Energy consumption, CO<SUB align="right">2 emission and economic growth: empirical evidence for Malaysia

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

Can we live within environmental limits and still reduce poverty? Degrowth or decoupling?

Economic development usually leads to increased energy consumption, which in turn will result in an increase in carbon emissions. To break the relationship between economic development and carbon emissions, scholars have turned their attention to the phenomenon of decoupling. In this paper, we studied the decoupling relationship between carbon emissions and economic growth of the equipment manufacturing industry in China from 2000 to 2014. We adapted the LMDI decomposition method, and we used the Tapio decoupling evaluation model to analyze our data. We found that the decoupling relationship between carbon emissions and economic growth of China’s equipment manufacturing industry is weak, which indicates the industry is experiencing faster economic growth than carbon emission growth. We found the economic output is the factor that has the strongest influence on the industry’s carbon emission, and energy consumption intensity has the strongest relationship with the decoupling of economic growth and carbon emission. The indicators of the industry’s decoupling-effort are all less than 1.0, which indicates that the industry is in the state of weak decoupling, and we also observed an annual decreasing trend in the industry’s indicators. Toward the end of this paper, we used the Grey forecasting model to predict the decoupling relationship between carbon emission and economic growth for 2015–2024, and we discussed the implications of our research.

PurposeThe purpose of this study is to investigate the dynamic relationship that exists between energy consumption, environmental pollution and per capita economic growth in Tanzania. The energy consumption is represented by electricity usage in kilowatt hours (kWh) per capita, while environmental pollution is represented by carbon emission per metric tons and economic growth by gross domestic product (GDP) per capita.Design/methodology/approachThis investigation is made based on the Environmental Kuznets Curve using time series annual data from 1975 to 2013 by applying the more robust causality technique of Toda and Yamamoto non-Causality test (1995), Impulse response and Variance Decomposition, Augumented and Dickey–Fueller test and Philips and Perron Test of unit root tests.FindingsEconomic growth rate (LGDP) and energy consumption per capita (LENGY), both being unidirectional, cause environmental pollution through carbon emission (LCO2) in Tanzania. Interestingly, after using impulse response, a significant and positive economic growth (GDP per capita) was found due to shocks from electricity per capita (energy consumption) and carbon emission (LCO2) with time. The Variance Decomposition suggested that the percentage of the variations due to shocks or innovations of economic growth (LGDP) and energy consumption (LENGY) to carbon emission is very high and significant, accounting to 46 and 41 per cent, respectively, in 10 years to come.Research limitations/implicationsThe study recommends that, in the future, the relationship be examined using super-exogeneity causality tests that takes into consideration the changes in policy or regime in contrast to Toda and Yamamoto. Furthermore, the addition of other variables such as fixed capital formation and labor force, which were not considered in this study, may result in strong correlation.Practical implicationsThe results imply that the government of Tanzania can adopt environment conservation and energy saving policies without affecting its economic growth. As a matter of fact, to put a stop to persistent environmental pollution in Tanzania, the energy saving policy should be put in place rather quickly. It is imperative that the government implements policies and strategies that ensure continuous economic growth without forsaking the environment.Originality/valueDespite the increase in carbon emissions, energy consumption and economic growth in Tanzania since 2000, to date, no previous work has been done to investigate their multivariate relationship. This is the first study that uses the Toda and Yamamoto non-Causality test, Impulse Response and Variance Decomposition Analysis to investigate a trivariate relationship of the variables mentioned above.

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.

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.

PurposeThe purpose of this paper is to examine the relationship among environmental pollution, economic growth and energy consumption per capita in the case of Pakistan. The per capital carbon dioxide (CO2) emission is used as the environmental indicator, the commercial energy use per capita as the energy consumption indicator, and the per capita gross domestic product (GDP) as the economic indicator.Design/methodology/approachThe investigation is made on the basis of the environmental Kuznets curve (EKC), using time series data from 1971 to 2006, by applying different econometric tools like ADF Unit Root Johansen Co‐integration VECM and Granger causality tests.FindingsThe Granger causality test shows that there is a long term relationship between these three indicators, with bidirectional causality between per capita CO2 emission and per capita energy consumption. A monotonically increasing curve between GDP and CO2 emission has been found for the sample period, rejecting the EKC relationship, implying that as per capita GDP increases a linear increase will be observed in per capita CO2 emission.Research limitations/implicationsFuture research should replace the economic growth variable, i.e. GDP by industrial growth variable because industrial sector is major contributor of pollution by emitting CO2.Practical implicationsThe empirical findings will help the policy makers of Pakistan in understanding the severity of the CO2 emissions issue and in developing new standards and monitoring networks for reducing CO2 emissions.Originality/valueEnergy consumption is the major cause of environmental pollution in Pakistan but no substantial work has been done in this regard with reference to Pakistan.

Summary Cities, contributing more than 75% of global carbon emissions, are at the heart of climate change mitigation. Given cities' heterogeneity, they need specific low-carbon roadmaps instead of one-size-fits-all approaches. Here, we present the most detailed and up-to-date accounts of CO2 emissions for 294 cities in China and examine the extent to which their economic growth was decoupled from emissions. Results show that from 2005 to 2015, only 11% of cities exhibited strong decoupling, whereas 65.6% showed weak decoupling, and 23.4% showed no decoupling. We attribute the economic-emission decoupling in cities to several socioeconomic factors (i.e., structure and size of the economy, emission intensity, and population size) and find that the decline in emission intensity via improvement in production and carbon efficiency (e.g., decarbonizing the energy mix via building a renewable energy system) is the most important one. The experience and status quo of carbon emissions and emission-GDP (gross domestic product) decoupling in Chinese cities may have implications for other developing economies to design low-carbon development pathways.

A multi-factor efficiency perspective to the relationships among world GDP, energy consumption and carbon dioxide emissions

In 2021, the Chinese government announced the goal and vision of carbon peak and carbon neutralization. The proposal of "double carbon strategy" has an important impact on China’s economic development. In this context, in order to accelerate the green development of Liaoning economy and realize the decoupling between economic growth and carbon emission. Taking Liaoning Province as the research object, this paper uses Granger causality test to analyze the relationship between energy consumption, carbon emission and economic growth, and uses Tapio decoupling analysis method to study the change of decoupling state between carbon emission and economic growth from 2010 to 2019. It is found that there is a two-way Granger causality between carbon emission, energy consumption and economic growth. At the same time, the decoupling analysis shows that the decoupling of carbon emission in Liaoning Province is more significant, and the carbon emission intensity of economy has decreased. Finally, it puts forward countermeasures and suggestions that Liaoning Province should optimize the industrial structure and speed up the application of clean energy.

Analysis of the Dependence on Economic Growth in China to Energy Consumption

This study measures the relationship and dynamic impacts of economic growth and forested area on carbon dioxide (CO2) emissions in Malaysia. Time series data over the period of 1990 to 2016 were used by employing the dynamic ordinary least squared (DOLS) approach. The results of DOLS estimation indicate that the coefficient of economic growth is positive and significant with CO2 emissions, meaning that RM1 million increase in gross domestic product (GDP) is associated with an increase in CO2 emissions of 0.931 kilo tons. Instead, the long-run coefficient of forested area found negative and significant, which implies that declining one hectare of forested area (i.e., deforestation) has an impact of three kilo tons of CO2 emissions rise in Malaysia. Our study findings indicate that economic growth and deforested area have an adverse effect on Malaysia’s carbon emissions where GDP growth fosters carbon emissions at a faster rate. Thus, the effective implementation of policy measures and economic instruments including afforestation and reforestation, forest conservation, sustainable forest management, REDD+ (reducing emissions from deforestation and forest degradation plus) mechanism and other emission reduction mechanisms inter alia could be useful for reducing carbon emissions while decreasing deforestation and maintaining the long-term economic growth in Malaysia.

This study investigates the asymmetric cointegration and causal relationships between economic growth, carbon emissions, and energy consumption in the next eleven (11) countries over the period 1972–2013. The nonlinear autoregressive distributed lag (NARDL) bounds testing approach and nonpragmatic Granger causality tests are employed. This research’s empirical results have entrenched vital relationships that have significant policy implications. We affirm nonlinear cointegration among the variables in Bangladesh, Iran, Turkey, and Vietnam. The long-run asymmetric effect outcomes indicate a definite boom in economic growth, significantly increases carbon emission in Turkey, and a decline in Vietnam. Additionally, a positive shock to energy consumption significantly increases the carbon emission in Bangladesh, Iran, and Turkey, but a decrease in emissions in Vietnam. Findings from the Wald test reveal a long-run asymmetric effect between carbon emission and economic growth in Bangladesh, Iran, and Vietnam, and for Iran, an asymmetric short-run impact. Long-run and short-run asymmetric effects between carbon emission and energy consumption in Bangladesh and Iran. In terms of asymmetric causality results, bidirectional causality between carbon emission and economic growth was noted in Bangladesh and Turkey, and a unidirectional causality from economic growth to carbon emission in Egypt and South Korea. Energy consumption causes carbon emission in Bangladesh, Egypt, Pakistan, South Korea, and not vice versa. We determined a bidirectional asymmetric causality relationship between carbon emission and energy consumption in Vietnam and a unidirectional causality link from carbon emissions to Turkey’s energy consumption.

Analysis of the carbon emission driving factors and prediction of a carbon peak scenario——A case study of Xi'an city

In recent years, the global greenhouse effect caused by excessive energy-related carbon emissions has attracted more and more attention. In this paper, we studied the dynamic evolution of factors driving China's energy-related CO2 emissions growth from 2007 to 2015 by using energy consumption method and input-output analysis and used the IO-SDA model to decompose the energy carbon emissions. Within the research interval, the results showed that (1) on the energy supply-side, the high carbon energy represented by raw coal was still the main factor to promote the growth of energy-related CO2 emissions. However, the optimization of energy consumption structure is conducive to reducing emissions. Specifically, the high carbon energy represented by raw coal exhibited a downward trend in promoting the increment of energy-related CO2 emissions, while the clean energy represented by natural gas showed an upward trend in promoting the increment of CO2 emissions. It is worth noting that there is still a lot of room for optimization of China’s energy consumption structure to reduce emissions. (2) On the energy demand-side, the final demand effect is the main driving force of the growth of carbon emissions from fossil energy. Among them, the secondary industry plays a major role in the final demand effect. The "high carbonization" of the final product reflects the characteristics of China's high energy input in the process of industrialization. At the same time, since the carbon emission efficiency of the tertiary industry and the primary industry is better than that of the secondary industry, actively optimizing the industrial structure is conducive to slowing down the growth of carbon emission brought by the demand effect. (3) The input structure effect is the main restraining factor for the growth of energy carbon emissions, while the energy intensity effect has a slight driving effect on the growth of energy carbon emissions. The results show that China's "extensive" economic growth model has been effectively reversed, but the optimization of fossil energy utilization efficiency is still not obvious, and there is still a large space to curb carbon emissions by improving fossil energy utilization efficiency in the future.