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

Most of the research articles on climate change study the relationships between economic growth, and, carbon dioxide (CO₂) emission or energy consumption separately for analyzing the impacts of economic growth and energy consumption on global carbon dioxide emissions. In this paper, the linkages among CO₂ emissions, Gross Domestic Product (GDP) growth and energy consumption are studied simultaneously using Data Envelopment Analysis (DEA). The time period considered for the study is 1980-2001. The results show that world in the year 1980 was the most efficient in achieving the highest economic growth, emitting least carbon dioxide for a given level of energy consumption for that year. The efficiency index reduced in the next 8 years, fluctuated with a declining trend for the next 7 years, and began to rise from 1996 till 2001. The model is further extended in this paper for technology forecasting to identify the links between energy consumption and carbon dioxide emissions for achieving projected levels of GDP under two different assumptions on efficiency index. It has been identified using the forecasting model that, when the carbon dioxide emissions are restricted to the levels emitted in the year 1990 and when the efficiency index for the year 2025 is assumed to be at the level registered for the year 1980 (highest value), the non-fossil energy consumption needed to meet the GDP level projected for 2025 will be much smaller (35.46 quadrillion Btu for the reference GDP) than the values actually recorded in the year 1990 (44.59). However, the non-fossil energy consumption in 2025 (118.8) increases much more than the actual recorded in the year 1990 when the efficiency index in 2025 is assumed to be at the level registered for the year 1990.     

Does financial development reduce CO2 emissions in Malaysian economy? A time series analysis

This study deals with the question whether financial development reduces CO₂ emissions or not in case of Malaysia. For this purpose, we apply the bounds testing approach to cointegration between the variables. We establish the presence of significant long-run relationships between CO₂ emissions, financial development, energy consumption and economic growth. The empirical evidence also indicates that financial development reduces CO₂ emissions. Energy consumption and economic growth add in CO₂ emissions. The Granger causality analysis reveals the feedback hypothesis between financial development and CO₂ emissions, energy consumption and CO₂ emissions and, between CO₂ emissions and economic growth.     

A decomposition analysis of CO2 emissions in the United States

This article decomposes the growth in US CO₂ emissions by state. Using the Logarithmic Mean Divisia Index (LMDI) method, we account for CO₂ emissions change in each state between 1990 and 2004. The change is decomposed into five effects: (a) emissions per unit of fossil fuel; (b) share of fossil fuel in total energy consumption; (c) energy intensity; (d) gross state product per capita and (e) population. Results show that for the past 15 years gains in the efficiency of energy use in the economy, the lowering share of fossil fuels in total energy consumption and lowering of emissions intensity of fuels all contributed to offsetting the effect of Gross Domestic Product (GDP) per capita and the population growth in carbon emission across the US.     

Economic growth and carbon emissions: evidence from CIVETS countries

ABSTRACT

This paper examines whether a long-run relationship exists between CO₂ emissions and selected variables: real gross domestic product per capita, inward stock of foreign direct investments, gross fixed capital formation, industry, value added and energy use per capita for Colombia, Indonesia, Viet Nam, Egypt, Turkey and South Africa countries in the period of 1989–2016. We used panel unit root testing, followed by panel cointegration tests and panel causality. The results clearly prove the existence of a bidirectional long-run causal relationship between all the variables except between CO₂ emissions and GDP and CO₂ emissions and GFCF. Major finding of the short-run causality analysis is that CO₂ emission in the short run does not result in changes of other variables. On the other hand, all variables except foreign direct investments (FDI) cause the changes in the CO₂ emissions, and there is a positive bidirectional causal relationship between GDP and FDI, between GFCF and FDI, and between GFCF and IVA. Finally, positive unidirectional causal relationship also exists, running from GDP to IVA, GDP to ENUSE, IVA to FDI and ENUSE to FDI.     

Norwegian Emissions of CO2 1987–1994 A Study of Some Effects of the CO2 Tax

Several countries have introduced taxes on fossil fuels with the aim of reducing atmospheric emissions, partly because of local environmental goals (SO₂, NO_x) and partly to participate in a global effort to reduce emissions of greenhouse gases. Many macroeconomic studies, based on both global and national models, have been made of how emissions can be reduced with the help of taxes and the consequent reduction in GDP following the introduction of such taxes. Norway has had a CO₂ tax for five years, thereby providing a unique opportunity to evaluate the effects of this tax on emissions. The paper provides a counterfactual analysis of energy consumption and emissions if no CO₂ taxes had been introduced, compared with the actual situation in which such taxes exist. The effect of a CO₂ tax on oil consumption, and thus CO₂ emissions is studied on the basis of partial economic models for various sectors of the Norwegian economy. The study indicates that the CO₂ tax has had an impact on CO₂ emissions in Norway.     

Revisiting the environmental kuznets curve hypothesis: evidence from the ASEAN-5 countries with structural breaks

This paper tests if the Environmental Kuznets Curve (EKC) hypothesis exists for ASEAN-5 countries in an annual sample data that covers 1971–2013, by utilizing Auto Regressive Distributed Lag (ARDL) methodology. The empirical findings give support for the EKC hypothesis for Thailand only, after considering the structural breaks. Furthermore, the paper tests the EKC hypothesis for a panel data of the ASEAN-5 by adopting the Pooled Mean Group (PMG) methodology. The results show that the long-run estimates provide no evidence for the EKC hypothesis. Finally, the paper examines the causality between the CO₂ emissions and GDP. For individual countries, bidirectional causality was found in the case of Thailand and Malaysia, plus unidirectional causality running from GDP and squared GDP to CO₂ emissions was found for Indonesia, but a unidirectional causality running from CO₂ emissions to GDP and squared GDP was found for the Philippines, however, no causality effect was found for Singapore. Furthermore, the pairwise Dumitrescu and Hurlin Panel Causality test show a bidirectional effect between CO₂ emissions and both GDP in addition to squared GDP.     

Renewable energy drivers: a panel cointegration approach

The expected gains from RES deployment to the reduction of carbon dioxide emissions (CO₂) and the cut-off of external dependence of electricity sources could be important. However, it is crucial to understand the determinants of RES growth to help policymakers drawing effective energy polices, involving a commitment of both citizens and governments. In this paper, we use novel panel econometric tools (taking into account structural breaks and cross-section dependence) and find evidence of nonstationary issues and cointegration issues between renewable energy production and its drivers (CO₂ emissions, GDP per capita, energy use and dependency). The results thus reveal that non-stationary issues should be attended, otherwise they could be biased. Using suitable estimators (DOLS, FMOLS) with two different data sets and different proxies and taking common factors into account by MG estimates, we find that there is no environmental concerns effect explaining the growth of renewables in European countries. However, national revenues, energy consumption (demand effect) and energy dependency have a positive impact on renewables deployment. Considering these results, economic assistance (subsidies) might be a mean to increase further the renewables deployment in EU countries and education about renewables deployment is needed.     

中国温室气体排放、能源消费与经济增长的实证分析

本文利用时间序列计量经济方法检验了中国的CO2排放量与能源消费、GDP、对外贸易、资本形成、人口等变量之间的关系。研究发现变量之间存在长期的均衡关系。长期内变量之间存在着双向因果关系;而在短期内,存在着GDP、能源消费、对外贸易、资本形成到CO2排放量等四种单向因果关系,其中CO2排放、能源消费、GDP和资本形成在各自的因果关系中所起的作用尤为显著。实证结果也发现能源消费对CO2排放具有加速影响趋势,对外贸易对CO2排放的影响也十分关键,而且变量之间存在着一个稳定的CO2排放方程。相应的政策建议是,中国应该实施低碳经济战略,加快低碳转型,发展低碳经济。     

Economic Growth and CO2 Emissions in the European Union

This paper examines the relationship between economic growth and CO₂ emissions in the European Union. A panel data analysis for the period 1981 to 1995 is applied in order to estimate the relationship between Gross Domestic Product (GDP) growth and CO₂ emissions in ten selected European countries. The analysis shows important disparities between the most industrialised countries and the rest. The results do not seem to support a uniform policy to control emissions; they rather indicate that a reduction in emissions should be achieved by taking into account the specific economic situation and the industrial structure of each EU member state.     

Do oil consumption and economic growth intensify environmental degradation? Evidence from developing economies

The purpose of this article is to empirically investigate the impact of economic growth, oil consumption, financial development, industrialization and trade openness on carbon dioxide (CO₂) emissions, particularly in relation to major oil-consuming developing economies. This study utilizes annual data from 1980 to 2012 on a panel of 18 developing countries. Our empirical analysis employs robust panel cointegration tests and a vector error correction model (VECM) framework. The empirical results of three panel cointegration models suggest that there is a significant long-run equilibrium relationship among economic growth, oil consumption, financial development, industrialization, trade openness and CO₂ emissions. Similarly, results from VECMs show that economic growth, oil consumption and industrialization have a short-run dynamic bidirectional feedback relationship with CO₂ emissions. Long-run (error-correction term) bidirectional causalities are found among CO₂ emissions, economic growth, oil consumption, financial development and trade openness. Our results confirm that economic growth and oil consumption have a significant impact on the CO₂ emissions in developing economies. Hence, the findings of this study have important policy implications for mitigating CO₂ emissions and offering sustainable economic development.     

Determinants of the global and regional CO2 emissions: What causes what and where?

Using the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and an unbalanced panel dataset of 128 countries covering 1990–2014, this study aims to examine the key impact factors (KIFs) of the global and regional carbon dioxide (CO₂) emissions and analyse the effectiveness of non-renewable and renewable energies. Given the potential cross-sectional dependence and slope heterogeneity, a series of econometric techniques allowing for cross-sectional dependence and slope heterogeneity is applied. The overall estimations imply that the KIFs at the global level are economic growth, followed by population size, non-renewable energy, and energy intensity in order of their impacts on CO₂ emissions; conversely, the KIFs at the regional level vary across different regions and estimators. The results also suggest that renewable energy can lead to a decline in CO₂ emissions at the global level. At the regional level, only for two regions (i.e., S. & Cent. America and Europe & Eurasia) renewable energy has a significant and negative effect on CO₂ emissions, which may be affected by the share of renewable energy consumption in the primary energy mix. Finally, the results indicate varied causality relationships among the variables across regions.

Abbreviations: AMG: Augmented mean group; BP: British Petroleum; BRICS: Brazil, Russia, India, China, and South Africa; CCEMG: Common correlated effects mean group; CD: Cross-section dependence; CIPS: Cross-sectionally augmented Im, Pesaran, and Shin; CO₂: Carbon dioxide; PS: Population size; D-H: Dumitrescu-Hurlin; EI: Energy intensity; EU: European Union; EU-5: Germany, France, Italy, Spain, and the United Kingdom; Europe & Eurasia, Europe and Eurasia; GDP: Gross domestic product; IEA: International Energy Agency; KIF: Key impact factor; LM: Lagrange multiplier; Mtoe, Million tonnes oil equivalent; NRE: Non-renewable energy; RE: Renewable energy; S. & Cent. America, South and Central America; STIRPAT: Stochastic Impacts by Regression on Population, Affluence, and Technology; VECM: Vector error correction model; WDI: World Development Indicators     

The carbon footprint of UK households 1990-2004: A socio-economically disaggregated, quasi-multi-regional input-output model

This paper presents a socio-economically disaggregated framework for attributing CO₂ emissions to people's high level functional needs. Based around a quasi-multi-regional input-output (QMRIO) model, the study, in theory, takes into account all CO₂ emissions that arise from energy used in production of goods and services to satisfy UK household demand, whether the emissions occur in the UK or abroad. Results show that CO₂ emissions attributable to households were 15% above 1990 levels in 2004, and that although absolute decoupling occurred between household expenditure and CO₂ during the UK's switch from coal to gas in the early 1990s, since then only slight relative decoupling is evident. The proportion of CO₂ that arises outside UK borders in support of UK consumption is rising, and reducing these emissions is particularly problematic in a global trading system. Investigation into the carbon footprint of different segments of the UK population shows wide variation: the segment with the highest carbon footprint emits 64% more CO₂ than the segment with the lowest. Results show that recreation and leisure are responsible for over one quarter of CO₂ emissions in a typical UK household in 2004. We conclude that expanding lifestyle aspirations are significant factors in driving household CO₂ emissions, but the study also emphasizes that attention must be paid to the infrastructures and institutions that result in considerable amounts of CO₂ being locked up in basic household activities through which people meet their everyday needs for subsistence, protection, and communication with family and friends. The findings highlight the sheer scale of the challenge facing UK policy-makers, and suggest that policies should be targeted towards segments of society responsible for the highest carbon footprints.     

Adoption of digital repositories for CO2 emissions reduction: the case of Korea

This study aims to estimate the potential economic benefits, energy and CO₂ emissions reductions when using trusted third-party digital repository (TTPR) services in one individual bank, and within the banking industry in Korea. First, the cost, benefit and net benefit of using TTPR services in the banking industry are estimated. Second, the net induced output effect is estimated. Third, based on an environmentally extended input–output analysis, CO₂ emissions reduction was estimated as 1924.32 tons in 2009 and the energy consumption reduction as 640.70 TOE. Fourth, the total economic benefit, which is the sum of the net induced output effect and economic value of CO₂ emissions reductions, is approximately $11.04 million. The findings demonstrate that energy consumption and CO₂ emissions reductions are meaningful enough to result in significant economic benefits. Therefore, the Korean government should promote the use of TTPR services in the entire industry.     

Quantification of the environmental impacts of road conditions in Brazil

This study evaluates the impacts of Brazilian highway conditions on fuel consumption and, consequently, on carbon dioxide (CO₂) emissions. For the purpose of this study, highway conditions refer to the level of highway maintenance: the incidence of large potholes, large surface cracks, uneven sections, and debris. Primary computer collected data related to the fuel consumption of three types of trucks were analyzed. The data were derived from 88 trips taken over six routes, each route representative of one of two highway conditions: better or worse. Study results are initially presented for each type of truck being monitored. The results are then aggregated to approximate the entire Brazilian highway network. In all cases, results confirmed environmental benefits resulting from travel over the better routes. There was found to be an increase in energy efficiency from traveling better roads, which resulted in lower fuel consumption and lower CO₂ emissions. Statistical analysis of the results suggests that, in general, fuel consumption data were significant at *P < 0.05, rejecting the null hypothesis that average fuel consumption from traveling the better routes is statistically equal to average fuel consumption from traveling the worse routes. Improved Brazilian road conditions would generate economic benefits, reduce dependency on and consumption of fossil fuels (due to the increase in energy efficiency), and reduce CO₂ emissions. These findings may have additional relevancy if Brazil needs to reduce carbon dioxide emissions to reach future Kyoto Protocol's emissions targets, which should take effect in January 2013.     

Empirical study on the determinants of CO2 emissions: evidence from OECD countries

This article empirically investigates the Environmental Kuznets Curve (EKC) for CO₂ emissions in the cases of 11 OECD countries by taking into account the role of nuclear energy in electricity production. The autoregressive distributed lag approach to cointegration is employed as the estimation method. Our results indicate that energy consumption has a positive impact on CO₂ emissions in most countries in the study. However, the impact of trade is not statistically significant. The results provide evidence for the role of nuclear power in reducing CO₂ emissions only in some countries. Additionally, although the estimated long-run coefficients of income and its square satisfy the EKC hypothesis in Finland, Japan, Korea and Spain, only Finland's EKC turning point is inside the sample period of the study, providing poor evidence in support of the EKC hypothesis.     

Decomposing the decoupling of CO2 emissions and economic growth in Brazil

This paper examines the occurrence of a decoupling between the growth rates in economic activity and CO₂ emissions from energy consumption in Brazil from 2004 to 2009. This decoupling was highlighted when economic activity and CO₂ emissions moved in opposite directions in 2009. More generally, we observe several periods of relative decoupling in Brazil, but not to the extent witnessed in 2009. To identify the determinants of emissions change, we develop a decomposition model based on a log-mean Divisia index (LMDI) framework. The results indicate that the carbon intensity and energy mix are the main determinant of emissions reduction in Brazil between 2004 and 2009. Modifications in the economy structure are also associated to emission mitigation in the period. Such evidence demonstrates similarities with events of decoupling registered for the interval 1980-1994 in Brazil. Finds from Brazil differ from observations in other countries in which improvement in energy intensity has been the most common determinant of emissions reduction.     

Environmental Kuznets Curve with Adjusted Net Savings as a Trade‐Off Between Environment and Development

The Environmental Kuznets Curve (EKC) hypothesises that emissions first increase at low stages of development then decrease once a certain threshold has been reached. The EKC concept is usually used with per capita Gross Domestic Product as the explanatory variable. As others, we find mixed evidence, at best, of such a pattern for CO₂ emissions with respect to per capita GDP. We also show that the share of manufacture in GDP and governance/institutions play a significant role in the CO₂ emissions–income relationship. As GDP presents shortcomings in representing income, development in a broad perspective or human well‐being, it is then replaced by the World Bank's Adjusted Net Savings (ANS, also known as Genuine Savings). Using the ANS as an explanatory variable, we show that the EKC is generally empirically supported for CO₂ emissions. We also show that human capital and natural capital are the main drivers of the downward sloping part of the EKC.     

Carbon dioxide emissions and interregional economic convergence in China

This paper examines the effect of carbon dioxide (CO₂) emissions on economic convergence among Chinese provinces from 1998 to 2012 using the framework of environmental total factor productivity (ETFP). We modify the standard β-convergence model to incorporate undesirable outputs such as CO₂ emissions. The bootstrap method is subsequently applied to estimate the values of ETFP, and the system generalized method of moments (GMM) estimator is employed to test for convergence. The results indicate that there is imperfect interregional economic convergence in China, which is supported by gross domestic product (GDP) and CO₂ emissions. However, the convergence process is inefficient due to the ‘catching up’ convergence trend of per capita CO₂ emissions in China. This paper also finds that the variation in the capital stock and labour does not support the hypothesis that all of the provinces can converge to a steady state.     

An analysis of China's climate policy using the China-in-Global Energy Model

The primary approach to address climate change in China has been the use of CO₂ intensity targets coupled with targets for low carbon energy deployment. We evaluate the impact of extending similar targets through 2050 on China's energy use profile and CO₂ emissions trajectory using the China-in-Global Energy Model (C-GEM). The C-GEM is a global computable equilibrium model that includes energy and economic data provided by China's statistical agencies, calibration of savings, labor productivity, and capital productivity dynamics specific to China's stage of development, and regional aggregation that resolves China's major trading partners. We analyze the combined impact of extending CO₂ intensity targets, implemented via a cap-and-trade program, and low carbon energy policies (directives for nuclear power expansion and feed-in tariffs for wind, solar, and biomass energy) through 2050. Although with the policy, simulated CO₂ emissions are around 43% lower in 2050 relative to a reference (No Policy) counterfactual, China's CO₂ emissions still increase by over 60% between 2010 and 2050. Curbing the rise in China's CO₂ emissions will require fully implementing a CO₂ price, which will need to rise to levels higher than $25/ton in order to achieve China's stated goal of peaking CO₂ emissions by 2030.     

中国工业部门碳排放与GDP脱钩因素影响力分析

基于Tapio脱钩模型,对2000．2008年间中国工业部门碳排放与能耗脱钩、能耗与GDP脱钩对碳排放与GDP脱钩影响力进行了实证研究。结果表明：中国工业部门在实现碳排放与GDP脱钩上取得比较显著的成绩;能耗脱钩影响力均值为正,能耗受经济驱动较小对碳排放与GDP脱钩做出了相当的贡献;排放脱钩影响力均值为负,碳排放受能耗驱动力较为明显,对工业部门碳排放与GDP脱钩产生了负向影响。为使中国工业部门在碳排放与GDP脱钩上取得更显著的效果,应加大能耗与GDP脱钩力度,同时政府应大力支持碳捕集利用与封存等低碳和零碳技术研发与应用,逐步改善碳排放与能耗整体挂钩的态势。