines the dynamic and long-term relationships between real gross domestic product (GDP), foreign direct investment (FDI), renewable energy consumption (RE), trade openness (TO), innovation (INN), and carbon dioxide emissions (CO2) in Slovakia. Using the Autoregressive Distributed Lag (ARDL) bounds testing approach to cointegration and error correction modelling, we explore whether clean energy and innovation can decouple growth from emissions in a small open European economy integrated into global value chains. Annual data are modelled with careful attention to lag selection, structural breaks, persistence, and endogeneity. We complement baseline ARDL with robustness checks (dynamic ARDL simulations, FMOLS/DOLS, and Toda–Yamamoto causality). The results template indicates: (i) a cointegrating relationship among the variables; (ii) in the long run, RE and INN are associated with lower CO2 intensity, while TO and FDI exert mixed effects depending on composition and technological spillovers; and (iii) short-run dynamics are dominated by adjustment toward equilibrium with moderate speed of correction. We discuss the policy implications for Slovakia's green transition in light of its EU climate targets.
The increasing urgency of climate change and the growing pressure to achieve sustainable development have intensified the need to understand the macroeconomic drivers of carbon emissions, particularly in emerging economies. In Thailand, rapid economic growth, expanding financial systems, and rising foreign investment have raised concerns about their environmental consequences.This study examines the nexus between financial development (FD), foreign direct investment (FDI), economic growth (EG), innovation (INNO), and carbon dioxide (CO2) emissions in Thailand over the period 1990–2024, using the autoregressive distributed lag (ARDL) bounds testing approach and Stata-based estimations. The ARDL methodology is employed to capture both long-run equilibrium relationships and short-run dynamic adjustments among the variables, even when integration orders differ. The bounds test confirms the existence of a stable long-run cointegrating relationship. Long-run estimates reveal that EG and FDI significantly increase CO2 emissions, reflecting dominant scale and production-composition effects. FD is also found to exacerbate emissions, suggesting that credit expansion has historically supported energy-intensive activities.In contrast, INNO reduces CO2 emissions, highlighting the role of technological progress and efficiency improvements in environmental sustainability. Short-run results indicate a significant negative error-correction term, confirming convergence toward the long-run equilibrium. Diagnostic and stability tests further validate the model's robustness.The findings underscore the importance of green FD, INNO-driven policies, and sustainable FDI strategies in achieving low-carbon growth in Thailand.
This paper examines the long- and short-run relationships between innovation (INNO), carbon dioxide emissions (CO2), real economic activity (GDP), foreign direct investment (FDI), trade openness (TRAD), and renewable energy (RE) in the Netherlands over 1990–2023 using the autoregressive distributed lag (ARDL) bounds testing framework. We specify a log-linear emissions model and, as a robustness check, an INNO-driven model to study feedback effects. The empirical strategy includes unit-root testing (ADF/PP/KPSS), structural break screening, ARDL bounds cointegration tests, long-run estimation with an error-correction representation, and extensive diagnostics (serial correlation, heteroskedasticity, and functional form) as well as stability tests (CUSUM/CUSUMSQ). While INNO, RE penetration, and trade structure are conceptually expected to reduce emissions through efficiency and substitution channels, scale effects from GDP and FDI can increase emissions unless accompanied by sufficiently strong technological upgrading. The study contributes country-specific evidence for the Netherlands, a small open economy with advanced INNO capacity and ambitious climate targets. Results sections include carefully formatted tables and figures templates ready for estimation. Rather than identifying generic emissions drivers, this study evaluates the effectiveness and stability of innovation-led decarbonization under intensified post-2020 climate policy regimes in the Netherlands.
Achieving sustained economic growth while reducing carbon emissions remains a central challenge for China's sustainability transition. Despite the rapid expansion of renewable energy capacity and innovation activity, carbon emissions continue to rise, suggesting that the environmental effects of technological progress and energy restructuring may be nonlinear and asymmetric. Understanding whether positive and negative changes in innovation and renewable energy exert different impacts on emissions is therefore fundamental for effective climate and development policies. This study examines the asymmetric relationships between innovation, renewable energy consumption, economic growth, trade openness, and CO2 emissions in China from 1990 to 2023. The analysis employs a Nonlinear Autoregressive Distributed Lag (NARDL) model as the base framework, allowing positive and negative shocks in innovation and renewable energy to affect emissions differently in the short and long run. Long-run cointegration is examined using the NARDL bounds testing approach, while dynamic multiplier functions trace adjustment paths following asymmetric shocks. Robustness is assessed through alternative lag specifications, a linear ARDL benchmark model, and extensive diagnostic and stability tests, including CUSUM and CUSUMSQ. The results reveal asymmetries. Positive shocks to innovation and renewable energy reduce CO2 emissions, while negative shocks increase emissions. Economic growth continues to raise emissions. Trade openness raises emissions in the short run. Policies should stabilize R&D, prioritize grid integration and storage, and strengthen links with the emissions trading system.
