Is nuclear energy clean? Revisit of Environmental Kuznets Curve hypothesis in OECD countries

A transition towards the adoption of clean energy sources in electricity generation is essential to reduce the emission of greenhouse gases. The present study aims to examine the EKC hypothesis by taking into account nuclear energy in 18 OECD countries for the period 1995–2015. This study employs panel dynamic Generalised Method of Moments (GMM) and panel Fully Modified Ordinary Least Squares (FMOLS) to investigate the effects of electricity production from nuclear source, electricity production from non-renewables and trade openness on CO₂ emissions. The empirical findings suggest that EKC hypothesis is valid in OECD countries where nuclear energy plays a pivotal role in protecting the environment. On the contrary, non-renewable energy sources tend to increase CO₂ emissions. Our results support the notion that electricity generated by nuclear source leads to lower CO₂ emissions without retarding the long run growth in OECD countries. The findings also provide important policy insights and recommendations not only for OECD countries, but also for developing countries in designing appropriate energy and economic policies.     

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.     

A panel data heterogeneous Bayesian estimation of environmental Kuznets curves for CO2 emissions

This article investigates the Environmental Kuznets Curves (EKC) for CO₂ emissions in a panel of 109 countries during the period 1959 to 2001. The length of the series makes the application of a heterogeneous estimator suitable from an econometric point of view. The results, based on the hierarchical Bayes estimator, show that different EKC dynamics are associated with the different sub-samples of countries considered. On average, more industrialized countries show evidence of EKC in quadratic specifications, which nevertheless are probably evolving into an N-shape based on their cubic specification. Nevertheless, it is worth noting that the EU, and not the Umbrella Group led by US, has been driving currently observed EKC-like shapes. The latter is associated to monotonic income–CO₂ dynamics. The EU shows a clear EKC shape. Evidence for less-developed countries consistently shows that CO₂ emissions rise positively with income, though there are some signs of an EKC. Analyses of future performance, nevertheless, favour quadratic specifications, thus supporting EKC evidence for wealthier countries and non-EKC shapes for industrializing regions.     

Does urbanization increase pollutant emission and energy intensity? evidence from some Asian developing economies

This paper aims to investigate the effects of urbanization on pollutant emissions and energy intensity in selected Asian developing countries after controlling for the effects of disaggregated (renewable and non-renewable) energy consumption, trade liberalization, and economic growth. We use both linear and nonlinear panel data econometric techniques and employ recently introduced mean group estimation methods, allowing for heterogeneity and cross-sectional dependence. However, to check the robustness of our panel results, we also apply the autoregressive distributed lag (ARDL)-bound testing approach to country-level data. In addition, the relationship between affluence and CO₂ emissions is examined in the context of the Environmental Kuznets Curve (EKC) hypothesis. The estimation results identify the population, affluence, and non-renewable energy consumption as major factors in pollutant emissions in Asian countries. However, the results of the EKC hypothesis show that when countries achieve a certain level of economic growth, their emissions tend to decline. Whereas nonlinear results show that renewable energy, urbanization, and trade liberalization reduce emissions, linear estimations do not confirm these outcomes. Thus, substitution of non-renewable for renewable energy consumption, cautious and planned urbanization programs and more liberal trading regimes may be viable options for sustainable growth of these developing Asian economies.     

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.     

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.     

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.     

The impact of population on CO<Subscript>2</Subscript> emissions: evidence from European countries

This paper analyses the impact of population growth on CO₂ emissions in European Union countries. Traditionally, researchers have assumed a unitary elasticity of emissions with respect to population growth. In this study population is treated as a predictor in the model, instead of being included as part of the dependent variable (per capita emissions), thus relaxing the above-mentioned assumption of unitary elasticity. We also contribute to the existing literature by taking into account the presence of heterogeneity in the sample and considering a dynamic specification. The sample covers the period 1975–1999 for the current European Union members. Our results show that the impact of population growth on emissions is more than proportional for recent accession countries whereas for old EU members, the elasticity is lower than unity and non significant when the properties of the time series and the dynamics are correctly specified. The different impact of population change on CO₂ emissions for the current EU members should therefore be taken into account in future discussions of climate change policies within the EU.      

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.     

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.     

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.     

Stochastic convergence of per capita carbon dioxide emissions and multiple structural breaks in OECD countries

This research applies an innovative panel data stationarity testing procedure developed by Carrion-i-Silvestre et al. [Carrion-i-Silvestre, J.L., Barrio-Castro, T.D. and Lopez-Bazo, E., 2005. Breaking the panels: An application to the GDP per capita, Econometrics Journal 8, 159–175.], which has the advantage of recognizing multiple structural breaks and the presence of cross-section dependence in order to re-investigate the hypothesis that per capita carbon dioxide (CO₂) emissions stochastically converge for 21 OECD countries from 1950 to 2002. Remarkably, the evidence clearly indicates that the panel dataset of relative per capita CO₂ emissions is stationary after the structural breaks and cross-sectional dependence are introduced into the model. These findings offer strong policy implications for governments, regardless of whether they are in “convergent group” or “divergent group” countries. We also find that the structural breaks in the 1960s and over the 1970–1982 period are associated with time periods of fossil fuel becoming the main source of productivity, higher oil prices, and the development of nuclear power.     

The impact of urbanization on CO2 emissions: Evidence from developing countries

This paper analyzes the impact of urbanization on CO₂ emissions in developing countries from 1975 to 2003. It contributes to the existing literature by examining the effect of urbanization, taking into account dynamics and the presence of heterogeneity in the sample of countries. The results show an inverted-U shaped relationship between urbanization and CO₂ emissions. Indeed, the elasticity emission-urbanization is positive for low urbanization levels, which is in accordance with the higher environmental impact observed in less developed regions. Among our contributions is the estimation of a semi-parametric mixture model that allows for unknown distributional shapes and endogenously classifies countries into homogeneous groups. Three groups of countries are identified for which urbanization's impact differs considerably. For two of the groups, a threshold level is identified beyond which the emission-urbanization elasticity is negative and further increases in the urbanization rate do not contribute to higher emissions. However, for the third group only population and affluence, but not urbanization, contribute to explain emissions. The differential impact of urbanization on CO₂ emissions should therefore be taken into account in future discussions of climate change policies.     

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     

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.     

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.     

Distribution Dynamics of CO<Subscript>2</Subscript> Emissions

This paper uses nonparametric methods to examine the convergence in CO₂ emissions per capita on a sample of 100 countries for the period 1966–1996. Industrial countries show a convergence pattern. However, there is little evidence of convergence for the whole sample.     

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.     

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.     

Does energy‐related aid affect emissions? Evidence from a global dataset

Donor countries have been using international aid in the field of energy for at least three decades. The stated objective of this policy is to reduce emissions and promote sustainable development in the global South. In spite of the widespread use of this policy tool, very little is known about its effect on emissions. In this paper we perform an empirical audit of the effectiveness of energy‐related aid in tackling CO₂ and SO₂ emissions. Using a global panel dataset covering 128 countries over the period 1971–2011 and estimating a parsimonious model using the Anderson and Hsiao estimator, we do not find any evidence of a systematic effect of energy‐related aid on emissions. We also find that the non‐effect is not conditional on institutional quality or level of income. Countries located in Europe and Central Asia do better than others in utilizing this aid to reduce CO₂ emissions. Our results are robust after controlling for the environmental Kuznets curve, country fixed effects, country‐specific trends, and time‐varying common shocks.