Energy consumption, carbon dioxide emissions, information and communications technology, and gross domestic product in Iranian economic sectors: A panel causality analysis

Energy consumption is a crucial driver for economic development, improving the quality of life of the population of a country. This study attempts to contribute to the discussion by employing a systemic approach and methodology to examine the relationship between energy consumption (EC), gross domestic product (GDP) and carbon dioxide emissions (CO2) in Ecuador using time series from 1990 to 2018 with a mixed methodology (quantitative and qualitative). The energy balance and the enlarged Kaya identity are utilised to quantify the environmental impact of human activities. Furthermore, correlational cointegration and Granger causality tests are used to analyse the long-term and short-term relationships between variables in different sectors. The results reveal that there is no Granger causality between the variables in the agriculture and transport sectors, but there are unidirectional causality relationships in the industry and services sectors. In the industry sector, the study finds that EC Granger causes GDP (Wald test p value = 0.0038) and CO2 Granger causes GDP (Wald test p value = 0.0433). In the services sector, GDP Granger causes CO2 (Wald test p value = 0.0075), and EC Granger causes CO2 (Wald test p value = 0.0122), reinforcing the loop between GDP and CO2 in both the sectors. The analysed relationships help to inform policymakers about the likely impact of interventions. In addition, the study shows that Ecuador is in the initial phase of the Environmental Kuznets Curve, and provides strategies to manage sectoral energy consumption and valuable insights for other developing countries in Latin America seeking to pursue sustainable development.

This study aims to investigate the effects of information and communication technology (ICT), energy consumption, economic growth, and financial development on carbon dioxide emissions using 1993–2013 panel data from 12 Asian countries. The study employs a panel unit root test accounting for the presence of cross-sectional dependence and found that Internet usage is stationary and carbon dioxide emissions, energy consumption, gross domestic production (GDP), and financial development are first-difference stationary. The results form Pedroni panel cointegration test confirms that the variables are cointegrated. The results of the cointegration test indicate that the ICT-energy-GDP-carbon dioxide emissions nexus has long-run equilibrium. Both energy consumption and GDP have significant, positive impacts on carbon dioxide emissions; energy consumption and GDP have an effect on carbon dioxide emissions growth. ICT has a significantly negative effect on carbon dioxide emissions; the promotion of ICT becomes one of the important strategies introduced to mitigate carbon dioxide emissions for various countries. Causality results show that energy consumption, GDP, and financial development cause more carbon dioxide emissions. Energy consumption, GDP, and carbon dioxide emissions cause ICT. GDP causes financial development, whereas energy consumption and GDP are interdetermined. The feedback hypothesis exists in the region; those countries need to develop alternative energy to replace fossil fuels. ICT does not threaten the environment and ICT policy can be seen as a part of carbon dioxide emissions reduction policy.

Climate change due to global warming is becoming a major global issue over the past few decades. The emission of carbon dioxide (CO2) and other greenhouse gasses cause global warming. Most carbon emissions come from energy sectors, whereas transportation, industrial, and residential sectors are among the chief contributors. The present study investigates the effect of fiscal policy instruments, economic development, and foreign direct investment (FDI) on the sectoral emissions in Belt and Road Initiative (BRI) countries. The data used in this study is taken from the World Development Indicators (WDI) for the period between 2000 and 2018. Dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) have been used to analyze the long-run impact of fiscal policy instruments, economic development, and FDI on CO2 emissions from transportation, energy, and industrial sectors. Furthermore, the pairwise Dumitrescu and Hurlin panel causality test was used to authorize the causal relationship among the variables under consideration. The results reveal that fiscal policy instruments, per capita gross domestic product, FDI, and CO2 emissions show a strong correlation in the industrial, electrical, and transportation sectors. Furthermore, it is shown that public spending is a more reliable tool to reduce CO2 emissions in the transportation and industrial sectors in the BRI region. This study provides useful information for policy-makers on taking preventive and corrective measures to reduce CO2 emissions in different sectors and promote sustainable development.

Population growth and trends are centrally important to the environment because it helps to determine the environmental impact of human activities. In this study, the World Bank database has been used. Here, carbon dioxide (CO2) emissions, and energy intensity (EI) are considered as environmental indicators. The population indicators are the proportion of the population aged 15-64 years, and the percentage of the urban population. The Gross Domestic Product (GDP) is considered a development indicator in a country. This study tries to identify the association between population environment and development. Correlation analysis has been employed to know association and Path analysis is used to determine the important factors for environmental impacts such as carbon dioxide (CO2) emissions. The result presents that the zero-order correlation exists among energy intensity (EI), the proportion of the population aged 15-64 (P15-64), urbanization (UR), gross domestic product (GDP) per capita (US$), total population (P) ) and carbon dioxide (CO2) emission in Bangladesh and India. It is observed that 8 paths for Bangladesh and 7 paths for India out of each 12 hypothesized paths are found to be statistically significant. In Bangladesh, the total effects of exogenous variables like as energy intensity (X1) and population aged 15-64 (X2) are observed negative direction on carbon dioxide emissions (X6) and the remaining variable like as urbanization (X3) is observed as positive direction on carbon dioxide emissions. However, in India total effects of these two exogenous variables population aged 15-64 (X2) and urbanization (X3) are observed positive direction on carbon dioxide emissions (X6) and the remaining variable like as energy intensity (X1) is observed negative direction on carbon dioxide emissions (X6). The total effects of endogenous variables like as GDP per capita (X4) show a negative direction on carbon dioxide emissions and population (X5) shows a positive direction on carbon dioxide emissions. The study demonstrates that CO2 emission is important for environmental impact in Bangladesh and India. There is a strong association between population, GDP per capita, energy consumption and urbanization and CO2 emission in Bangladesh and India. The factors of CO2 emissions play an important role in environmental degradation. Thus, attention should be focused on using low energy consumption, and proper urbanization, particularly on modern technology which assures fewer uses of CO2 emissions in Bangladesh and India.

Based on the Kuznets's environmental theory, we examine the effect on carbon dioxide (CO2) emission of gross domestic product (GDP), energy consumption, trade openness, and industrial structure in OPEC countries during 1974-2013, using the Full Modified Ordinary Least Square (FMOLS) method. We find that GDP, energy consumption, and industrial structure have positive effects on CO2 emission. The GDP squared, however, negatively affects CO2, although the effect is small. The positive effect of GDP but negative effect of GDP squared validates the environmental Kuznets curve for OPEC countries. In addition, we find that an increase in trade openness leads to decrease in CO2 emission. Using the panel vector error correction model (VECM) and Granger causality test, we confirm that long-run causality is supported for all of our equations. We also find bi-directional short-run causality between energy consumption and CO2 emission and between energy consumption and industrial structure. Moreover, we find one-way causality running from energy consumption to GDP, from CO2 emission to trade openness, from GDP to trade openness, and from GDP to emission.

Analysis of South Korea’s economic growth, carbon dioxide emission, and energy consumption using the Markov switching model

Carbon dioxide emissions, energy consumption, economic growth, and foreign direct investment: Causality analysis for Sub-Saharan Africa

This study empirically analyzes the long-term relationship between agricultural production and carbon dioxide (CO2) emissions in Azerbaijan using annual data covering the period of 1992-2014. Additionally, real income and energy consumption variables were included in the model in testing the existence of the environmental Kuznets curve (EKC) hypothesis. Autoregressive distributed lag (ARDL) method is undertaken to reveal the existence of the long-term relationship between the CO2 and its determinants. The ARDL mechanism shows that gross domestic product (GDP) and energy consumption have a positive and statistically significant effect on carbon dioxide emissions. However, agricultural production and the square of GDP have a negative impact on air pollution. Furthermore, when the coefficients of real GDP and squared GDP included in the model were examined to analyze the inverted-U-shaped relationship between economic growth and environmental pollution, the EKC hypothesis was confirmed to be valid. According to Toda-Yamamoto causality test results, there is a bidirectional relationship between GDP, the square of GDP, and carbon emissions. From energy consumption and agricultural value-added to CO2 emissions, a unidirectional Granger causality relationship was found. Ultimately, the findings suggest that policies and reforms that increase or support agricultural production will help lower the country's CO2 emissions level.

The main objective of this study is to examine the linkage between CO2 emissions, total factor productivity as a measure of income, information and communication technology (ICT), trade, financial development, and energy consumption in Tunisia from 1975 to 2014. To achieve this goal, the autoregressive distributed lag (ARDL) with the break point method is performed. The results demonstrate the rejection of the Kuznets environmental curve (EKC) hypothesis by obtaining a higher value of the long-term total factor productivity parameter compared to the short-term one. Moreover, our result shows an insignificant impact of ICT on CO2 emissions as a measure of pollution. In addition, trade, financial development, and energy consumption affect negatively the environmental quality. As a result, Tunisian policymakers should enhance the total factor productivity, expand the information and communication technology, further develop the financial sector, enhance the share of renewable energy consumption, and reduce the energy consumption resulting in import and export goods. These goals will be achieved by improving Tunisia's technological and innovation capacity, enhancing the use of ICT in transport, building, and industry sectors considered as the most pollutant ones, and creating renewable energy projects.

This paper explored the energy–environment–economy (EEE) causal nexus of Pakistan, thereby reporting the causal determinants of the EEE nexus by employing the newly developed modified Peter and Clark (PC) algorithm. The modified PC algorithm was employed to investigate the causal ordering of energy consumption, CO2 emissions and economic growth across Pakistan’s domestic, industrial, transportation and agricultural sectors. An empirical comparison, i.e., following Monte Carlo simulation experiments demonstrates that the proposed modified PC algorithm is superior to the original PC proposition and can differentiate between true and spurious nexus causalities. Our results show that significant causality is running from energy consumption in industrial and agricultural sectors towards economic growth. There is no causal association between energy consumption and economic growth in the domestic and transportation sectors. On the other hand, causality runs from energy consumption in the transportation, domestic and industrial sectors towards CO2 emissions. It is concluded that energy consumption in industrial and agricultural sectors leads to economic growth alongside the associated CO2 emissions. On the other hand, the contribution of domestic and transportation sectors in economic growth is trivial with significant CO2 emissions. This paper provides novel empirical evidence of impacts of energy mismanagement at sectoral levels, economic output and environmental consequences; alongside policy recommendations for sustainable energy-based development on the national scale.

Better modeling of urbanization trends helps improve our understanding of the potential range of future energy demands and carbon dioxide emissions in developing countries and make informed response strategies. This paper extends the current analytical structure by integrating the population migration process from rural to urban areas with the energy system into a systematic framework, within which a link between urbanization and energy service demands through direct and indirect effects is built. Taking China as a study case, the results show that approximately 333 million people from rural areas are expected to migrate to urban areas toward 2050, resulting in the expansion of large-sized cities and the rapid growth of future energy service demands. Without significant technological improvements, urbanization will lead to more than double and triple the current energy consumption levels by 2050 in the building and transport sectors, respectively, while energy consumption growth in the industry sector will be the largest due to the rising demand for materials through the indirect effect. As a result, urbanization in China will cause more than double the total primary energy demand and an 82% increase in the carbon dioxide emissions by 2050, compared with 2013. In response, major mitigation measures and the role of each sector in the low carbon urbanization transition have been identified. Non-fossil fuel power generation is the top mitigation strategy, which can contribute 40% to the total mitigation potential, while power sector and industrial sector play a key role in realizing an earlier peak for the whole country. The total capital investment needed in each period will cost less than 2.5% of the total gross domestic product (GDP). Therefore, this work highlights the importance of understanding urbanization impact on energy system through applying an integrated population-energy-environment analytical framework and synthesizing the urbanization and long-term low carbon strategies in developing countries which are under rapid urbanization process.

Effectively addressing today’s energy challenges requires advanced technologies along with policies that influence economic markets while advancing the public good.

This study investigates the impact of agriculture, industry, and service sector value added in the gross domestic production (GDP) on carbon (CO2) emissions in Sri Lanka from 1965 to 2023. The study employed the Autoregressive Distribution Lagged (ARDL) bound test to investigate the study variables; long run relationship. The study results show that carbon emissions and value added in agriculture have negative significant association while value added in service and carbon emission has positive significant association in both short and long run. The results analysis does not support the EKC hypothesis in Sri Lanka. Furthermore, in this study, The EKC hypothesis contradicts in the sense that Sri Lanka moves from the secondary to the tertiary sector (Services) but CO2 emissions do not decrease but rather increase with rising income that is the new findings of the research. Thus, the implication of the research is that staying service economy is not the only way of reducing CO2 emissions because value added services in GDP are also associated with CO2 emissions. As well as other factors that affect CO2 emissions such as environmental awareness, technique effects, trade openness, and environmental regulations, are welcome to further researchers.

Transportation is a sector of increasing importance between energy efficiency and production. Increasing the energy efficiency of this sector and effectively reducing energy consumption, which forms the economic building blocks of countries, is considered a critical step for the protection of the natural environment. The role of transportation in energy saving and alternative energy technologies in the creation of environmentally friendly cities is the main focus of this study. The aim of the study is to examine the effects of energy efficiency in the transportation sector, to identify the factors affecting energy efficiency and to offer solutions to them. Within the scope of the study, five main criteria were examined: CO2 emissions, energy consumption, gross domestic product (GDP), crude oil barrel price and fuel consumption. These criteria have a wide range of impacts, from human health to the world economy. The relationships and importance levels between the criteria were weighted using the Analytic Hierarchy Process (AHP). As a result of the analysis, it was determined that CO2 emissions and energy consumption were the most important criteria. It has been shown that energy consumption in the transportation sector increases CO2 emissions by negatively affecting the environmental impacts, and at the same time, the increase in the barrel price of crude oil reduces CO2 emissions. It has been observed that today's technology is looking for alternative energy sources because fuel consumption affects energy consumption and CO2 emissions. A good gross domestic product indicates the existence of a green environment with low emissions and low energy consumption. As a result, it has been determined that energy consumption and CO2 emissions, which affect each other in parallel, are more important parameters for the transportation sector.

Do population density, economic growth, energy use and exports adversely affect environmental quality in Asian populous countries?