The aim of this paper is to augment the existing literature on convergence of CO2 emissions, by adding carbon footprint per capita and ecological footprint per capita to the convergence debate. We use the residual augmented least squares regression to examine the stochastic convergence of the environmental indices in 27 OECD countries. Furthermore, in contrast to the previous studies which mainly used the conventional beta-convergence approach to examine conditional convergence, we use a beta-convergence method that is capable of identifying the actual number of countries that contribute to conditional convergence. The sigma-convergence of the environmental indices is also examined. The results suggest that conditional convergence exists in 12 countries for CO2 emissions per capita, 15 countries for carbon footprint per capita and also 13 countries for ecological footprint per capita. There is evidence for sigma-convergence for all the three indicators. The policy implications of the results are discussed in the body of the paper.
This paper examines the pattern of convergence in electricity intensity in a sample of 79 countries. We apply the residual augmented least squares regression to the convergence of energy intensity. This method has been used in the convergence of per capita energy consumption but not convergence of energy intensity. Furthermore, in contrast to the previous studies which mainly used the conventional beta convergence approach to examine conditional convergence, we use a beta convergence method that is capable of identifying the actual number of countries that contribute to conditional convergence. The sigma and gamma convergences of electricity intensity are also examined. In addition to the full sample of countries, we also examine convergence in African countries, Asian and Oceanic countries, American countries and European countries, separately. Convergences in OECD and non-OECD countries are also examined, separately. In the full sample, the results show convergence exists in 54% of the countries in the total sample. There is convergence in 65% of the African countries, 61% of the American countries, 43% of the Asian and Oceanic countries and 33% of the European countries. In terms of the regional classification, it is also observed that convergence exists for 58% of the non-OECD countries and 31% of the OECD countries. There is evidence for sigma convergence in all the blocs with the exception of European and non-OECD countries. With the exception of African countries, there is evidence for gamma convergence in all the countries and the various blocs. The policy implications of the results are discussed.
Most of the existing studies on stochastic convergence of emission have not adequately considered smooth structural changes. The primary purpose of this paper is to examine the validity of stochastic convergence at different income levels by recently proposed Fourier-based wavelet augmented Dickey-Fuller test with smooth shifts. Empirical results can be summed up as follows: (i) carbon emission per capita follows the stationarity process in 35 high-income countries, while carbon emission per capita follows the stationarity process in 27 upper-middle-income countries; (ii) besides, carbon emission per capita follows stationarity process in 30 lower-middle-income countries, while carbon emission per capita follows stationarity process in 13 low-income countries; (iii) in light of these findings, it can be said that stochastic convergence among different income groups is valid. The implications of the empirical findings for environmental planning and management are discussed in the body of the paper.
Wind energy is one of the renewable energy sources that has been touted to address the challenges of energy security and environmental degradation. This is only attainable if countries with substantial wind energy potential use it in significant proportion to satisfy their energy needs. One promising sector where wind energy can be employed to actualize this potential is the electricity sector. However, the current reality is that fossil fuels still dominate the energy profiles of most economies of the world, including the advanced economies, with wind renewable energy source accounting for a very small proportion of the energy mix. Germany is one of the few countries that offers promising opportunities in deploying wind energy to its full potentials. This study therefore explores the feasibility of substituting wind energy for nuclear energy and other fossil fuels using Germany as a country of focus. We use the ridge regression procedure to analyse yearly time series data for the German power sector that spans the period 1986 to 2018. With respect to output elasticities of the energy inputs, the results reveal that wind and natural gas have positive output elasticity estimates while the estimates for nuclear and coal are negative. We also found that all the inputs pairs have positive substitution elasticity estimates between them. With respect to wind energy, the highest substitutability estimate occurred with nuclear power which is followed by natural gas and then coal. The study recommended that policies such as granting of tax credit for wind energy technology, reduction in property taxes for wind power facilities, and allocation of fund for research and development (R&D) in wind energy technology are recommended to promote the use of wind energy in the economy.
Environmental degradation remains a huge obstacle to sustainable development. Research on the factors that promote or degrade the environment has been extensively conducted. However, one important variable that has conspicuously received very limited attention is energy innovations. To address this gap in the literature, this study investigated the effects of energy innovations on environmental quality in the U.S. for the period 1974 to 2016. We have incorporated GDP and immigration as additional regressors. Three indices comprising of CO2 emissions, ecological footprint and carbon footprint were used to proxy environmental degradation. The cointegration tests established long-run relationships between the variables. Using a maximum likelihood approach with a break, the results showed evidence that energy innovations significantly improve environmental quality while GDP degrades the quality of the environment, and immigration has no significant effect on the environment. Policy implications of the results are discussed in the body of the manuscript.
This study aims to contribute to the existing literature by looking at the influence of foreign direct investment on carbon dioxide emissions, carbon footprint, and ecological footprint. In order to realize the aim of this study, we have utilized the augmented mean group estimator, which is supported by common correlated effect mean group estimator in the analysis for 20 countries. The panel results reveal that foreign direct investment has no effect on environmental degradation indicators. The panel results further reveal that gross domestic product, energy consumption, and urbanization are the main contributors to environmental degradation. The results at country level show that foreign direct investment and urbanization increase pollution in the developing countries while they mitigate pollution in the developed countries. Moreover, gross domestic product and energy consumption increase pollution for both developed and developing countries, which includes China and the USA. The negative impact of foreign direct investment on environmental degradation in the developed countries can be explained on the basis that these countries have strong environmental regulations, which makes it almost impossible for dirty foreign industries to invest therein. From the output of this research, several policy recommendations are enumerated for the investigated countries.
The objective of this study is to examine the impact of natural gas consumption, output, and urbanization on CO2 emission in China and India for the period, 1965-2013. A cointegraton test, which provides for endogenously determined structural breaks, has been applied to examine the long-run relationship and to investigate the presence of environmental Kuznets curve (EKC) in the two countries. The presence of causal relationship between the variables is also investigated. The findings show that there is a long-run relationship in the variables and natural gas, real GDP, and urbanization have long-run positive impact on emission in both countries. There is no evidence for EKC in China and India. The findings further suggest that there is a long-run feedback relationship between the variables. The policy inferences of these findings are discussed.
The energy profile of India is dominated by fossil fuels, which create concerns over resource and environmental sustainability as fossil fuels are non-renewable and high carbon emitting. This scenario has necessitated the call for more renewables to replace fossil fuels to address resource and environmental sustainability concerns. This study, therefore, investigates the possibility of switching the fossil fuels of oil, coal, and natural gas for renewable energy in India. Using annual Indian data spanning more than four decades, a transcendental logarithmic production function based on a second-order Taylor Series approximation is estimated with the ridge regression technique. To achieve robustness, two equations with gross domestic product and adjusted net savings as regressands are estimated to proxy economic growth and sustainable development, respectively. The empirical results show substantial substitution possibilities between the fuels for both gross domestic product and adjusted net savings equations. The empirical findings show that India has the capacity to satisfy its energy needs through renewables to pursue not only economic growth but sustainable development. To actualize this potential, the Indian government should promote investment in renewables as this also promotes economic growth and development.
The objective of the study is to extend the existing literature by investigating the effects of foreign direct investment, gross domestic products and per capita and energy diversification on the nitrogen oxide emissions in Brazil, Russia, India, China and South Africa (BRICS) by using annual data during the period 1992-2019. As per our knowledge, the present study is a first of its kind to examine the impact of a new energy diversification index, based on Herfindahl-Hirschman framework on pollution. This study has adopted a new quantile regression augmented method of moments, which is capable of producing the total impacts of the independent variables across the entire distribution of nitrogen oxides emissions. The findings suggest that an increase in foreign direct investment leads to a decrease in nitrogen oxides emissions at the aggregate level and in both manufacturing and service sectors. We observe that foreign direct investment leads to an increase in nitrogen oxides emissions in the agricultural sector in most of the quantiles. Diversification towards renewable energy causes a decrease in nitrogen oxides emissions in most quantiles at aggregate level, agricultural and manufacturing sectors, whilst diversification leads to an increase in nitrogen oxides emissions in the service sector. The findings also suggest that GDP per capita leads to an increase in NOx emissions in all the quantiles. The study suggests the policy to use and attract more clean energy through foreign direct investment for towards the achievement of sustainable development.
This paper focusses on the examination of the fishing ground footprint in a group of 89 countries using fractional integration. The fishing ground footprint is one of the components of the ecological footprint. Nevertheless, it has not been investigated very much from an empirical viewpoint. We contribute to the existing literature on fishing ground footprint by using fractional integration techniques to examine the persistence of the series. Our results are very heterogeneous across countries though we find that most of the series are nonstationary and non-mean reverting, with most of the countries belonging to the upper-middle and high income levels. On the other hand, most of the 14.4% of countries that show a stationary pattern belong to lower-middle and low income countries. One of the implications of the study is that policies aimed at reducing fishing grounds footprint are likely to be effective in most of the investigated countries.
The primary objective of this paper is to investigate the isolated impacts of hydroelectricity consumption on the environment in Malaysia as an emerging economy. We use four different measures of environmental degradation including ecological footprint, carbon footprint, water footprint and CO2 emission as target variables, while controlling for GDP, GDP square and urbanization for the period 1971 to 2016. A recently introduced unit root test with breaks is utilized to examine the stationarity of the series and the bounds testing approach to cointegration is used to probe the long run relationships between the variables. VECM Granger causality technique is employed to examine the long-run causal dynamics between the variables. Sensitivity analysis is conducted by further including fossil fuels in the equations. The results show evidence of an inverted U-shaped relationship between environmental degradation and real GDP. Hydroelectricity is found to significantly reduce environmental degradation while urbanization is also not particularly harmful on the environment apart from its effect on air pollution. The VECM Granger causality results show evidence of unidirectional causality running from hydroelectricity and fossil fuels consumption to all measures of environmental degradation and real GDP per capita. There is evidence of feedback hypothesis between real GDP to all environmental degradation indices. The inclusion of fossil fuel did not change the behavior of hydroelectricity on the environment but fossil fuels significantly increase water footprint.
We investigate the role of military expenditure on emission in USA during the period 1960-2015. To achieve the objectives of this study, two measures of military expenditure are utilised, while several timeseries models are constructed with the gross domestic product (GDP) per capita, population, energy consumption per capita, non-renewable energy consumption per capita, renewable energy consumption per capita, urbanisation, trade openness and financial development serving as additional determinants of air pollution. We also use ecological indicator as an alternative measure of pollution. Moreover, different timeseries methods are utilised including a likelihood-based approach with two structural breaks. The output of this research concluded that all the variables are cointegrated. It is found that military expenditure has mixed impact on CO2 emissions. Real GDP per capita, energy consumption per capita, non-renewable energy consumption per capita, population and urbanisation increase CO2 emissions per capita in the long-run, while renewable energy consumption, financial development and trade openness reduce it. There is also evidence for the mixed role of military expenditure, when ecological footprint is utilised as the environmental degradation index. From the output of this research, few policy recommendations are offered for the examined country.
The main objective of this study is to investigate the influence of the globalisation (Trans-Pacific Partnership (TPP) agreement in particular) on air pollution in Malaysia. To achieve this goal, the Autoregressive Distributed Lag (ARDL) model, Johansen cointegration test and fully modified ordinary least square (FMOLS) methods are utilised. CO2 emission is used as an indicator of pollution while GDP per capita and urbanisation serve as its other determinants. In addition, this study uses Malaysia's total trade with 10 TPP members as an indicator of globalisation and analyse its effect on CO2 emission in Malaysia. The outcome of this research shows that the variables are cointegrated. Additionally, GDP per capita, urbanisation and trade between Malaysia and its 10 TPP partners have a positive impact on CO2 emissions in general. Based on the outcome of this research, important policy implications are provided for the investigated country.
The main objective of this paper is to estimate the interfuel substitution elasticities between hydropower and the fossil fuels of coal and natural gas used in the generation of electricity for Malaysia. Due to the violation of the assumption behind the ordinary least squares (OLS) method on account of the correlated error terms in the system of equations, the econometrics techniques of seemingly unrelated regression (SUR) was adopted to obtain the parameter estimates using dataset that covers the period 1988 to 2016. The main finding is that there exists substantial substitution possibility between hydropower and fossil fuels in the generation of electricity for Malaysia. CO2 emissions mitigation scenarios were also conducted to explore the possible effects of substituting fossil fuels for hydropower to generate electricity. The results show that switching from high carbon-emitting fuels to renewable energy such as hydropower will substantially reduce CO2 emission and assist the country towards achieving the carbon emissions reduction targets. Policy recommendations are offered in the body of the manuscript.
This study aims at exploring the impact of corruption control on energy efficiency in 60 countries categorized by income: lower middle (LMI), upper middle (UMI), and high (HI). Panel methodology was utilized taking the period of 2000-2017. As cross-sectional dependence is confirmed among the tested equations, the Pesaran (J Appl Econ 22(2):265-312, 2007) unit root test and the augmented mean group estimator proposed by Eberhardt and Teal (2010) were utilized to overcome this matter. The results in general indicate that the lower the corruption is, the more the energy efficiency for all income group economies. Moreover, renewable energy reduces energy efficiency in lower-middle income and high-income economies while its effect is positive in middle-income economies. In addition, the environmental Kuznets curve (EKC) found to be present in all income group economies. Lastly, causality relationships among energy efficiency, corruption, and GDP were present mostly in upper-middle income and high-income economies. From the results, it was recommended that the countries from all income groups should increase their corruption control for the purpose of enhancing energy efficiency.
The objective of this research is to examine the effects of stock market on air pollution in Malaysia during the period 1980-2017. To realize this aim, a nonlinear autoregressive distributed lag (ARDL) model is constructed. The short results in general revealed that the increase in stock markets will increase CO2 emissions and its significance increases in the long run. Moreover, the decline in stock market will reduce Malaysia's CO2 emissions but only in the long run. From the outcomes obtained, a number of policy recommendations were provided for the investigated country.
This paper aims to examine convergence of income inequality in 21 OECD countries using several empirical techniques. In particular, we have used a new panel stationarity test, which allows for structural changes and cross-sectional dependence to examine the stochastic convergence of income inequality. We also employed a time series approach, residual augmented least squares-Lagrange multiplier unit root test. The empirical results show evidence for absolute, conditional, and sigma convergence. The conditional convergence test results suggest that countries are converging, but conditional on the two structural factors-economic and population growth. The stochastic convergence test results indicate the existence of convergence at the country-specific level. The results further confirm the existence of convergent clubs among OECD countries.
An optimal energy mix is a sine qua non for sustainable development. However, the global energy mix is sub-optimally dominated by fossils which endangers energy security and threatens the attainment of sustainable development. Understanding the convergence of energy series can assist the transition path to optimal energy mix and sustainable development. Thus, research on the convergence of several energy series has gained prominence in recent years. This study extends this important niche in the literature on the convergence of natural resources and environmental series by examining the convergence in energy diversification along several dimensions for a panel of 79 lower-middle, higher-middle, and high-income countries. As a departure from the existing studies, the study employs a novel methodology that allows abrupt or smooth changes through the Fourier approximation of smooth breaks, while including factor structures to test for the presence of unit roots in the relative energy diversification series. The results provide evidence of convergence of the energy diversification series in the majority of the considered countries, with 90% of the sample demonstrating convergence. A disaggregated country analysis was conducted and the findings show that 93% of the lower-middle-income countries are converging, while 95% of the upper-middle-income countries and 87% of the high-income countries are converging. Policy implications of the findings are also discussed.
Despite being directly related to anthropogenic consumption and production, researchers have paid less attention to understanding the dynamics of non-methane volatile organic compounds. The primary objective of this research is to investigate the persistence of potential shocks to non-methane volatile organic compounds in 20 developed from 1820 to 2019 performing traditional unit root approaches and a newly developed Fourier quantile unit root test. Great portion of the empirical results obtained by traditional unit root tests reveal that the sectoral non-methane volatile organic compounds follow a non-stationary process, while the Fourier quantile unit root test indicate quite different results. The Fourier quantile test shows that non-methane volatile organic compounds are stationary in the United Kingdom, Ireland, Germany, France and Austria. In the other 15 countries, government interventions to reduce non-methane volatile organic compounds can have lasting effects and success. The inferences and policy outcomes of the empirical results are discussed in the main body of the paper.
In this study we examine the time-varying causal effect of the novel COVID-19 pandemic in the major oil-importing and oil-exporting countries on the oil price changes, stock market volatilities and the economic uncertainty using the wavelet coherence and network analysis. During the period of the pandemic, we explore such relationship by resorting to the wavelet coherence and gaussian graphical model (GGM) frameworks. Wavelet analysis enables us to measure the dynamics of the causal effect of the novel covid-19 pandemic in the time-frequency space. Regarding the findings displayed herein, we first found that the COVID-19 pandemic has a severe influence on oil prices, stock market indices, and the economic uncertainty. Second the intensity of the causality effect is stronger in the longer horizon than in the short ones, suggesting that the causality exercise continues. Our findings also provide evidence that the COVID-19 pandemic and oil price changes in oil-importing countries mirror those in oil-exporting countries and vice versa. Further, the COVID-19 pandemic has a profound immediate time-frequency effect on the US, Japanese, South Korean, Indian, and Canadian economic uncertainties. A better understanding of oil and stock market prices in the oil-importing and oil-exporting countries is vital for investors and policymakers, specially since the novel unprecedented COVID-19 crisis has been recognized among the most serious ever happened. Thus, the findings suggest that the authorities should strongly take efficient actions to minimize risk.