Impact of Energy Consumption, and Economic Dynamics on Environmental Degradation in ASEAN

The study aims to investigate the impact of energy consumption, population size, economic growth, urbanization, industrialization and poverty on environmental degradation in Malaysia by using the data for the period of 1995-2017. Data was gathered from different sources such as Global Economy, World Bank and Index Mundi. Augmented Dickey-Fuller (ADF) test is used to check the stationarity of the data. While Auto Regressive Distributive Lag model (ARDL) to analyze the results. The study finds a positive impact of energy consumption on environmental degradation in short as well as in long run. Population, industrialization and poverty positively contribute in environment degradation while urbanization negatively contributes in environmental degradation in long run. Economic growth positively contributes in environmental degradation in short run only. The study suggests government to produce energy by using renewable sources that have less contribution in environmental degradation. This study provides guideline to the policy making authorities that they should enhance their emphasis towards energy consumption and environmental degradation.


INTRODUCTION
Environment is a main area of interest of different researchers in the current period. Everything around us is environment. It can be living or non-living factors. It consists of chemical, physical and other natural forces. All the living things live in an environment, so they use natural resources. As these natural resources are continuously extracted, they degrade the environment. Degradation of environment is one of the main hazards of emerging nations (Dhami et al., 2013). It is a process of environment deterioration through extraction and depletion of natural resources like soil, air and water, habitats destruction, ecosystem's devastation and pollution etcetera. A degraded environment affects or changes the climate, due to which global temperature rises. As the temperature increases, the amount of carbon dioxide (CO 2 ) in the atmosphere also increases. population. The energy makes the provision of basic necessities and whenever there is increase in population size, there will be increased basic needs and wants of people as they will require more space for their living arrangements. There will be increase in transportation, consumption of energy for the satisfaction of their needs that degrades the environment by increasing CO 2 emissions.
If people are unable to satisfying their needs, they become poor and they may start deterioration in the environment for the satisfaction of their basic needs. Therefore, there is a need to increase in production due increase in industrialization and economic growth. Basically, industrialization traditionally leads to urbanization by generating economic growth opportunities but the reality is that both urbanization and economic growth have enough contributions in environmental degradation. Urbanization leads to increase commercial energy consumption and CO 2 (Gasimli et al., 2019;Kamran and Omran, 2018;Yildirim et al., 2014;Sbia et al., 2017) while economic growth is an increase in per head level of production of goods and services over a specific period of time.
There is no controvert that economic growth takes many benefits but the reality is that accumulative measures of production also deteriorates ecosystem and exhaust natural resources because economic growth is usually measured as a percentage increase in gross domestic product (GDP) that grows with the increase in the production of goods and services. A country's economy uses labor, energy, raw material and capital in the production of goods and services. In this process of production, raw material such as minerals, water, trees and metals etcetera are extracted from environment that deteriorate the environment.
This study contributes to the existing literature in such a way that this study uses all those independent variables (EC, POP, POV, IND, URB, EG) that have enough contributions in ED. Many study investigated the individual impact of these independent variables with ED but we didn't find any study in which the collective impact of all these variables has been investigated. There is a huge need to investigate the collective impact of all these variables on ED. Moreover, all the variables i.e. EC, EG, POP, IND, URB, POP have some effect on ED. The coefficient of independent variables will become more reliable which makes us able to draw best policy suggestions. Therefore, the study is an attempt to collectively examined the impact of all those important variables that have enough contributions in environmental degradation. The remaining paper has 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 of further research.

LITERATURE REVIEW
This section provides the review of existing literature and construction of hypothesis. Hasnisah et al. (2019) empirically investigated the relationship between EC "renewable and non-renewable energy consumption" and environment quality (CO 2 ) by using the data of 13 developing countries in Asia for a period of 1980-2014 and showed that nonrenewable energy consumption (NRE) was inversely related with CO 2 whereas renewable energy consumption (RE) was insignificant in the contribution of less pollution respecting the emissions of CO 2 because EC share from RE foundations comparatively low and it had inadequate contributions in the total energy. The linkage between bio-mass EC and ED in west Africa from the period of 1980-2010 and showed that increase in mass EC increases ED because mass EC upsurges the CO 2 emission which in turn rises the environment pollution. Haruna and Mahmood (2018) explored the impact of conventional EC on CO 2 released and revealed that the EC caused environment pollution in short term as well as in long term. The bi-directional relationship between EC and CO 2 emissions by using the data of 28 provinces in china from 1995-2007 and found that the quality of environment and EC moves in opposite direction and EC is the cause of increase in CO 2 emissions in long term. So, it is proposed that: H 1 : "There is a positive relation between Energy Consumption and Environmental Degradation." Shi (2003) investigated the impact of population on ED by using the data of 93 countries over the period of 1975-1996 and found a direct relationship between POP and ED. The study also found that this relation was more obvious in developing nations. Sherbinin et al. (2007) studied the relationship between size of POP and CO 2 emissions and showed that there was a positive association between size of POP and CO 2 emission. Ray and Ray (2011) also found the positive relationship between ED and POP size in the case of India. The study concluded that increasing POP contributes to the deterioration of land that tends to increase ED. So, it is proposed that: H 2 : "There is a positive relation between Energy Consumption and Environmental Degradation." Alper and Oguz (2016) used the data of eight European member nations to examine the impact of economic progress on ED and showed that the EG was positively related with ED. A positive association between ED and EG. Aremu et al. (2014) investigated the relationship between ED and EG and found a long term relationship between EG and ED. Shahbaz et al. (2019) used the data of Vietnam over the period of 1974-2016 and revealed that the relationship between ED and EG follows N-curve pattern. Kahuthu (2006) revealed that there was inverted U-shape relationship between ED and EG. This study confirms the environment-Kuznet curve (EKC) in global context. So, it is proposed that: H 3: "There is positive relationship between Economic Growth and Environmental Degradation."

Environmental Degradation (ED) and Urbanization (URB)
The influence of URB on ED by using the data of UAE and revealed a negative significant influence of URB on EG. Katircioglu et al., (2019) investigated the contributions of URB on ED in the context of Turkey by using the structure of EKC. The results of the study concluded that consumption of traditional energy increases due to URB that in turn have direct effects on CO 2 emissions. It means that URB have positive effects on ED. Moreover, the EKC hypothesis is not confirm in the case of turkey. Similarly, Wang et al. (2016) also concluded that the level of URB have positive and significant effects on ED in western region while in the eastern region there is no any significant effects of URB on ED. Gasimli et al. (2019) conducted their study on the relationship between URB and ED in the case of Sri Lanka and found the negative impact of URB on ED and concluded that URB is not dangerous for environment as it is not responsible for increase in CO 2 releases. So, it is proposed that: H 4: "There is a relationship between Urbanization and Environmental Degradation." Bhandari and Garg (2015) examined the influence of IND on ED by using the data of India and concluded that IND has enough contributions in ED. The study also concluded that IND results increase in harmful releases in soil, water and air that tends to degrade the environment. Dhami et al. (2013) took support from environmental input/output analysis and examined the influence of IND on ED and found a significant positive effect of IND on ED. Thus, it is proposed that: H 5: "There is positive relationship between Industrialization and Environmental Degradation."

Environmental Degradation (ED) and Poverty (POV)
The relationship between environment degradation and poverty in Pakistan over the period of 1974-2016 and found a direct relationship between ED and poverty. They considered environment as a basis for the survival of poor people that became suspected when the environment was deteriorated. Aggrey et al. (2010) used the data of Katanga basin and found a positive impact of environment quality on poverty reduction and suggested that a flourishing environment was a main index for sustainable progress and the toxic environment condition executed adverse effects on the residents. Ravnborg (2003) also showed a positive link between ED and poverty in Nicaraguan Hillsides and suggested that the government should make policies that reduce poverty. Therefore, it is proposed that: H 6: "There is positive relationship between Poverty and Environmental Degradation."

DATA AND METHODOLOGY
The study empirically examined the impact of EC, EG, POP, POV, IND, and URB on POV. The data for the period of 1995-2017 are gathered from three different sources; Global Economy, World Bank and Index Mundi. Augmented Dickey Fuller (ADF) test is used for checking the stationarity of the data. The data achieved stationarity at level and first difference, so we take support from Auto Regressive Distributive Lag (ARDL) model for examining the results. EC, EG, POP, POV, IND, and URB are used as independent while POV is used as dependent variable.
The explanation and measurement of the variables are presented in Table 1.

Specification of the Model
The study uses following econometric model for analyzing the impact of EC, EG, POP, POV, IND, and URB on POV.
Where "EC is Energy Consumption, POP is Population, EG is Economic growth, URB is Urbanization, IND is industrialization and POV is poverty" Table 2 demonstrates the results of descriptive statistics of the data. 6 variables are being used in our study. This Table 2 shows the mean, median and standard deviation of the data. Furthermore, it also shows skewness and kurtosis along with maximum and minimum values.

EMPIRICAL FINDINGS
Normality of residuals has also been checked through Jarque-Bera test. The null hypothesis for this test is set as "the residuals are normal", as we can see that all the probability values are insignificant which states that we can't reject null hypothesis so that all the residuals are normal in our case. Table 3 represents the findings of ADF test of unit root that has been used for testing the stationarity and order of integration of data.
Here, we have a null hypothesis that "the series are non-stationary".
Results of ADF shows that all the variables EC, POP, EG, URB, POV are insignificant at level, while they become significant at first difference by rejecting the null hypothesis at 1% and 5% which states that all these variables are stationary at first difference and have an integration of order 1, I (1). While IND and ED are significant at level by rejecting the null hypothesis at 5% and it also become significant at first difference by rejecting the hypothesis at 1% which states that IND and ED are stationary at level and at first difference and have an integration of order 0 and 1, I (0) and I (1). As all the variables are integrated at I (0) and I (1), the study moves forward for ARDL approach.
Before using ARDL approach we use bound testing and after that we apply the ARDL approach to check the short and long run association among the independent and dependent variables.
Before proceeding to our further analysis, we have to ensure that our data must be free from serial correlation, and heteroscedasticity.  "Environment degradation is a process of environment deterioration through extraction and depletion of natural resources like soil, air and water, habitats destruction, ecosystem's devastation and pollution etcetera. A degraded environment affects or changes the climate, due to which global temperature rises. As the temperature increases, the amount of carbon dioxide (CO 2 ) in the atmosphere also increases. The study uses CO 2 emission as a measure of environment degradation." Data Source: Global Economy ED Independent Variables Energy Consumption "Per Capita" "Per capita "energy consumption contains all forms of energy sources from domestic creation and imports. Energy is expressed in kilograms of oil equivalent. Energy use refers to use of primary energy before transformation to other end-use fuels, which is equal to indigenous production plus imports and stock changes, minus exports and fuels supplied to ships and aircraft engaged in international transport." Data Source: Global Economy EC Population Size "In Millions" "Population refers to the collection of humans. In simple words, population is the number of people living in a specific region, town, city, country or world. It is determined through a particular process known as census. It is measured as a total number of people (in millions) in a country." Data Source: Global Economy POP Economic Growth "Rate of Change of Real GDP" "Economic growth is an increase in per head level of production of goods and services over a specific period of time. Usually, it is measured as a percentage increase in gross domestic product (GDP). Economic growth rate is an annual growth rate in GDP between current and prior year over a specific time period." Data Source: Global Economy and Trading Economy EG Poverty "Head Count Ratio" "Poverty is defined as the "state of being extremely poor." It is a situation of not having enough possession of material or sufficient income to fulfill basic needs. It is a multilayered concept which includes political, social and economic elements. It is measured as headcount ratio at national lines as a percentage of total population. This headcount ratio is a percentage of people living below the poverty line." Data Source: Index Mundi  The results of the bound test are depicted in Table 5. The null hypothesis for the bound testing is that there is a log run association between the variables. The value of F-Statistic is greater than upper and lower bound so we cannot reject the null hypothesis and conclude that there exists a long run association among the variables. Table 6 shows the short run and long run results. The coefficient of ED is positive and significant at 5% level of significance in short run (0.0016) while at 1% level of significance in long run (0.0039). It depicts that if 1-unit increase in EC causes, on average, to degrade the environment by 0.001640 units and 0.003913 units in short run and long run, respectively. Here, H 1 is accepted in short run as well as in long run. The coefficient of POP is insignificant in short run while significant in long run (0.011124) at 5% level of significant and depicts that if there is 1-unit increase in POP, the ED will be increased by   We checked the stability of the models by applying the CUSUM test suggested by Brown et al. (1975). Figure 1 represents the stability of the model. As we can see that the plots of our model remain in critical bounds so, we can say that our model is stable.

DISCUSSIONS AND CONCLUSIONS
Environment is a main area of interest of different researchers in the current era. Everything around us is environment. It can be living or non-living factors. It consists of chemical, physical and other natural forces. All the living things live in an environment. These living things use natural resources extracted from environment. As these natural resources are continuously extracted, they degrade the environment. Degradation of environment is one of the main hazards of emerging nations (Dhami et al., 2013 The present research finds positive and significant impact of EC on ED in short run as well as in long run because usually energy is produced from conventional sources that results an increase in CO 2 emissions which pollutes the environment. Results are consistent with previous studies (Hasnisah et al., 2019;Haruna and Mahmood, 2018; Among others). The study also finds that the size of POP positively contributes in ED in Long run. An increase in the size of POP leads to increase the basic needs of the people as they require more space for their living arrangements. There will be more increase in transportation, consumption of energy for the satisfaction of their needs which  (Ray and Ray, 2011;Sherbinin et al., 2007).
The study also finds a positive relation of EG with ED in Short run. The results can be linked with EKC because firstly, ED increases due to increase in EG, after that, economy will face turning point (after few years) then ED starts decreasing due to EG. The results are similar with previous studies (Alper and Oguz, 2016;Shahbaz et al., 2019). Findings show a negative impact of URB on ED which means that URB is not responsible in increasing in CO 2 emissions rather it fetches proficiency in public accommodations such as "public transport and electricity". Results are consistent with previous studies (Gasimli et al., 2019).
Result also shows positive contribution of IND in ED as fast progress of production and consumption results undesirable externalities such as increase in uproar, CO 2 emissions, and road blocking. Results are significant with previous studies (Bhandari and Garg, 2015;Dhami et al., 2013). Lastly, study also find a positive effect of POV on ED. One possible explanation of these outcomes is that if people are unable to satisfy their needs, they become poor and they may start deterioration in the environment for the satisfaction of their basic needs. The results are in line with previous studies (Aggrey et al., 2010).

Practical Implications
The implications derived from the study are following: 1. POV is an important factor that have enough contribution in ED. Poor people are deteriorating the environment for the satisfaction of their desires. Therefore, there is a need that government should make the energy assessable, so that the people may satisfy their needs. 2. EC is also an important factor that increase ED. Energy is produced from conventional sources that have enough contributions in ED. Therefore, the Malaysian government should produce energy from renewable sources that has less contributions in ED. 3. IND is also a main contributor in ED. Therefore, there is a need to reconsider the industrial policies.

Limitations and Future Directions
The study has some limitations: Firstly, this study is conducted in Malaysia by taking the data of 22 years. Future studies can be conducted by using the cross-country data and may also increase the data period. This study uses only one measure of each independent variable. Future study can be conducted by using different proxies of these variables.