Search

Global warming remains the most devastating environmental issue embattling the global economies, with significant contributions emanating from CO2 emissions. The continued rise in the level of greenhouse gas (GHG) emissions serves as a compelling force which constitutes the core of discussion at the recent COP26 prompting nations to commit to the net-zero emission target. The current research presents the first empirical investigation on the roles of technological advancement, demographic mobility, and energy transition in G7 pathways to environmental sustainability captured by CO2 emissions per capita (PCCO2) from 2000 to 2019. The study considers the additional impacts of structural change and resource abundance. The empirical backings are subjected to pre-estimation tests consisting of cross-sectional dependence, second-generation stationarity, and panel cointegration tests. The model estimation is based on cross-sectional augmented autoregressive distributed lag, dynamic common correlated effects mean group, and augmented mean group for the main analysis and robustness checks. The findings reveal the existence of EKC based on the direct and indirect effects of the components of economic growth. The indicators of demographic mobility differ in the direction of influence on PCCO2. For instance, while rural population growth negatively influences PCCO2 in the short-run alone, urban population growth increases PCCO2 in the short-run and long-run periods. Nonrenewable energy, information computer technology (ICT) imports, and mobile cellular subscriptions serve as positive predictors of PCCO2, while ICT exports and renewable energy moderate the surge in PCCO2. Policy implications that enhance environmental sustainability are suggested following the empirical verifications. [ABSTRACT FROM AUTHOR]

Today's economically developed nations are also among the most advanced in energy production and consumption. In particular, the widespread implementation of renewable energy sources and the plethora of technological advancements supporting long-term prosperity stand out. The present research examines how carbon dioxide (CO2) emissions, technological advancements, and renewable energy sources affect economic expansion. Research and development (R&D) expenses are considered a proxy for technological progress. The analysis quantified the interplay between the factors using annual data for the G7 countries from 1996 through 2020. We examine the association between our variables using panel unit root tests, Pedroni cointegration tests, ARDL coefficient estimations, and Dumitrescu and Hurlin causality tests. The Pedroni cointegration test indicated that the variables are cointegrated. According to the ARDL method of computation, increasing levels of CO2 emissions are beneficial to long-term economic growth. However, improvements in renewable energy and technology dampen economic expansion. The economy's expansion and increased carbon dioxide emissions have a reciprocal relationship. The Dumitrescu and Hurlin causality test shows a uni-directional chain of events from CO2 emissions to technological improvements, from economic growth to the use of renewable energy, and from consumption of renewable energy to technological advances. Based on our research results, investing in renewable energy consumption is still suggested for long-term sustainable development and environmental protection. Also, directing technological innovations to renewable energy resources and facilities to reduce costs and improve efficiency is suggested. [ABSTRACT FROM AUTHOR]

Currently, Pakistan is in a stage of urbanization and industrialization, raising its energy demand and supply and carbon dioxide emissions (CO2Es) due to the excessive use of fossil fuels. In meeting future demand and supply predictions, much emphasis should be given to both energy consumption and the level of inter-factor and inter-fuel substitution possibilities. Specifically, future outcomes for energy demand are more valid when production models contemplate substitution elasticity occurring during the period. To analyze the potential for little reliance on fossil fuels and diminish CO2Es, the present research has examined the potential for the substitution of energy and non-energy factors (i.e., natural gas, electricity, petroleum, labor, and capital) by using translog productions function over the period between 1986–2019. The ridge regression method is applied to evade the multicollinearity issue in the data. The model analyzes the output elasticity, substitution elasticity, technical progress, and carbon emission scenarios. The results show that the output elasticities are growing, presenting that the contribution of all factors adds to economic growth. The inputs between capital-petroleum, capital-electricity, labor-electricity, capital-natural gas, and natural gas-electricity are extreme substitutes. These substitutes are increasing capital growth and production sizes. The relative difference in technical progress shows a small positive change between 3–7% with convergence evident. Lastly, the investment scenarios under 5% and 10% investment in petroleum reduction are evidence that the CO2Es would reduce by 7.5 Mt and 10.43 Mt under scenario 1 and 7.0 Mt and 10.9 Mt under scenario 2. The results have broader suggestions for energy-conserving policies, particularly under the China–Pakistan Economic Corridor. [ABSTRACT FROM AUTHOR]

Digital development is critical for achieving coordinated regional economic growth, energy conservation, and emissions reduction, which makes it a viable method for achieving carbon neutrality and peaks. This study investigates the impact of the digital economy on urban total factor productivity and carbon emissions, as well as its mechanism, from 2011 to 2019 by developing a digital economy evaluation index system. We find that the growth of the digital economy can increase urban total factor productivity while lowering carbon emissions and also has a significant spatial spillover effect on regional economic growth, energy conservation, and emissions reduction. The main influencing mechanism is that the digital economy accelerates marketization by encouraging industrial structure upgrades and technological progress, which results in higher total factor productivity and lower energy consumption. In terms of the spatial distribution, the digital economy promotes total factor productivity more in the central and western regions and large cities and promotes carbon emission reduction less in the eastern regions and smaller cities. The findings extend the benefits of the digital economy beyond economic and social welfare benefits and serve as a model for achieving a win–win situation in terms of both economic growth and carbon emissions reduction. [ABSTRACT FROM AUTHOR]

As geographic limitation has gradually vanished, many economic activities occurred with apparent spillover on the neighboring regions. To study other social pressures on energy consumption considering spatial spillover effects, this paper constructs STIRPAT spatial model to investigate the relationship among energy intensity, foreign direct investment (FDI), economic growth, population scale, and technology progress in the case of 30 provinces in China over the period of 2001–2016. Spatial correlation test methodologies are applied, and STIRPAT spatial Durbin model (SDM) is preferred to describe the pushing-in and pushing-out effects among regions. We find that there is obvious spatial spillover of energy intensity; economic growth, industrial development, and population scale positively relate to energy intensity in local regions; technology progress is an effective way for energy conservation; the spillover effects of global domestic production (GDP), population size, and technology in adjacent regions are significant on local energy consumption; in China, FDI inflows into the local and neighboring regions negatively affect energy intensity, indicating that FDI would release the pressure of energy consumption. [ABSTRACT FROM AUTHOR]

Some empirical studies show that natural resources and physical capital are likely to be complements in the production process rather than substitutes. What is more, the assumption of substitutability in many theoretical papers leads to some counterfactual conclusions. This paper proposes a simple model of economic growth with complementarity between these two factors of production via energy production. We consider the equilibrium state of this model and derive the conditions necessary to maintain balanced growth of all macroeconomic variables. We also analyze the time to depletion of natural resources when these resources are the main energy source. [ABSTRACT FROM AUTHOR]

Energy and green innovation are important to a country's economic progress, but the externalities of increased pollution as a result of a rise in energy used and economic growth must not be overlooked. Within the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) framework, this study aims to check empirically the effect of environment-related technologies (ERT), coal consumption (CC), economic growth (EG), and population density (PD) on the consumption-based CO 2 emissions (CCO 2e) in the BRICS (i.e., Brazil, Russia, India, China, & South Africa), as with fast economic progress BRICS is facing problems of CO 2 emission. The econometric techniques of the cross-sectional dependence test, slope heterogeneity test, and second-generation panel unit root test were used to check the nature of the data. The available balance data over the period 1985–2018 were analyzed via Driscoll and Kraay and a dynamic common correlated effect mean group (DCCEMG). Long-term empirical findings show that ERT has a negative impact on the CCO 2e , while per capita GDP and CC have a positive impact on CCO 2e. Empirical evidence recommends that ERT is important for BRICS countries' long-term sustainability. It is suggested that policymakers should encourage ERT that help in curbing their CO 2 emanations. [ABSTRACT FROM AUTHOR]

Based on threshold regression models, this paper analyzes the effect of economic growth on energy intensity by using panel data from 21 developed countries from 1996 to 2015. Results show that a 1% increase in GDP per capita can lead to a 0.62–0.78% reduction in energy intensity, implying economic growth can significantly reduce energy intensity. The extent of the reduction in energy intensity varies depending on the economic development stages represented by key influencing factors including energy mix in consumption, urbanization, industrial structure, and technological progress. Specifically, the reduction in energy intensity due to economic growth can be enhanced with relatively more renewable energy consumption and more urban population until a threshold point, where the enhancement disappears. On the other hand, the extent of the energy intensity reduction due to economic growth can be weakened with relatively more tertiary industry activities and more research and development (R&D) investment in an economy until a threshold point, where the weakening cannot continue. However, compared to the early stages represented by the low ends of renewable energy consumption, urban population, tertiary industry activities, and R&D investment, the later stages represented by the high ends of these key factors after a threshold show the weakened effect of economic growth on the decline of energy intensity. Hence, when an economy is well-developed, policy makers are advised to put fewer expectations on the role of economic growth to reduce energy intensity, while pursuing relatively cleaner energy, greater urbanization, more tertiary industry activities, and advanced technologies. [ABSTRACT FROM AUTHOR]

We employ a non-parametric modelling technique to examine the time-varying impact of renewable and non-renewable energy consumption on economic growth. The specific nonparametric method that we employ is the local linear dummy variable estimation (LLDVE) method, which we apply to OECD and non-OECD panels for the period 1990 to 2015. While previous studies employing parametric models have recognised the existence of non-linearities and instability in the relationship between renewable (and non-renewable) energy consumption and economic growth, the LLDVE method has the advantage that it does not make any assumptions about functional form and, hence, is better able to approximate the non-linear relationship. Our estimates suggest that non-renewable energy consumption exerts a positive and significant impact on economic growth across OECD nations with the coefficient function exhibiting an upward trajectory over time. The impact of renewable energy consumption on economic growth, however, is statistically indistinguishable from zero in these countries for most of the study period. Both renewable and non-renewable energy consumption promote economic growth in non-OECD countries, suggesting that developing countries may play an important role in the transition process to renewables despite constraints in technical progress. [ABSTRACT FROM AUTHOR]