Transiting toward sustainable development: stochastic convergence of energy diversification using a newly constructed index.

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.

Mean reversion and convergence of ecological footprint in the MENA region: evidence from a fractional integration procedure.

This paper deals with the analysis of mean reversion and convergence of the ecological footprint (EF) in the MENA region. Using a long memory model based on fractional integration, we find that the results are very heterogeneous across countries depending on the assumptions made on the error term and the use of original versus logged data. Nevertheless, some conclusions can be obtained. Thus, mean reversion is decisively found in the case of Tunisia, and other countries showing some degree of reversion to the mean include Israel, Syria, Yemen, and Iran. Dealing with the issue of convergence within the MENA countries, similar conclusions hold and only Tunisia reports statistical evidence of convergence for the two types of errors. Additional evidence is found in the case of Syria, Yemen, and Jordan with uncorrelated errors and for Iran with autocorrelation. It is recommended that environmental policies targeted at stabilizing the trends in EF in the MENA region should not be indiscriminately applied in consideration of the heterogeneous nature of the series in the region.

On the convergence of ecological footprint in African countries: New evidences from panel stationarity tests with factors and gradual shifts.

Convergence of the environmental indicators has been one of the significant research areas for researchers since the study of Strazicich and List (2003) was published. Earlier papers have concentrated on investigating the existence of the convergence of indicators of the environment by using carbon emissions as a pollution indicator. However, some researchers have criticized the use of carbon emission as a one-dimensional indicator and proposed using ecological footprint as a more comprehensive indicator. The primary aim of this paper is to examine whether stochastic convergence of ecological footprint exists in 49 African countries from 1973 to 2018 by employing a battery of traditional stationarity methods and a newly proposed stationary method with smooth shifts and a combination of p-values. The empirical results show that panel findings of the conventional stationarity test with no structural shifts reveal that ecological footprint follows a stationary process. In contrast, panel findings of the traditional stationarity method with sharp and smooth changes and the newly developed stationary method with smooth shifts and a combination of p-values reveal that ecological footprint follows a non-stationary process. Moreover, the majority of individual results show that the ecological footprint follows a convergent pattern in 38 African countries, whereas it follows a divergent pattern in the remainder. Therefore, the main finding indicates the stochastic convergence of ecological footprint in African countries is validated. The policy outcomes of the empirical results are given in the body of the paper.

The impact of technological innovation on renewable energy production: accounting for the roles of economic and environmental factors using a method of moments quantile regression.

Advancement in renewables is one of the most effective techniques for sustained long-term development, and nations across the globe are making efforts to change their economic and industrial structures in a bid to boost green growth. With the advent of the Fourth Industrial Revolution (4IR), the availability, access, and use of green technologies including renewable energy have significantly improved. Researches on the factors that influence renewable energy production are available. However, we are unaware of any previous research that examines the role of renewable energy innovation in the promotion of renewable energy production. As a result, this study evaluates the impact of technical innovation on green growth from 1993 to 2018, while accounting for real GDP, producer price index, and CO2 emissions. Due to their pivotal status among the developing countries, our study has focused on the BRICS countries. By using a new panel quantile regression augmented with the method of moments, the empirical findings suggest that the influence of renewable energy innovation on renewable energy production is significantly positive across all quantiles. Moreover, the coefficients are generally bigger at the small quantiles, which suggests that countries with smaller renewable energy production per capita (India and South Africa) have a higher probability to experience a greater impact of renewable energy innovation per capita than countries with bigger renewable energy production per capita (Brazil and Russia).

Convergence analysis of ammonia emissions by sector and fuel source in OECD countries from 1750 to 2019 using a new Fourier-centric wavelet approach.

Although ammonia emissions are not as huge as carbon and methane emissions, they pose significant threats to ensuring environmental sustainability and productivity. However, the existing literature has paid less attention to the underlying characteristics of ammonia emissions. The chief target of this study is to investigate the stochastic convergence of ammonia emissions at the aggregate level, by sector, and by fuel source in 37 Organization for Economic Cooperation and Development countries for more than two centuries of data. Using a newly proposed Fourier-augmented wavelet unit root test, the empirical findings reveal that the relative ammonia emissions series in most Organization for Economic Cooperation and Development countries follow the unit root process in the aggregate, sectoral, and fuel-specific analyses. Therefore, these findings refer to the existence of divergence, while stochastic convergence does not exist in most cases. Having a divergent pattern of ammonia emissions has several policy implications for policymakers in the context of environmental sustainability. (i) Relative ammonia emission cannot revert to its steady-state path without policy intervention, (ii) policymakers have a chance of affecting the dynamics of ammonia emissions in Organization for Economic Cooperation and Development countries. (iii) As a policy response, the study recommends the pursuant of national environmental policies with consideration to the unique characteristics of the individual countries as the non-existence of convergence of environmental series could result in a diverse level of consciousness of environmental degradation among countries with divergent patterns on emissions levels.

Wind energy and sustainable electricity generation: evidence from Germany.

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.

Output and substitution elasticity estimates between renewable and non-renewable energy: implications for economic growth and sustainability in India.

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.

Interfuel substitution, hydroelectricity consumption and CO2 emissions mitigation in Malaysia: evidence from a transcendental logarithm (trans-log) cost function framework.

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.

Energy innovations and environmental sustainability in the U.S.: The roles of immigration and economic expansion using a maximum likelihood method.

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.

The impact of electricity consumption on CO2 emission, carbon footprint, water footprint and ecological footprint: The role of hydropower in an emerging economy.

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.