Search

The research investigates the relationship between intelligence quotient (IQ) and environmental degradation, aiming to understand how cognitive abilities influence environmental outcomes across different nations and time periods. The objective is to examine the impact of intelligence quotient (IQ) on environmental indicators such as carbon emissions, ecological demand, and the Environmental Kuznets Curve (EKC), seeking insights to inform environmental policy and stewardship. The study utilizes statistical techniques including Ordinary Least Squares (OLS), Two Stage Least Squares (2SLS), and Iteratively Weighted Least Squares (IWLS) to analyze data from 147 nations over the years 2000–2017. These methods are applied to explore the relationship between IQ and environmental metrics while considering other relevant variables. The findings reveal unexpected positive associations between human intelligence quotient and carbon emissions, as well as ecological demand, challenging conventional notions of "delay discounting." Additionally, variations in the Environmental Kuznets Curve (EKC) hypothesis are identified across different pollutants, highlighting the roles of governance and international commitments in mitigating emissions. The study concludes by advocating for the adoption of a "delay discounting culture" to address environmental challenges effectively. It underscores the complex interactions between intelligence, governance, and population dynamics in shaping environmental outcomes, emphasizing the need for targeted policies to achieve sustainability objectives. • The study examines how intelligence quotient (IQ) relates to environmental outcomes globally. • It employs OLS, 2SLS, and IWLS to analyze 147 nations' data from 2000 to 2017. • The finding shows unexpected positive links between IQ and carbon emissions, challenging traditional assumptions. • The study also Identifies EKC variations by pollutant, emphasizing governance and international commitments in emission reduction. • The policy implications suggest an adoption of a "delay discounting culture" for effective environmental policy, stressing intelligence and governance interactions in sustainability. [ABSTRACT FROM AUTHOR]

In the context of sustainable development, this study investigates the intricate dynamics among good governance, renewable energy investment, and green finance in BRICS nations. The aim of the study is to assess how green finance and governance effectiveness moderate the impact of renewable energy investment on CO 2 emissions. Utilizing the Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) model, a meticulous analysis spanning two decades was conducted to unravel the relationships among key variables and CO 2 emissions. The findings underscore a nuanced interplay where renewable energy investments, synergized with robust governance and strategic green finance, significantly mitigate CO 2 emissions, contributing to sustainable economic development. However, the study reveals non-linear relationships, highlighting the necessity for optimal allocation and strategic planning to maximize environmental benefits. In the short-run, a government effectiveness policy threshold that should be attained in order for renewable energy investment to reduce CO 2 emissions is provided. In the long-run, the negative responsiveness of CO 2 emissions to renewable energy investment is further consolidated by green finance. Moreover, enhancing renewable energy investment in the long run is positive for environmental sustainability. It follows that policy makers should tailor policies aimed at enhancing renewable energy investment in the long-run as well as complementing renewable energy investment with green finance in the long-run in order to ensure environmental sustainability by means of reducing CO 2 emissions. Policymakers in BRICS nations are urged to strengthen governance structures, promote renewable energy investments, leverage green finance, foster public-private partnerships, adopt a holistic approach, and address non-linear effects to accelerate the transition to a low-carbon economy. • The study investigates linkages among governance, renewable energy investment, and green finance. • The study uses the Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) model. • Renewable energy investments, with robust governance and strategic green finance, mitigate CO 2 emissions. • The study reveals non-linear relationships, highlighting the necessity for optimal allocation and strategic planning. • Policy implications are discussed. [ABSTRACT FROM AUTHOR]