Environment, Mix Energies, A SEAN Economies and Education

Education, environment, energies and economic, have several number high impacts of research in 5 years. Data from Dimensions.ai, the most comprehensive research grants database which links grants to millions of resulting publications, clinical trials and patents, have several results about education, environment, energies and economic research, in Studies in Human Society 146 papers, Economics 96 papers, Applied Economics 95 papers, Engineering 93 papers, Policy and Administration 63 papers. Using vosviewer.com analysis, files downloaded from the free version of Dimensions may contain data for at most 2500 documents. (Larger numbers of documents are supported when a subscription-based version of Dimensions is used), we can see that Education have high impact on energy, environment, sustainability and sustainable development. The study aims to investigate the environmental effects of mix energies on the three most polluted countries of ASEAN economies. The study uses the data of the Philippines, Vietnam, and Thailand over the period of 1995-2017 as gathered from the World Bank and Global Economy. The study uses Brush Pagon LM and Pearson CD to test the cross-section dependence among variables while Levin et al., (2002) panel unit root test to check the stationary in the data. Westerlund (2007) cointegration and FMOLS tests are applied to analyze the long-run relationship. The result confirms the adverse environmental effects of fossil fuel electricity generation (FEG) and positive environmental effects of solar electricity generation (SEG), nuclear-power electricity generation (NEG), and geothermal electricity generation (GEG) on the ASEAN economies. Wind electricity generation (WEG) and hydroelectricity generation (HEG) do not significantly contribute to deteriorating the environment. The study suggests using GEG, WEG and SEG methods of producing electricity instead of FEG.


INTRODUCTION
Now a days, universal environmental problems are receiving huge consideration particularly the intensification of a high temperature of earth and air. The governments are gradually conscious of the need to bound these environmental problems from human accomplishments (Gogoi, 2013). These environmental problems are arising due to intense consumption of energy (Chopra, 2016). Nonetheless, a considerable amount of energy is essential for the better performance of economy, but it usually generated from fossil fuels, which is very unadventurous source and has enough contribution in CO 2 emissions that have adverse effects on environment (Zwolinska et al., 2011;Fujihashi et al., 2015;Kunz et al., 2011;Martıńez et al., 2003;Gil-León, 2020). So, the quality of environment is decreasing due to the consumption of energy. 50 years ahead, ASEAN state is foreseen to be most pretentious by the increment of CO 2 omission (IFAD). Therefore, this might be suitable for the government of the ASEAN region to produce the electricity by using most suitable and advantageous sources that have less contributions in environmental degradation because different apparatuses and machines that are used in the consumption of energy process, are omitting CO 2 emissions that in turn have adverse effects on the quality of environment. International warming and the changes in climate become the most significant hazard for people of ASEAN nations in 21 st century (Zhang, 2008;Janssen, 2020).
It is proposed that there are increases in apprehensions about the international energy demand and releases of toxic gases in the future (Chontanawat, 2018;Mavrotas et al., 1999;Tilman et al., 2009;Vusić et al., 2013). For reducing these apprehensions, international groups are trying to discover and appliance diverse environment-friendly approaches. Production of energy through renewable sources is one of these approaches that include production of energy through wind turbines, solar energy, geothermal, nuclear power, hydroelectricity (Hall and Buckley, 2016;Hong et al., 2016;Wouters et al., 2015;Chen et al., 2020;Dong et al., 2020). Though all these methods of producing electricity have less significant contributions in degrading the environmental quality as compared to conventional sources, however some of these methods have contributions to decreasing the quality of environment (Esha, 2008;Among others). The comparison of all types of energy with their environmental effects is shown in Table 1. Table 1 shows the differential environmental effects of different types of energy sources (mix energies). Different types of energy having different environmental effects. Some have environmental damaging effects, but some do not have environmental damaging effects. Correspondingly, Table 2 shows the increase in CO 2 emissions per kilowatt electricity production by using different energy sources. Table 2 shows that the electricity that are generated through Fossil fuels (Coal and Gas) have highest level of CO 2 emissions (minimum of 700 and a maximum of 1280 per kilowatt electricity production while the electricity, produced by using Nuclear Power, have the lowest level of CO 2 emissions (minimum of 3 and maximum of 1280 per kilowatt electricity production).
We have found different studies that tried to find out the impact of energy consumption on environmental degradation (Zwolinska et al., 2011;Kunz et al., 2007;Gunerhan et al., 2008;Among others). However, until now no study has been found in which the environmental effects of mix energy sources have been investigated. Therefore, current study attempts to empirically investigate the environmental effects of mix energy sources by using the data of most polluted ASEAN nations that are the Philippines, Vietnam and Thailand. So that best policy recommendations can be made for the government of ASEAN regions through which they can produce energy by using those sources that have less contribution to environmental degradation. Until now, no study has been conducted in this scenario.
Education, environment, energies and economic, have several number high impacts of research in 5 years. From data from Dimensions.ai, the most comprehensive research grants database which links grants to millions of resulting publications, clinical trials and patents, have several results about education, environment, energies and economic research, in Studies in Human Society 146 papers, Economics 96 papers, Applied Economics 95 papers, Engineering 93 papers, Policy and Administration 63 papers. Using vosviewer.com analysis, files downloaded from the free version of Dimensions may contain data for at most 2500 documents. (Larger numbers of documents are supported when a subscription-based version of Dimensions is used), we can see that Education have high impact on energy, environment, sustainability and sustainable development.
The remaining paper has the following structure: In section 2 there is brief review of literature and hypotheses. Section 3 represents the data and methodology while empirical findings are represented in section 4. Finally, section 5 concludes the research and paper ends with some practical implications and directions for further research.

LITERATURE REVIEW
This section explains the review of existing literature and the construction of hypothesis: Zwolinska et al., (2011) were interested in finding out the relationship between FEG and CO 2 emission, for this purpose they conducted a study and found that FEG positively and significantly contributes in CO 2 emissions and concluded that FEG have negative impact on environment because FEG causes to increase the CO 2 emissions that deteriorate the quality of environment. Hunt and Weber (2019) also revealed the adverse effects of FEG on the environment and proposed that FEG increases noxious gasses that not only reduce the quality of environment but also increases the illness and chronic diseases in children. Perera et al. (2018) revealed that most of the smog in air is the result of FEG methods that includes the production of electricity by using "coal, diesel fuel, gasoline, oil, and natural gas." The study concluded that all these methods adversely affect the environment and have very negative effects on environment. Tyagi et al., (2014) conducted a study for examining the role of energy consumption in the quality of environment. For this purpose, they used FEG as a proxy of energy and concluded a negative impact of FEG on the quality of environment and depicts that FEG has large contributions in increasing CO 2 that continuously decreasing the quality of environment. The above literature leads to construct the following hypothesis:

CO 2 Emission and Fossil Fuels Electricity Generation (FEG)
H 1 : "Fossil fuels electricity generation negatively contributes to environmental degradation" Saidur et al. (2011) found a positive relation between WEG and CO 2 omission and concluded that the production of electricity by wind turbines increases CO 2 emissions. Dincer (2003) conducted a study on WEG for elaborating its effects on environment and concluded that WEG has positive effects on environment in such a way that this method does not reduce the quality of environment because this method does not significantly contribute to increasing the CO 2 emissions. Grande Prairie Wind (2014) concluded that WEG has no impacts on environmental degradation, and only a few quantities of CO 2 emission are increased during the preservation phase of wind turbines that are engrossed by the trees during the route of photosynthesis. Kunz et al. (2007) were interested in investigating the effects of WEG on environment and found an insignificant association between WEG and CO 2 emissions and concluded that if the electricity is produced by using the method of WEG, the depletion of fossil fuel diminishes that lessen the CO 2 emissions. Based on above discussion, it is proposed that:

CO 2 Emission and Wind Electricity Generation (WEG)
H 2 : "Wind electricity generation insignificantly contributes to environmental degradation" Gunerhan et al., (2008) conducted a study on the generation of electricity by using the solar energy sources and CO 2 omission and concluded that as compared to conventional energy sources, SEG has less contribution in environmental degradation. Mahajan (2012) elaborated the prospective problems of SEG on the environment and concluded that sound and visual disturbance arose during the fixing and annihilation phase of solar systems. Tsoutsos et al., (2005) examined the association between CO 2 emission and SEG and found both positive and negative effects of SEG on environment. According to their study, SEG has fewer contributions in environmental degradation as compared to conventional energy sources but still it has some adverse effects on environment, although solar cells don't release any gases, but their cubicles comprises some poisonous materials that may increase the risk of omitting the substances to the atmosphere in the course of fire. Gish et al. (2019) described SEG as boundless source that has very fewer contributions in decreasing the quality of environment as compared with fossil fuel. The study also elaborated that during the built-up process, there are some negative effects of this method on the quality of environment. The above discussion leads to develop the following hypothesis:

CO 2 Emission and Solar Electricity Generation (SEG)
H 3 : "Solar electricity generation has an impact on environmental degradation" Zeleňáková et al. (2018) found a positive effect of HEG on the environment. The study described HEG as a very clean method of producing electricity that has very fewer contributions in CO 2  Esha (2008) revealed that there is no significant contribution of HEG in the CO 2 omission and concluded that as compare to conventional sources, HEG has positive effects on the quality of the environment. The study further explained that one of the main reasons of environmental degradation is CO 2 omission, and HEG method doesn't contributes in CO 2 omission. Conclusively, the method of generating energy through hydroelectricity generation method does not have adverse effects on environment. Therefore, the study proposed that:

CO 2 Emission and Hydro Electricity Generation (HEG)
H 4 : "Hydro electricity generation has an insignificant impact on environmental degradation" 2.5. CO 2 Emission and Nuclear Electricity Generation (NEG) Sovacool (2008) investigated the influence of NEG on CO 2 emissions and showed that NEG has less significant contributions in increasing the greenhouse gas emissions. The results showed little environmental influence and lesser specific greenhouse releases. Kunz et al. (2007) also indicated that NEG has very less contribution in decreasing the quality of environment and perceived NEG as confirmed technology that have significant influences in reducing the poisonous gases and additional ecological cargos from the energy subdivision. Shen et al. (2019) reviewed the literature of NEG's effects on CO 2 emissions and concluded that the countries with huge nuclear programs, having better environmental quality as compare to those countries who do not have nuclear programs. The above arguments allow to construct the following hypothesis: H 5 : "Nuclear electricity generation has positive impact in environmental degradation" 2.6. CO 2 Emission and Geo-thermal Electricity Generation (GEG) Berrizbeitia (2014) examined the impact of GEG on CO 2 emissions and found both positive and negative effects of GEG on CO 2 emissions. The study concluded GEG as an environmentally friendly approach of producing electricity but also indicated its some negative effects on environment that may lessen the quality of environment. Glassley (2014) indicated that as compare to convectional energy sources, GEG has less contributions in environmental degradation, but still it has some effects in decreasing the quality of environment through liquescent and compacted waste, and the usage of land. thus, it is proposed that: H 6 : "Geo-Thermal Electricity Generation positively contributes in environmental degradation" Figure 1 represents the conceptuall framework of the study. This study aims to analyse the impact of energy mix in the case of Phillipines, Vietman and Thialand. Environmental degradation is the dependent variable of the study that is measured by CO 2 emission while mix methods of electricity generation are used as indepemdent variables that include FEG (H 1 ), WEG (H 2 ), SEG (H 3 ), HEG (H 4 ), NEG (H 5 ), GEG (H 6 ).

DATA AND METHODOLOGY
The study analyzes the impact of FEG, WEG, SEG, HEG, NEG, and GTG on CO 2 emission. The data of three most polluted nations (Phillipines, Vietman and Thialand) from ASEAN economies are collected from World Bank and Global Economy. The data period ranges from 1995 to 2017.
The study uses Brush Pagon LM and Pearson CD for testing the cross-section dependency of each variable. Levin et al., (2002) panel unit root test is used to check the stationary. Westerlund (2007) Cointegration test is used for testing the long run relationship among variables. Fully Modified least square (FMOLS) model is used to estimate the long run results. FEG, WEG, SEG, HEG, NEG, and GTG are used as independent variables while CO 2 emission is used as dependent variable. The explanation and measurement of the variables are presented in Table 3.

Model Specification
CO 2 it = β 0 + β 1 (FEGit) + β 2 (WEGit) + β 3 (SEGit) + β 4 (HEGit) + β 5 (NEGit) + β 6 (GEGit) + e "Where; CO 2 is corban dioxide omission, FEG is fossil fuel electricity generation, WEG is wind electricity generation, SEG is solar electricity generation, HEG is hydro electricity generation, NEG is nuclear electricity generation, GEG is geo-thermal electricity generation, i and t stands for country and the time respectively; while e denotes normally distributed error term." Table 4 depicts the results of "Breusch-Pagan LM, BFK and Pesaran CD" tests applied to check the Cross-Section dependence of variables, meaning that either the shock in a selected country have a tendency to be transferred in other countries or not. We have a null hypothesis that there is no cross-section dependence among variables. Null hypothesis is rejected for all variables at the significance level of 1% and 5% which concludes that there exists cross-section dependence among variables. Table 5: Panel unit root test Table 5 presents the outcomes of a panel unit root test that is used to test the stationarity and order of integration of data. Here, we have a null hypothesis that the series are nonstationary. The study used Levin et al., (2002) unit root test for testing the stationarity of the data. Results elaborate that all the series are non-stationary at level and become stationary at first difference by rejecting the null hypothesis at 1% and 5% level of significance which states that all the variables have an integration of order 1. In other words, all the variables are integrated at I(1). Table 6 demonstrates the results of descriptive statistics of study variables. 7 variables are being used in the study. The Table shows the mean, median and standard deviation of the data, furthermore, it also shows skewness and kurtosis along with maximum and minimum values.

DATA ANALYSIS
Normality of residuals also been check through Jarque-Bera test. The null hypothesis for this test is that the residuals are normal, as we can see that all the probability values are significant which rejects the null hypothesis, so the residuals are not normal in our case. Table 7 elaborates the results of Cointegration. As mentioned above, there is cross section dependence among variables, so the study applied Westerlund (2007) error correction-based panel cointegration tests with boot for testing that either the cointegration (long run relation) exist among the variables or not. The null hypothesis is set as "there is no cointegration" which is strongly rejected at 1% and 5% level of significance and the results conclude that there is presence of cointegration among variables. The study used Westerlund (2007) cointegration as it is vigorous beside cross sectional dependence in the panel data.
As mentioned above, there is presence of Long rung relationship among the variables. Thus, the study used FMOLS for the estimation of Long run coefficient. Table 8, therefore shows the results of FMOLS. The study used FMOLS for the estimation because this method is operative in the removal of endogeneity problem. "Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring."

Independent variable
Fossil fuel electricity generation (FEG) "Billion kilowatt-hours of electricity generated from fossil fuels including oil, coal, and natural gas". Wind electricity generation (WEG) "Billion kilowatt-hours of electricity generated from wind" Solar electricity generation (SEG) "Billion kilowatt-hours of electricity generated from sunlight" Hydro electricity generation (HEG) "Hydroelectric generation excludes generation from hydroelectric pumped storage, billion kilowatt-hours is used as measuring unit of HEG" Nuclear electricity generation (NEG) "Nuclear electricity net generation (Net generation excludes the energy consumed by the generating units)". The measuring unit of NEG is billion kilowatt-hours. Geo-thermal electricity generation (GEG) "Billion kilowatt-hours of geothermal electricity generated" "**, *** denotes statistical significance at 1%, 5% and 10% respectively" The coefficient of FEG (0.0671) is positive and significant at 5% level which shows that 1-unit increase in FEG causes to increase CO 2 emissions by 0.0671 units in long run and representing the negative effects on environment, therefore, H 1 is accepted. Coefficient of SEG (−0.0142) is negative and significant at 5% level of significant, demonstrating that in the long run about 0.0142 units of CO 2 emission is reduced due to 1-unit increase in SEG and concludes the positive effects of SEG on environment, supporting H 3 . Similarly, coefficient of NEG (−0.0417) is also significant and negative which shows that by increasing 1-unit of NEG, CO 2 emission can be reduced by 0.0417 units. Here, H 5 is also accepted. Coefficient of GEG (−0.0028) also shows the reduction in CO 2 emissions by 0.0028 units against 1-unit of GEG. H 6 is also confirmed. While WEG and HEG do not have significant contribution in decreasing the quality of environment.
Hence accepting H 2 and H 4 . Value of adjusted R 2 shows that 88.72% variations in CO 2 emissions are collectively explained by FEG, WEG, SEG, HEG, NEG, and GTG. Universal environmental problems are receiving huge consideration particularly in the intensification of high temperature of earth and air. Government are gradually conscious about the needs to bound these environmental problems from the human accomplishments. These environmental problems are arising due to intense consumption of energy (Chopra, 2016). Nonetheless, a huge amount of energy is essential for the better performance of economy but it usually generated from fossil fuels, that is very unadventurous source and have enough contribution in CO 2 emissions that have negative effects of environment (Zwolinska et al., 2011) and the quality of environment is decreasing due to the consumption of energy. Therefore, the study analyzes the impact of FEG, WEG, SEG, HEG, NEG, and GTG on CO 2 emissions. The data of three most polluted nations (Phillipines, Vietman and Thialand) from ASEAN economies are collected for the period of 1995-2017 from World bank and Global economy. The study use FMOLS model for examining the results.

DISCUSSIONS AND CONCLUSIONS
The study finds the negative effects of FEG on environment as FEG results in increasing in noxious gasses that not only reduce the quality of environment but also increases the illness and chronic diseases in children. The results are consistent with (Zwolinska et al., 2011;Hunt and Weber, 2019). Study didn't find any contribution of WEG and HEG in increasing the CO 2 emission. Only a few quantities of CO 2 emission are increased during the preservation phase of wind turbines that are engrossed by the trees during the route of photosynthesis. Similarly, NEG method doesn't contribute in CO 2 omission, therefore, it doesn't have adverse effects on environment. Results are consistent with (Zeleňáková et al., 2018;Saidur et al., 2011;Aldahmani et al., 2020;Alkamil et al., 2020). SEG, GEG and NEG shows positive effects on environment in such a way that CO 2 emission will be reduced if electricity is produced by using these methods because NEG is perceived as confirmed technology that have significant influences in reducing the poisonous gases and additional ecological cargos   from the energy subdivision and SEG is a boundless source that have less contributions in decreasing the quality of environment as compare to fossil fuel. Results are similar with (Gish et al., 2019;Sovacool, 2008).
The study has some practical implications. First, there is need to use solar, geo thermal and nuclear energy source for the production of electricity. Second, fossil fuels have adverse effects not only on environment but also on the health of children. The government should avoid to produce electricity by using fossil fuel. The study also has some limitations: Firstly, this study used only 3 countries of ASEAN nations. Future study can be conducted by using whole ASEAN economies and can make comparison. Future study may extend the data period for more reliable results.