The impact of trade openness on global carbon dioxide emissions: Evidence from the top ten emitters among developing countries

This study aims to analyze the relationship between carbon dioxide (CO₂) emissions, trade openness, real income and energy consumption in the top ten CO₂ emitters among the developing countries; namely China, India, South Korea, Brazil, Mexico, Indonesia, South Africa, Turkey, Thailand and Malaysia over the period of 1971–2011. In addition, the possible presence of the EKC hypothesis is investigated for the analyzed countries. The Zivot–Andrews unit root test with structural break, the bounds testing for cointegration in the presence of structural break and the VECM Granger causality method are employed. The empirical results indicate that (i) the analyzed variables are co-integrated for Thailand, Turkey, India, Brazil, China, Indonesia and Korea, (ii) real income, energy consumption and trade openness are the main determinants of carbon emissions in the long run, (iii) there exists a number of causal relations between the analyzed variables, (iv) the EKC hypothesis is validated for Turkey, India, China and Korea. Robust policy implications can be derived from this study since the estimated models pass several diagnostic and stability tests.     

Does globalization impede environmental quality in India?

Using annual data for the period 1970–2012, the study explores the relationship between globalization and CO₂ emissions by incorporating energy consumption, financial development and economic growth in CO₂ emission function for India. It applies Lee and Strazicich (2013) unit root test for examining the stationary properties of variables in presence of structural breaks and employs the cointegration method proposed by Bayer and Hanck (2013) to test the long-run relationships in the model. The robustness s of cointegration result from the latter model was further verified with the application of the ARDL bounds testing approach to cointegration proposed by Pesaran et al. (2001). After confirming the existence of conitegration, the overall long run estimates of the estimation of carbon emission model points out that acceleration in the process of globalization (measured in its three dimensions – economic, social and political globalizations) and energy consumption result in increasing CO₂ emissions, along with the contribution of economic development and financial development toward the deterioration of the environmental quality by raising CO₂ emissions over the long-run. This finding validates the holding of environmental Kuznets curve (EKC) hypothesis for the Indian context.     

Testing environmental Kuznets curve hypothesis: The role of renewable and non-renewable energy consumption and trade in OECD countries

This paper investigates the causal relationships between per capita CO₂ emissions, gross domestic product (GDP), renewable and non-renewable energy consumption, and international trade for a panel of 25 OECD countries over the period 1980–2010. Short-run Granger causality tests show the existence of bidirectional causality between: renewable energy consumption and imports, renewable and non-renewable energy consumption, non-renewable energy and trade (exports or imports); and unidirectional causality running from: exports to renewable energy, trade to CO₂ emissions, output to renewable energy. There are also long-run bidirectional causalities between all our considered variables. Our long-run fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) estimates show that the inverted U-shaped environmental Kuznets curve (EKC) hypothesis is verified for this sample of OECD countries. They also show that increasing non-renewable energy increases CO₂ emissions. Interestingly, increasing trade or renewable energy reduces CO₂ emissions. According to these results, more trade and more use of renewable energy are efficient strategies to combat global warming in these countries.     

Empirical investigation of environmental Kuznets curve for carbon emission in Morocco

This study explored the relationship among income, carbon emissions, energy consumption, and trade openness for Morocco from 1971 to 2011. The Johansen cointegration technique confirmed the long run relationship among the variables. The energy consumption deteriorated the environment quality and found to be true for both short run and long run. Foreign trade is beneficial for environment quality as foreign trade openness has negative impact on carbon emissions. This study did not confirm the environmental Kuznets curve hypothesis in long run. Furthermore, there is a strong one way causation from income to carbon emissions. Thus, Morocco can improve environment quality by reducing the carbon emissions and it will not disturb economic pace of the economy. Therefore, energy and trade policies should be made growth oriented. In the same way energy production and consumption has to be made environmental friendly.     

Economic growth,electricity consumption,urbanization and environmental degradation relationship in United Arab Emirates

The present study explores the relationship between economic growth, electricity consumption, urbanization and environmental degradation in case of United Arab Emirates (UAE). The study covers the quarter frequency data over the period of 1975–2011. We have applied the ARDL bounds testing approach to examine the long run relationship between the variables in the presence of structural breaks. The VECM Granger causality is applied to investigate the direction of causal relationship between the variables. Our empirical exercise reported the existence of cointegration among the series. Further, we found an inverted U-shaped relationship between economic growth and CO₂ emissions i.e. economic growth raises energy emissions initially and declines it after a threshold point of income per capita (EKC exists). Electricity consumption declines CO₂ emissions. The relationship between urbanization and CO₂ emissions is positive. Exports seem to improve the environmental quality by lowering CO₂ emissions. The causality analysis validates the feedback effect between CO₂ emissions and electricity consumption. Economic growth and urbanization Granger cause CO₂ emissions.     

Investigating the environmental Kuznets curve hypothesis in seven regions: The role of renewable energy

The aim of this research is to investigate how renewable energy consumption effects pollution and whether the relationship between income and pollution formulates the inverted U-shaped relationship which signals the existence of the environmental Kuznets curve (EKC). To realize the aims of this study, non-stationary panel data techniques were utilized to examine the seven selected regions. According to Pedroni and Fisher type cointegration tests, the variables were cointegrated. Moreover, the dynamic ordinary least square (DOLS) and the vector error correction model Granger causality revealed that renewable energy consumption has a significant negative effect on pollution in Central and Eastern Europe, Western Europe, East Asia and the Pacific, South Asia, and the Americas. However, the tests revealed that renewable energy consumption has no significant effect on pollution in the Middle East and North Africa and Sub-Saharan Africa. In addition, the results in general indicated that the existence of the EKC hypothesis is determined by the significance of the renewable energy consumption. Therefore, the EKC hypothesis was only found in the regions where their renewable energy has a significant correlation with pollution in both the short run and the long run. Furthermore, a number of policy recommendations were provided for the investigated regions.     

Does energy intensity contribute to CO2 emissions? A trivariate analysis in selected African countries

The present study investigates the dynamic relationship between energy intensity and CO₂ emissions by incorporating economic growth in environment CO₂ emissions function using data of Sub Saharan African countries. For this purpose, we applied panel cointegration to examine the long run relationship between the series. We employed the VECM Granger causality to test the direction of causality amid the variables.At panel level, our results validate the existence of cointegration among the series. The long run panel results show that energy intensity has positive and statistically significant impact on CO₂ emissions. There is also positive and negative link of non-linear and linear terms of real GDP per capita with CO₂ emissions supporting the presence of environmental Kuznets curve (EKC). The causality analysis reveals the bidirectional causality between economic growth and CO₂ emissions while energy intensity Granger causes economic growth and hence CO₂ emissions, while across the individual countries, the results differ. This paper opens up new insights for policy makers to design comprehensive economic, energy and environmental policy for sustainable long run economic growth.     

Investigating the environmental Kuznets curve (EKC) hypothesis by utilizing the ecological footprint as an indicator of environmental degradation

This study investigates the environmental Kuznets curve (EKC) hypothesis using a country’s ecological footprint as an indicator of environmental degradation. Ninety-three countries were examined, categorized by income. The fixed effects and the generalized method of moments results clearly showed an inverted U-shaped relationship between the ecological footprint and GDP growth, which represents the EKC hypothesis in upper middle- and high-income countries but not in low- and lower middle-income countries. This relationship only occurs in a stage of economic development in which technologies are available that improve energy efficiency, energy saving and renewable energy, which are not accessible for countries with low income due to their high cost. Moreover, energy consumption, urbanization, and trade openness increase environmental damage through their positive effect on the ecological footprint of most countries across all income groups. However, financial development reduces environmental degradation in lower middle-, upper middle- and high-income countries. This relationship confirms that loans from banks are primarily given to firms that establish investments in projects that are mostly environmentally friendly. From the results of this study, a number of recommendations can be provided for the investigated countries.     

Do nuclear and renewable energy improve the environment? Empirical evidence from the United States

The central focus of this article is to assess the dynamic effects of nuclear and renewable energy consumption on CO₂ emissions, for a given level of income and energy consumption. We apply an autoregressive distributed lag (ARDL) approach to cointegration to U.S. data from 1960 to 2010. We find that nuclear energy consumption indeed reduces CO₂ emissions in both the short- and long-run, while renewable energy consumption does only in the short-run. We also find that income increases CO₂ emissions in the long-run after showing the environmental Kuznets curve (EKC) initially in the short-run. Finally, energy consumption is found to have a negative impact on reducing CO₂ emissions in the short- and long-run.     

经济发展对环境质量的影响——环境库兹涅茨曲线国内外研究进展

“环境库兹涅茨曲线 (Environm ental Kuznets Curve)”是指环境破坏与收入水平之间成倒 U形曲线关系 ,即随着经济发展和收入水平的提高 ,环境质量先破坏后好转。 2 0世纪 90年代初 ,揭开了 EKC研究的序幕 ;之后涌现大量实证研究和理论解释模型的探索 ;近年来的研究在前人的基础上视野更加宽阔 ,更注重理论模型的完善。从实证研究、计量模型和解释理论等 3条线索回顾了近年来国内外的主要研究进展 ,认为现有研究在计量模型、数据处理、指标选取等方面虽然取得了巨大进展 ,但仍存在许多不足 ;EKC研究要得到更进一步发展必须突破这些局限     

Estimating the environmental Kuznets curve for Spain by considering fuel oil prices (1874–2011)

We perform a structural analysis on an environmental Kuznets curve (EKC) for Spain by exploiting long time series (1874–2011) and by using real oil prices as an indicator of variations in fuel energy consumption. This empirical strategy allows us to both, capture the effect of the most pollutant energy on carbon dioxide (CO₂) emissions and, at the same time, preclude potential endogeneity problems derived from the direct inclusion of fuel consumption in econometric specification. Knowing the extent to which oil prices affect CO₂ emissions has a straightforward application for environmental policy. The dynamics estimates of the long and short-term relationships among CO₂, economic growth and oil prices are built through an autoregressive distributed lag (ARDL) model. Our test results support the EKC hypothesis. Moreover, real oil prices are clearly revealed as a valuable indicator of pollutant energy consumption.     

CO2, economic growth,and energy consumption in China's provinces: Investigating the spatiotemporal and econometric characteristics of China's CO2 emissions

This study addresses the spatiotemporal variations at play in China's CO₂ emissions, based on an estimation of emission levels in the period 1995–2012 and an provincial analysis of the relationship of CO₂ emissions to economic growth and energy consumption. Using a series of econometric models and data on the combustion of fossil fuels and cement manufacturing, the study first estimated CO₂ emission levels during the study period, exploring their spatiotemporal pattern. The results indicate that both China's total and its per capita CO₂ emissions have increased significantly over the study period, with both measures evidencing a similar evolution (albeit one that is characterized by noticeable regional discrepancies at the provincial level and which displays properties of convergence). From a geographical perspective, we found both total and per capita CO₂ emissionsto be higher in China's eastern region than in the country's central and western regions. Panel data analysis was subsequently undertaken in order to quantify the dynamic casual relationship between economic growth, energy consumption, and CO₂ emissions. The empirical results indicated that the variables were in fact cointegrated and exhibited a long-run positive relationship. The results of further Granger causality tests indicated the existence of a bidirectional positive causality between economic growth and energy consumption, as well as between energy consumption and CO₂ emissions, and a unidirectional positive causality running from economic growth to CO₂ emissions. The findings of this study suggest that China is, in the long run, dependent on carbon energy consumption for its rapid economic growth, a dependency which is the cause of considerable increases in CO₂ emissions. China should therefore make greater efforts to develop low-carbon technologies and renewable energy, and improve energy efficiency in order to reduce emissions and achieve green economic growth.     

Environmental Kuznets Curve hypothesis and the role of globalization in selected African countries

The present study incorporates globalization and energy intensity into the CO₂ emissions function and investigates the presence of Environmental Kuznets Curve (EKC) in 19 African countries for the time period of 1971–2012. We have applied the ARDL bounds testing approach for cointegration to examine the long run relationship in the variables. Our results confirmed the presence of cointegration between the series in Africa, Algeria, Angola, Cameroon, Congo Republic, Ghana, Kenya, Libya, Morocco, Nigeria, South Africa, Sudan, Tanzania, Togo, Tunisia, Zambia and Zimbabwe. The results indicated the positive effect of energy intensity on CO₂ emissions in Africa, Algeria, Angola, Cameroon, Congo Republic, Ghana, Kenya, Libya, Morocco, Nigeria, South Africa, Sudan, Togo, and Tunisia while energy intensity declines CO₂ emissions in the case of Zambia and Zimbabwe. Globalization decreases CO₂ emissions in Africa, Angola, Cameroon, Congo Republic, Egypt, Kenya, Libya, Tunisia and Zambia but increases CO₂ emissions in Ghana, Morocco, South Africa, Sudan and Tanzania. The EKC exists in Africa, Algeria, Cameroon, Congo Republic, Morocco, Tunisia and Zambia but U-shaped relationship is found between economic growth and CO₂ emissions in Sudan and Tanzania.     

Change in cereal production caused by climate change in Malaysia

This study attempts to estimate the effects of climate change variables, such as average temperature, CO₂ emissions and average rainfall, on cereal production in Malaysia from 1969 to 2018. After preliminary tests on time series data, we employed a novel autoregressive distributed lag (ARDL) method known as the dynamic ARDL simulations technique. The results showed that a long-run co-integration relationship exists between cereal production and climatic and non-climatic factors. All climate variables have a negative impact on cereal yield, while energy consumption and cultivated land have a positive effect on cereal yield in the short- and long-run. Granger causality analyses also showed that a unidirectional causality link exists between rainfall and temperature with cereal production and between CO₂ emissions and cereal production. Energy consumption, as a proxy for technology, has a one-way Granger cause with cereal production. The results of the dynamic ARDL simulations suggest that cereal yield was most sensitive to CO₂ emissions, rainfall and temperature. In the long run, a 1% increase in temperature is associated with a 2.87% and 3.52% decrease in general and predicted estimates of cereal production, respectively. The dynamic ARDL simulations methodology provides a better understanding of the variability of cereal production in Malaysia as a result of climate change.     

Moving forward socio‐economically focused models of deforestation

Whilst high‐resolution spatial variables contribute to a good fit of spatially explicit deforestation models, socio‐economic processes are often beyond the scope of these models. Such a low level of interest in the socio‐economic dimension of deforestation limits the relevancy of these models for decision‐making and may be the cause of their failure to accurately predict observed deforestation trends in the medium term. This study aims to propose a flexible methodology for taking into account multiple drivers of deforestation in tropical forested areas, where the intensity of deforestation is explicitly predicted based on socio‐economic variables. By coupling a model of deforestation location based on spatial environmental variables with several sub‐models of deforestation intensity based on socio‐economic variables, we were able to create a map of predicted deforestation over the period 2001–2014 in French Guiana. This map was compared to a reference map for accuracy assessment, not only at the pixel scale but also over cells ranging from 1 to approximately 600 sq. km. Highly significant relationships were explicitly established between deforestation intensity and several socio‐economic variables: population growth, the amount of agricultural subsidies, gold and wood production. Such a precise characterization of socio‐economic processes allows to avoid overestimation biases in high deforestation areas, suggesting a better integration of socio‐economic processes in the models. Whilst considering deforestation as a purely geographical process contributes to the creation of conservative models unable to effectively assess changes in the socio‐economic and political contexts influencing deforestation trends, this explicit characterization of the socio‐economic dimension of deforestation is critical for the creation of deforestation scenarios in REDD+ projects.     

Environmental Kuznets curve estimation for NO2 emission: A case of Indian cities

Interaction between environmental degradation and economic growth is a growing matter of interest among policymakers. Here we have estimated environmental Kuznets curve (EKC) for 139 Indian cities considering NO₂ emissions. Study has been done for 2001–2013, and the data have been segregated by residential and industrial areas, and as well as low, medium, and high income areas. By virtue of different forms of EKC being found, policy level decisions have been designed. Moreover, non-rejection of EKC hypothesis reemphasized the impact of growth catalyzing economic policy decisions on environment.     

Estimation of environmental Kuznets curve for SO2 emission: A case of Indian cities

Interaction between environmental degradation and economic growth is a growing matter of interest among policymakers. Here we have estimated Environmental Kuznets Curve (EKC) for 139 Indian cities considering SO₂ emissions. Study has been done for 2001–2013, and the data have been segregated by residential and industrial areas, and as well as low, medium, and high income areas. By virtue of different forms of EKC being found, policy level decisions have been designed. Moreover, non-rejection of EKC hypothesis reemphasized the impact of growth catalyzing economic policy decisions on environment.     

EKC and the income elasticity hypothesis Land for housing or land for future?

This paper investigates the relationships between land consumption and per capita gross domestic product (GDP) for a panel of 20 Italian regions over the period 1980–2010. As proxy of land consumption, it uses the supply of new housing, being residential construction the main cause of soil sealing. To test this hypothesis it runs a panel data regression model. In the considered period, results show the existence of an inverted EKC whereas, on a longer period, a N-shaped curve may be inferred. Contrary to the EKC hypothesis, both fixed effect and random effect model estimates show that higher income does not induce greater environmental awareness or, in different words, that the income elasticity hypothesis holds for housing demand rather (or more) than for environment. According to these results, considering the specificity of the resource under consideration, the paper claims for a shift from market to public policy. A tighter urban planning and a higher “environmental” property taxation could be efficient strategies to combat land consumption.     

Does income growth relocate ecological footprint?

The aim of this paper is to investigate whether countries tend to relocate their ecological footprint as they grow richer. The analysis is carried out for a panel of 116 countries by employing the production and import components of the ecological footprint data of the Global Footprint Network for the period 2004–2008. With few exceptions, the existing Environmental Kuznets Curve (EKC) literature concentrates only on the income-environmental degradation nexus in the home country and neglects the negative consequences of home consumption spilled out. Controlling for the effects of openness to trade, biological capacity, population density, industry share and energy per capita as well as stringency of environmental regulation and environmental regulation enforcement, we detect an EKC-type relationship only between per capita income and footprint of domestic production. Within the income range, import footprint is found to be monotonically increasing with income. Moreover, we find that domestic environmental regulations do not influence country decisions to import environmentally harmful products from abroad; but they do affect domestic production characteristics. Hence, our findings indicate the importance of environmental regulations and provide support for the “Pollution Haven” and “Race-to-the-Bottom” hypotheses.     

Environmental Kuznets curve for CO2 emissions in China: A spatial panel data approach

Different from previous studies which mainly focused on conventional estimation techniques, this paper examines the CO₂ EKC hypothesis of China using a spatial panel data model to avoid the coefficient estimation error covering the period of 1997–2012. Furthermore, a comparative analysis of the turning points between the non-spatial panel model and spatial panel model is conducted. The results show that the relationship between economic growth and CO₂ emissions shapes as an inverted-N trajectory. Spatial spillovers effects are confirmed to affect the shape of the CO₂ environmental Kuznets curve. There exists an apparent block distribution in spatial structure of China's provincial CO₂ emissions. Specifically, CO₂ emissions have a relatively sharp increase from the eastern regions to the central and the western regions of China. It has also been found that urbanization and coal combustion are main factors on increasing CO₂ emissions. While the trade openness contributes to slight decrease in CO₂ emissions. The government should make targeted carbon-reduction policies for CO₂ emission reduction.