Inequalities by energy sources: An assessment of environmental quality

Energy demand is rising day by day, driven mainly by the development of countries. At the same time, uneven economic growth in countries is the prime cause of inequality in energy consumption. Keeping in view the worth of energy in the growth process, this study quantifies the impact of energy inequalities and trade on environmental quality over the period 1995–2018 for 57 countries. The Theil approach is used to quantify inter-and intra-regional disparities in five energy sources; oil, coal, natural gas hydroelectricity, and renewable energy. The results show that North America has the highest oil consumption inequality between the regions while East Asia & Pacific has the highest index value within the regions. Coal consumption inequality is declining in North America, but not in East Asia and the Pacific. Europe & Central Asia, and North America have the highest inequalities in natural gas consumption between the regions. Inequality is shrinking in hydropower consumption between the regions, however, such trend has not loomed within the regions. Europe & Central Asia and East Asia & Pacific have major renewable consumption inequalities within the regions. Generally, there is a decreasing temporal trend in energy consumption inequalities of all energy sources. The GMM technique is applied to investigate the impact of energy inequalities and trade openness on environmental quality. The results reveal that energy inequalities degrade environmental quality. Moreover, trade has a positive impact on environmental quality. However, democratic countries can be advantageous to improve the environmental quality. The study implies that countries should take actions to reduce energy inequalities within and between the regions. Specialization in production through trade can also be an option for improvement in the environment.


Introduction
Energy is one of the most important inputs for economic growth and development [1]. It is the indispensable need of each sector of the economy, such as household, industry, and agriculture [2,3]. On the contrary, a decrease in energy consumption can affect the Trade is an important economic aspect that affects the environment by accelerating economic development [19,20]. Trade activities are linked with higher energy use, particularly in the manufacturing of industrial goods and transportation of final products. A plethora of studies have examined the environment-trade nexus; however, the results are mixed and inconsistent. For instance, Akin [21] argues that trade mitigates the environmental problems while others using various parameters with trade conclude positive effect of trade on the environment [22][23][24][25][26]. Likewise, Tiwari et al. and Chebbi et al. [27,28] reported positive relationship between trade and the environment. In the global value chain scenario, Yasmeen et al. [29] found that at the earlier stage of development trade harms the environment but at the later stage it improves the environmental system by adopting clean technologies. Another study conducted by Wu and Wang [30] determines the drivers of emissions embodied in provincial trade and argues that final demand and carbon emission intensity are leading elements for emissions embodied in trade. Furthermore, the structure of trade is also important reason for emission encompassed. Nevertheless, Antweiler et al. [31] decomposed the positive and negative impact of trade on the environment into three possible ways: (i) the scale effect, (ii) technique effect, and (iii) composition effect. Under the scale effect, trade stimulates development process via production and the use of energy, which ultimately damage the environmental efficiency [32,33]. While, in the second phase of the development, the state engages in cleaner production because of sophisticated technologies with less/environmental friendly energy consumption which in turn improves environmental efficiency [34] called the technique effect. The composition effect arises when the share of emission-intensive goods in the production processes decreases [10,31,35]. Above and beyond, effective trade policy on energy consumption is necessary to attain sustainable growth with a clean environment. Trade can yield efficiency by access to eco-friendly technologies and via modern production methods which can reduce energy inequalities [35].
Though trade activities are inevitable without the effective use of the energy and its expansion reshapes the demand for energy due to a surge in the production rate. Developing countries are still tied up with obsolete energy-intensive production methods. Whereas, trade allows developing economies to access advanced energy-saving technologies and reduce energy inequalities between trading countries. Thereby, energy inequalities are also an important mechanism for predicting energy consumption patterns along with trade. Moreover, diverse types of energy sources have different effects on the environment. Hence, to achieve concrete results, it is imperative to conduct further investigation into energy inequalities and environmental quality nexus with different energy sources. Henceforth, energy inequality in its use cannot be overlooked in the process of environmental degradation. Thus the aim of this study is to unravel the disparities of energy consumption in renewable and non-renewable sources of energy. Each source of energy has its own energy consumption pattern that can differ in its inequalities and environmental impacts. Therefore, considering one source of energy is not sufficient to comprehend the entire consumption pattern of the energy sector. This study contributes to the growing literature on energy in many ways. First, it has selected five main energy sources; oil, coal, natural gasses, hydro, and renewable energy to explore energy consumption patterns and disparities. It also spotlights on non-renewable (oil, coal, natural gas) and renewable (hydro and other renewables) energy disparities. To the best of our knowledge, this paper is the first of its nature to investigate disparities of energy consumption in renewable and non-renewable sources of energy. Second, the trade sector heavily relies on energy as an input in the manufacturing of industrial goods and the transportation of products. Trade openness can, therefore, be an important factor in reducing inequalities by opening the door to more equal opportunities, especially for developing countries towards energy sources and technologies. Thus, this study also invokes the role of trade openness in the presence of energy inequalities. Additionally, we incorporate the role of political regimes which will be helpful in giving insightful implications to policymakers. Finally, the results could vary across the countries; thus the estimated functions might suffer from the problem of parameter heterogeneity. For the sake of robustness and to tackle the issue of parameter heterogeneity in estimated functions, estimation results are obtained both at global and regional levels. Moreover, this study also analyzes how energy inequality in inter-and intra-regions affects the environment. This enables us to recommend insightful measures for controlling energy inequalities among the regions. Energy disparities are calculated via cross-entropy (Theil's index) in five energy sources for the world and six regions.

Theil inequality index and econometric approach
The Theil inequality index [36] based on "Cross-Entropy" function is used to quantify the consumption disparities in oil, coal, natural gas, hydropower, and renewable energy. Theil index computes the disparities of random variables between two sets of distributions [37]. This index measures the information inequality between two probability distributions [36]. Moreover, "Theil's index" is more convenient and gives a more accurate picture of inequality within and between defined population groups [38]. Because it allows decomposing difference into the parts i.e. one due to inequality within regions and other is due to dissimilarities between regions. It aggregates the inequalities at each level/hierarchy of data as the final value of the Theil's Index is made of two components such as between the region and within the region. Upon this, it is a better measurement of regional energy consumption inequalities than others.
To extract the information inequality in the distribution cross-entropy (CE), the following equation can be used: Where, c it is the prior probability of an event occurred, and d it is the subsequent probability from unexpected information for "ith" country in the year "t"; i = 1,2,. . .. . .N, and t represents time (annual) t = 1,2. . .. . .t. Precisely, since "c it " is the energy consumption by different sources and "d it " is the population of "ith" country, then energy consumption share by source (E s ) can be computed as follows: Where, E s,it is the energy consumption of "s" source of the country "i" in the year "t", while, P N i¼1 E s;it is the total energy consumption of "s" source of all "N" countries at time "t". Just as, the population share of a country at year "t" can be computed as follows: Where, P it is the population of the country "i" in year "t", while, P N i¼1 P it is the total population of all "N" countries at time "t". The cross-entropy (CE) for energy consumption inequality by energy source can be calculated as follows: Eq (4) is used to measure energy consumption inequality in oil coal, natural gas, hydropower, and renewable energy. This index quantifies whether the consumption of the energy among the economies is diverging or converging. The CE t reduces if energy consumption inequality decreases over time, in contrast, vice versa. The total energy consumption inequality (At s ) for different energy sources can be computed through within and between regions inequalities. Suppose a world grouped into a region ("r") and it consists of many countries that have different energy consumption patterns in different sources. If a country situated in "r" region for = 1995, 1996,. . .,2018 then inequalities index of between-regions ("bt") and withinregions ("wt") for "s" energy-source can be estimated as: Where, energy consumption share in "s" source of region "r" is defined as E s;rt ¼ P r i¼1 e s;it , and share of the population is as P rt ¼ P r i¼1 p it . The "At s " is the sum of "bt s,t " and "wt s,t " inequalities that described in the following ways: Between-regional inequality "bt s,t " calculated the energy consumption inequality that exists in different energy sources, while "wt s,t " measures the energy consumption inequality in different energy sources within countries in region "r".
Energy consumption is an important pillar for the sectoral growth of economy including household, industry, transportation, agriculture and others those consuming energy resources at an unsustainable rate. This instability in energy consumption increases the potential for resource-based geopolitical conflicts that prevent nations to develop collectively to global climate threats. Moreover, it has been acknowledged by the environmental researchers that greenhouse gases produced by human activities have detrimental impacts on the global environment. A nation with unhealthy energy consumption patterns due to lack of cleaner sources poses a great threat indirectly towards the environment that cannot be ignored in the coming years. On the other side, trade can open doors to access advanced energy resources. Given the importance of energy consumption inequalities the empirical model is composed following Gozgor; Hasson and Masih; Pascual Sáez et al.; Hafeez et al. [22,23,39,40] as: Environmental quality is signified by EQ it . ECS it is the set of energy inequality in oil, coal, gas, hydropower and renewable consumption (BECS is between energy consumption inequality, WECS is within energy consumption inequality, TECS is total energy consumption inequality) are expected to be positive. TO is the trade openness, which can be either positive or negative. While composing the premise for examining the impact of energy consumption inequalities on environmental quality, the development process and prevailing political situation can also affect the level of carbon emission. Therefore, consistent with the literature, [10,22] this study includes the GDP (predicted to be positive) and SGDP (anticipated to be negative) to quantify the impact of development on environmental quality. The countries' institutions have been argued to benefit countries' commitment to improve the environmental quality by adopting stricter environmental policies, and curb carbon dioxide emission [41,42,43]. Moreover, democratic institutions are expected to be stronger enough to in climate change mitigation than non-democratic regimes. The democratic countries are under pressure of their voters to take actions for improvement in the energy efficiency and environmental quality. Thus to capture the political regimes (PRG) effect the political regime index is used which is classified as closed autocracy, electoral autocracy, electoral democracy, liberal democracy. The empirical estimates will be helpful in giving insightful implications to policymakers in the light of energy inequalities and trade. Moreover, the application of different energy sources will elaborate on the inequality situation in energy consumption substantially.

Generalized Methods of Moments (GMM)
In the present study, the dynamic panel data model is estimated. To evaluate the significant impact of the concerned explanatory variables on the environmental quality, we use the Blundell and Bond system GMM methodology. The GMM is the most popular estimation technique if time span (T) is less than cross-sections (N) Arellano and Bond [44]. The choice of system GMM is justified on the basis that if the dependent variable is persistent to a random walk then difference GMM performs poorly, as past values are vague about future changes. So, higher-order lags of the regressors are weak instruments for the differenced variables [45]. In such case, system GMM is the best choice Blundell and Bond [46]. Secondly, fixed effects estimator is biased in the presence of the lagged dependent variable and it also accounts for possible endogeneity issues. Moreover, if the difference GMM estimates lie below or close to fixed effects, this will be biased downward, and consequently, system GMM would be efficient. Additionally, GMM estimator, in the absence of MLE, can be used as an alternative to other methods. The beauty of both difference and system GMM methods are the use of the instruments which are valid based on the assumption that the disturbance terms are truly independent and are serially uncorrelated. Therefore, the Arellano-Bond test, checks for serial correlation in the residuals by testing the residuals in the differenced equations for serial correlation. However, the first-order serial correlation is to be expected and therefore the key test is to check for second-order serial correlation which should not be rejected the null hypothesis of no second-order serial correlation. Moreover, the joint validity of the instruments can be verified by running the Sargan/Hansen test.

Data
In the first instance, global analysis has been performed to identify the inequalities of energy consumption in oil, coal, natural gas, hydroelectricity, and renewable energy. Then, sample countries have been classified for regional comparison, based on World Bank data definition. Due to the unavailability of data, the Middle East & North African region is excluded while we quantified the inequality in renewable energy consumption. Further, due to the data limitation, we have selected overall 57 countries for empirical analysis over the period 1995-2018. The detail of sampled countries is provided in Table A1 in S1 Appendix. The data for CO2, oil, coal, natural gas, hydroelectricity, and renewable energy (including wind, geothermal, solar, biomass) are extracted from the World Energy Outlook [6]. While the data of population and trade are taken from the World Development Indicators [47]. The data description in detail is mentioned in Table 1.

Panel correlation matrix of energy inequalities by source
The correlation statistics are reported in Table 2. The environmental quality (EQ) is positively correlated with between (BECS), within (WECS), and total (TECS) energy inequality for oil, coal, and natural gas. It demonstrates that inequality in energy sources degrades environmental quality by rising CO2 emissions. However, hydropower source is negatively related to within energy inequality and the environmental quality. There is also a negative association between and within renewable energy inequality and EQ. This negative direction reveals that cleaner sources of energy are key to reduce CO2 emissions, even though inequality exists in its use. The variable of trade openness is negatively correlated with environmental degradation. While, at the initial stage of development, income (GDP) decrease the environmental quality (EQ), while, in the second stage of the development it improves as the correlation between SGDP and EQ is negative. In addition, trade decreased the energy inequality between and within regions. Moreover, it is also effective in reducing total energy inequalities. In a nutshell, trade opens door to more equal opportunities for developing countries towards energy sources and technologies. As per expectations political regime positively contributes to improve the environmental quality.

Estimates of energy inequality
The world energy consumption disparities are computed by using the model presented in Eq (4). The oil energy consumption inequality graphs depict that the index of oil energy inequality  less energy inequality in oil consumption between the regions. Meanwhile, North America, and Europe & Central Asia are showing major and minor disparities in oil energy consumption, respectively. These energy inequalities in oil consumption indicate that every region has a different growth level. Moreover, economies differ in production methods, market size, industrial growth, and weather conditions.   The lowest part of the index reveals minor total energy inequality for gas in Latin America & Caribbean, and East Asia & Pacific regions, while, South Asia is showing a steady trend in its total gas energy inequality. Total energy consumption is declining over time in sample regions (Fig 10).
With liberalization, inequality has fallen over the time in hydroelectricity consumption. The energy inequality between the regions for hydroelectricity is illustrated (Fig 11). The lower index value reveals less hydroelectricity consumption difference between the sampled regions   It is a common belief that renewable energy is comparatively environment friendly. Over the time, the inequality in renewable energy consumption has decreased in the world. Renewable energy consumption inequality between the regions is demonstrated in Fig 14. Lower series of the index showed that there is a little discrepancy in Latin America & Caribbean relative to other regions. South Asia also has fewer disparities. North America has the highest inequality between the regions that has lowered over the time. Fig 15 outlined the inequality scenario for renewable energy consumption within regions. East Asia & Pacific has the highest disparities in renewable energy consumption within the region until 2004, afterward it has fallen over the time. A decreasing trend is visible in renewable consumption inequality within Europe & Central Asian region, while South Asia has a little discrepancy in the consumption of renewable energy, and its disparities have declined over the time, while disparities in Latin America have a tiny upward trend. Total energy inequality in renewable energy consumption is explained in Fig 16. The upper index value revealed that North America had the highest inequality in total renewable energy consumption, which is declining over the time while South Asia has minor inequality in total renewable consumption. However, the total renewable energy disparities in East Asia & Pacific have decreased over the time. Latin America & Caribbean has very minute inequality in total renewable energy consumption.
There is a clear decreasing trend in global inequalities in levels of energy consumption, especially within regions. It implies that the situation within regions is comparatively better than between world countries. But the inequality in energy access to resources did not vanish.

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According to the World Energy Council (2000) 40 percent of the world's population has no systematic access to energy products in their homes [48]. Ultimately, unequal energy consumption patterns translate into different rates of greenhouse gas emissions throughout the world. People

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Inequalities by energy sources: An assessment of environmental quality living in developing countries have unequal access to modern technology and clean energy resources [12,14]. Energy is the biggest source of greenhouse gases emitted into the air that have widespread detrimental impacts on home-grown, regional and world eco-systems. Moreover, the evenhanded approach to address the problem of global climate change would be to define a standard per capita emissions rate and then put penalties on states that beat the standard [49].

Empirical assessments of energy inequalities on environmental quality
In order to conduct a comprehensive study, we have applied the system GMM to our study and also include the standard diagnostic tests mentioned above section. Different countries

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Inequalities by energy sources: An assessment of environmental quality and regions are technologically at different stages but it data are not available for each country. Therefore, to minimize the technology differences, region level analysis will be more appropriate as these differences are comparatively low at regional level. It will also be important for robustness of the findings.
Region-wise environmental implications of between, within, and total energy consumption inequalities by oil are presented in Table 3. It is evident that countries are becoming more liberalized owing to trade operations and have access to various kinds of energy sources that lead to a decrease in inequality over time in oil, coal, natural gas, hydroelectricity, and renewable energy consumption. However, the energy industry still needs to be improved by giving global economies equal access to energy resources. Although we are observing a reduction in disparities in oil consumption, it is still insufficient to reduce environmental degradation. Oil energy inequality between the regions has a significant positive impact on carbon emissions in the world, Europe & Central Asia, North America (except within region), East Asia & Pacific, South Asia and Latin America & Caribbean regions. The energy inequality index also showed that North America has the greatest disparities between the regions. However, the Middle East & North Africa has a negative impact on the environmental quality. The majority of Middle Eastern countries, are endowed with natural resources and recognized as oil-producing and exporting countries. So possibly it has a modest impact of inequalities on the environment due to abundant resources.
The inequality index also showed less severity in its consumption which has a declining trend after 2015. The energy inequality of oil within region also decreases the environmental quality. North America and Middle East & North Africa inequalities within regions have no detrimental impact on the environment. As inequality index of oil consumption also showed fewer disparities within the North America region. Total oil consumption inequality is also increasing environmental pollution in the world and all regions except the Middle East & North Africa. These results depict that inequalities in oil consumption accrue sever damaging impact on environmental quality as indicated by (Shafiei et al; Tang et al) [50,51] which also       Table 3 show that environmental degradation increases at the initial stage of the development. These results are consistent with [22]. However, in the latter phase of development environmental degradation improves, as the impact of GDPS is negative in all sample regions. However, the impact of political regimes is statistically negative in the world and across all regions. It implies that countries having more liberal democracy take action to reduce carbon emissions.
Coal is the largest source of energy; however, most of the countries are striving to switch from coal to cleaner sources of energy along with the demand for higher economic growth, especially in developing countries. The inequality impact of coal consumption is reported in Table Table 4 sustain the cogency of the EKC hypothesis among the selected sample countries of the world and across six regions.
Natural gas is another important energy source and has major environmental implications. The results of gas consumption inequalities are described in Table 5. Inequality in natural gas consumption is also not environment friendly as the coefficient of between regions inequality  Table 5 again validate the inverted U-Shaped EKC curve.
Hydroelectricity is a competitive source of renewable energy. In the coming years, its consumption is anticipated to rise as a cleaner source. However, its consumption inequality fails to yield better environmental outcomes. The results of energy consumption inequalities by hydroelectricity sources are presented in Table 6. The results show that the inequality between regions is harmful to the environment in the case of all regions except the world and the Middle East & North Africa. However, the inequality of hydroelectricity consumption within (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.000) (0.00) (0.00) (0.00)

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Inequalities by energy sources: An assessment of environmental quality region which are decreasing over the time. Possibly, due to the large production of China in hydroelectric power the inequality within East Asia & pacific regions is on decreasing path.     The utilization of hydroelectricity in Asian countries is increasing that emit less emission [52,53]. Moreover, total energy inequality also increases environmental degradation positively in all regions except the world and Middle East & North Africa. In the case of hydroelectricity energy source, the coefficient of trade remained almost positive except the Middle East and North Africa, North America and to some extent in the world. However, the impact of political regimes on the environment is negative. Moreover, the results of GDP and square of GDP indorsed our previous results and confirm the inverted U-Shaped EKC curve in the sampled countries.
Recently, the importance of renewable energy to safeguard the environment has risen. However, the study also found inequalities in renewable energy consumption. The impact of renewable energy consumption inequality on the environment is reported in Table 7 [24,25]. However, trade remained negative in North America region. Again we find the negative impact of political regimes on the environment. Moreover, the results of GDP and square of GDP indorsed our previous results and confirm the inverted U-Shaped EKC curve in the countries.
By considering the environmental Kuznets curve, the environmental situation can be alarming at the early stage of the development as the country starts trade its income and production level grows. However, at this stage, countries have more pollution because of less access to cleaner energy resources. Additionally, economies are mostly dependent on obsolete methods of production that consume more energy and emit more carbon. So, trade impact possibly is positive. In addition, trade does not enhance environmental quality if a nation produces high-emission products. Secondly, developing nations are causing more pollution by the lax rules and regulations laid down in free trade agreements [20,54,55]. Under the race to the bottom hypothesis, trade may have hazardous effects on the environment especially in the case of developing countries [20]. Yasmeen et al [29] also find that the trade impact on eight air pollution indicators is positive at first stage of the development but it leads to improving the environmental quality in the second phase of the development. In this context, our results are in line with the extant literature. In renewable energy, Europe & Central Asian region seems to improve the environment by trading as the coefficient sign is negative.

Conclusion
The world is experiencing rapid growth in energy consumption due to economic expansion and population growth. Thus, keeping in view the worth of energy in the growth process and trade sector, this study finds inequalities in oil, coal, natural gas, hydropower, and renewables. Energy inequalities by renewable and non-renewable sources provide insightful information for policy development. The inequalities are calculated by applying "Theil's cross-entropy" that shed light on inter-and intra-energy consumption among six regions of the world.

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Inequalities by energy sources: An assessment of environmental quality North America has the highest oil consumption inequality between the regions while, East Asia & Pacific region has the highest index value within the region. Most importantly, all regions are experiencing a declining trend in oil consumption inequality. However, inequality in coal consumption is decreasing between the North American. Inequality in coal consumption is increasing in East Asia & Pacific regions. This increasing trend in inequalities is possibly due to China's economic expansion. Regardless of the regional situation, the overall world is experiencing decreasing inequality in coal consumption. Europe & Central Asia, and North America are two major regions that have the highest inequality in natural gas consumption between the regions. While, East Asia & pacific have the highest level of energy consumption inequality within regions. Moreover, there is a downward tendency in natural gas consumption inequality between and within regions. Inequality is decreasing in hydropower consumption between regions; however such a trend has not loomed within the regions. North America has large disparities between the regions that declined over the time. Within regions, North America and Europe & Central Asia have a higher-level of inequality in hydro-energy consumption, which remains almost sustained over the time except in 2009. In contrast, total energy consumption inequality is decreasing over the time. In East Asia & Pacific, however, there is a rising trend in total inequality in hydro consumption. Europe & Central Asia, and East Asia & Pacific have major inequalities in renewable consumption within regions. However, there is a decreasing trend over the time. The inequality gap is also diminishing between North American regions for renewable energy sources. In total renewable energy consumption inequality, we find a decreasing pattern for all regions. By using the GMM method, we discover that inequalities in energy consumption have a positive effect on the quality of the environment. Trade is considered the engine of growth and development in the economy. Trade has a positive impact on environmental quality. The study also shows that the democratic political regime can be advantageous to improve environmental quality. Despite this, the study results validate the inverted U-shaped impact on environmental quality.
Although the study found the declining trend in energy inequality, the mechanism of the energy sector still needs to be improved. The primary cause of energy inequalities and carbon emissions is the growth in power demand. Switching to renewable energy is not the only way to decarbonize. Therefore, unlike just renewable energy, advanced technology needs to be adopted that consumes less energy and fewer emissions. Trade can help to reduce energy inequalities by opening the doors to more equal opportunities for developing countries towards energy sources. Developing economies, however, are not good at shaping the effect of trade on the environment due to emission-intensive goods. Therefore, its compositional impact (engagement to products) must be revised in order to enjoy trade-led growth with the green environment. Institutional reforms are also important for improving trade and energy efficiency. To balanced energy consumption and strong institutions can actively regulate inequalities within regions. In addition, the identification of inequalities in distinct sources of energy can provide policymakers with helpful guidance on energy consumption and sustainable growth. Though the present study found considerable variations in energy inequality among the regions, however, overall inequality in oil consumption has decreased over the time. This declining trend in oil energy consumption inequalities shows equal access to oil resources. Overall this study implies that countries should take necessary actions to reduce energy inequalities within and between the regions. Specialization in production through trade can also be an option for improvement in the environment. The study has limitation as each country has different resource endowments, different climates, different economic developments, different industrial structures, and different levels of technology. The consumption of energy per capita is naturally different thus the analysis is also conducted at regional level to minimize the country specific effects as these differences are comparatively low at regional level.