Modelling Urbanization, Economic Growth, and Ecological Footprint Using Environment Kuznets’ Curve in Selected Asian Countries

This paper examines the relationship between urbanization, economic growth, and environmental quality using environmental Kuznets curve (EKC) hypothesis. The hypothesized link is tested using time-series analysis of 10 selected Asian countries over the period 1990–2018. First, the EKC hypothesis is tested through examining the relationship between EF, GDP, and URB. Further, the long-run relationship between EF, URB, and GDP is investigated using a vector error correction model. It was found that there is a cointegrated relationship between the variables in the countries China, Malaysia, and Thailand. Additionally, almost all error correction terms are correct in sign and are significant, which implies that some percentage of disequilibrium in EF in the previous year adjusts back to the long-run equilibrium in the current year. Therefore, an efficient trade-off between environmental protection and economic benefits should be taken, and EF should be reduced through changing consumption patterns, improving the efficiency of use of resources and cleaner technology choices.


INTRoDUCTIoN
In economic history, the relationship between environment and economic growth gradually caught attention of the researchers with soil degradation in 1930 and air pollution during 1950-60 (Jiang, et al., 2020).In late 20 th century, it was accepted that environment sustainability through use of natural resources is the biggest challenge for the process of economic growth.Therefore, for global economy, environment is considered as an important factor to shape the economic development.There exists complex relationship between environment and economic growth especially in relation to causes and impacts of each other.Various research studies in literature have demonstrated the positive as well as negative relationship of economic growth with the environment (Dong & Karmacharya, 2018), (Lin, et al., 2017) & (Shahbaz, et al., 2016).This impact depends upon the degree of use of natural resources and release of pollutant from the use of those resources.Not only this, human activities highly impact earths' climate and ecosystem.Therefore, increasing population and urbanization can be considered as the key factors affecting the environment.In the previous chapter, it is found that there exists U-shaped relationship between urbanization and environment in selected Asian countries for this study.It depicts that at initial level, there is positive relationship between urbanization and environment quality but at later stages, this relationship becomes negative with increase in rate of urbanization.This research study aims at comparing selected Asian countries based on the relationship between urbanization, economic growth and environment degradation using Environment Kuznets Curve.

Environment Kuznets Curve
The concept of Kuznets curve (KC) was given by Simon Kuznets in 1955.The key focus of Kuznets' curve was to confront the relationship between environment quality and economic development.According to Kuznets, in developing countries, development is associated with transition of people from agriculture to industrialization or from rural to urban shift.At the initial stage, this development harms environmental quality but after reaching a certain point, it is converted into development process and positively impact the environment quality.Therefore, Kuznets claimed that there exists non-linear relationship between economic development and environment quality (Kuznet, 1955).This relationship found by Kuznets between economic development and environment quality was later termed as Kuznets U-hypothesis (Kapuria-Foreman & Perlman, 1995).Later on, while analyzing the relationship between per capita income and air pollution, a non-linear relationship was found which was similar to Kuznets curve.According to this relationship, development in early stages degrades the environment but after reaching a turning point, the development positively affects the environmental quality (Grossman & Krueger, 1995).This relationship between economic development and environment degradation is termed as environmental Kuznets curve as shown in figure 1.
This environment Kuznets curve in figure 1. predicts the inverted U-shaped ratio between per capita income and environment quality.But there exists a different reason behind inverted U-shaped curve for different countries.In developed countries, the reason behind inverted U-shaped relationship is trade with other countries as well as the adoption of environmental regulations as compared to the developing countries.According to the Heckscher-Ohlin trade theory, the countries become specialized in only those goods in which they are relatively abundant in and export excess of the goods to other countries.Developed countries require more labor and capital, on the other hand, developing countries require more labor.Production of different type of goods may have different impact on the environment and it can be the main reason of inverted U-shaped EKC (Stern, 2004).List & Gallet (1999) have also examined N shaped relationship between economic development and its impact on environment.As per N shaped environment Kuznets curve, the environment degradation increases with the rise in economic development in the initial phase.It starts declining in the next phase and after some time it again moves back to positive relationship with increased level of economic development.Dasgupta et al. (2002) gave his alternative view for Environment Kuznets curve and described the relationship between pollution and income in four different ways as shown in figure 2.
There are different views of economists for this inverted U-shaped relationship between income and environment quality.According to two pessimistic views, this EKC can be referred as the Race to the Bottom as shown in figure 2. For this idea of the race to the bottom, some critics claim that when emission level increases due to globalization, it stays at the absolute maximum level in a so-called "race to the bottom" of the environmental standard (Andrée, et al., 2019).Some other pessimistic critics claimed that there may be rise in the absolute emission with increasing level of economic development in the economy or it may result into new emissions as well which can also refer to as "New Toxic" (Ahmed, et al., 2019).On the other hand, another optimistic view states that innovations in the developed countries can have positive spillover effect on the developing countries as well.This results into efficient handling of inputs and reduction in the environmentally hazardous activities.Therefore, the peak level of environment degradation in developing countries is lowering down as compared to the developed countries (Dasgupta, et al., 2002).Stern (2004) mentioned this relationship between income and environment quality as a mixture of New Toxics and Revised EKC.
There is another type of Environment Kuznets Curve named as N-Shaped Environment Kuznets curve shown in figure 3.But the existence of N-shaped EKC has been challenged by various economists in literature for long run (Kerekes, et al., 2018).This N-shaped EKC has three different phases.The first phase represents the upturn of curve and indicates that environment degradation increases with increase in GDP per capita.This phase of N-shaped EKC characterizes the poor countries which cannot afford cleaner technologies.Second phase of EKC characterizes the middle-income economies where investment in clear technology associates the economic growth with environment quality.Third phase is when investment in cleaner technologies starts providing benefits.Overall, this N-shape curve reveals that after reaching a certain stage of development, the relationship between economic growth and environment become positive.

LITERATURE REVIEw
Various empirical research studies have used panel data and cross-sectional approach to prove environment Kuznets curve hypothesis (Ahmed, et al., 2019).But there are very few studies which have conducted time series analysis (Dinda (2004) & Lieb (2003)).Moreover, the few studies which have conducted time series analysis shows totally different results from the studies with panel data and cross-sectional data analysis.Dinda (2004) stated that time series analysis is helpful for the development of clear picture of relationship between environment degradation and economic development.Lieb (2003) also focused on the critical analysis of using panel data and time series analysis of measuring Environment Kuznets' curve.In literature, a variety of environmental indicators have been used to analyze environment Kuznets curve hypothesis.But no one has defined the variables which are most appropriate for this estimation purpose.Some studies have used emission of GHG gases, while others have used environmental pressure indicators for this purpose (Bekhet & Othman, 2017) (Kaur & Kaur, 2020).Various studies have also developed their own environment index to measure environment Kuznets curve.
This study is focused on a comprehensive form of analysis of environment Kuznets curve through the use of Ecological Footprint (EF).Ecological footprint is a method used to measure the demand of human beings for natural capital.The method is given by Global Footprint Network.It is also defined as the quantity of nature taken to support people and an economy.This demand of human beings for nature is tracked through ecological accounting system.This indicator is widely used in the fields of environmental social sciences and is also known as a reliable indicator which helps in the measurement of anthropogenic pressure on the environment (Kaur & Kaur, 2019).Most of the research studies have used income data as independent variable for examining Environment Kuznets curve.Though various other variables have also been considered in this model but it is assumed that income level has the most significant effect on the quality of environment (Kaur & Kaur, 2019).But as the main aim of this study is to analyses the relationship between economic growth and environment in the selected panel of economies, therefore, the study has used gross domestic product per capita as the independent variable and ecological footprint as the dependent variable.
The study aims at examining Environment Kuznets curve for selected economies (China, Bangladesh, Nepal, India, Thailand, Philippines, Indonesia, Cambodia, Vietnam and Malaysia) for the period of 1990 to 2018.These countries vary in terms of size of population, economic development, consumption of renewable and nonrenewable resources and emission of GHG gases.Therefore, the study focused on examining the relationship between urbanization, ecological footprint (EF) and Gross Domestic Product Per Capita (GDPPC) by testing Environment Kuznets Curve Hypothesis (EKC).The data sources for Ecological Footprint and GDPPC are Global Footprint Network and World Development Bank respectively.

THEoRETICAL FRAMEwoRK
According to environment Kuznets curve theory, GDP per capita is positively linked with environment degradation, but after reaching a certain level of GDP per capita, their would-be inverse relationship.In other words, EKC postulates a non-linear relationship between GDP per capita and environment degradation.It is to test this hypothesis in selected Asian countries, the study has followed the EKC model adopted by previous empirical studies (Lieb (2003), Dinda (2004), Saboori, et al., (2012) & Sinha, et al., (2018).According to Saboori, et al., (2012), the general format of EKC hypothesis is as follows.
Where E refers to environmental indicator, Y is the growth indicator and Z is an explanatory variable that may impact the relationship between environment and economic growth.This chapter focuses on exploring turning point of EKC for selected countries that is why it is has not considered any other variable that may have impact on the environment.Based on EKC hypothesis, the study has also calculated turning point of curve between urbanization and environment.
Most of the articles in literature on Environment Kuznets curve has used Logarithm of GDP per capita in quadratic form (Bekhet & Othman, 2017).Moreover, this form has been considered as the best measure in literature.This quadratic form represents a relationship between GDP per capita of residents of country and its effect on the environment quality of that country and expresses the inverted U-shaped relationship between them.But the researchers (List & Gallet, 1999) have mentioned that cubic form of model can represent N shaped relationship between the variables.This study has used logarithm form of GDP per capita, Ecological footprints and Urbanization.The linear, quadratic and cubic form of the models used in the study to test country specific Environment Kuznets Curve.These three forms of the models can be generally presented as follows.
The specific form of the model representing the linear relationship between urbanization and environment in the selected Asian economies is as follows.

EF URB
EF t in the equation is ecological footprint that has been used as a proxy of environment degradation in the economies.URB is urbanization index that has been used as a proxy of urbanization.The model representing the linear relationship between environment and economic growth in the selected Asian economies is as follows.

EF GDP
EF t in the equation is ecological footprint that has been used as a proxy of environment degradation in the economies.GDP t in the equation is GDP per capita that has been used as a proxy of economic growth in the selected economies.
b 0 & e t in the above models are intercept and error term respectively.b b b , and are slope coefficients.The type of linear relationship (concave, convex or linear) between to variables is represented through the sign of β. β 1 shows the impact of independent variable on dependent variable.In case of β 1 > 0, independent variable would have positive influence on dependent variable."1=2=3 = 0 reveals a flat pattern or no relationship" "1>0 and 2=3 = 0 reveals a monotonic or linear increasing relationship" "1>0, 2<0 and 3 = 0 reveals an inverted U-shaped relationship" "1<0, 2>0 and 3 = 0 reveals a U-shaped relationship" "1>0, 2<0 and 3 > 0 reveals a cubic polynomial or N-shaped relationship" "1<0, 2>0 and 3 < 0 reveals an inverse the N-shaped relationship" As per Environment Kuznets Curve, these shapes are based on the relationship between economic growth and environment, but there are several possible driving forces that may lead to Kuznets curve representing the relationship of environment with variable other than economic growth (Kaika & Zervas, 2013).Therefore, the study has examined the relationship between urbanization & environment and economic growth and environment through this Environment Kuznets Curve.
Following figures (4) show the pattern of above-mentioned different curves.Though, it is mentioned that the condition of N-shaped Environment Kuznets curve is 1>0, 2<0, 3 > 0 and for an inverse the N-shaped relationship 1<0, 2>0 and 3 < 0, but this condition is not sufficient to comment on the nature of Environment Kuznets Curve because this condition does not reflect the validity of the model.It is required to differentiate the model to the first order to test the validity of the model.The first order differential equation to test the model is given below.
It is also required for the above given equation to have local maxima and minima at the distinct value of Y3.The required condition for local maxima and minima is given below.
The next step is to find the value of maxima and minima to arrive at the second order condition.For this purpose, second order derivate of the equation 11 would be taken using the following formula.
The equation 12 proves validity of the second order condition.Therefore, it can be considered as sufficient condition for an N-shaped or an inverted N-shaped curve.From this, it is clear that two required conditions for N-shaped curve are 1>0, 2<0, 3 > 0 and b b b On the other hand, for inverted N-shaped curve, two required conditions are "1<0, 2>0 and 3 < 0 and b b b It would not be possible to estimate the environment Kuznets curve in case first condition is fulfilled but second is not.Moreover, the turning points calculated in this case, would also not be valid.However, there are various studies, that have commented upon the shape of environment Kuznets curve on the basis of the results of first condition.
To investigate the country specific relationships between urbanization, economic growth and urbanization, the study has used annual time series data for the selected Asian economies.Data for GDP per capita has been fetched from World Bank Database, Urbanization index has been used as a proxy of urbanization and data for Ecological footprint has been obtained from Global Footprint Network.
The estimation strategy for the further analysis of the models is as follows.First of all, stationarity of all the time series variables has been checked using ADF unit root test.
It is required to check the stationarity of data for all three models.Equation 14represents to first model based on intercept only.Equation 15 represents to second model based only based on intercept and trends and equation 16 represents model 3 based on no intercept and no trend.Only if the variables are stationary at their level, first difference or second difference, then co-integration test can be applied.For regression analysis, it is important to consider lagged variables in the data, therefore selection of lags is an important process of this econometric analysis.
For investigating co-integration between the variables, it is essential to identify the number of lags.This lag value is identified using Akaike Information Criterion (AIC), the Schwarz-Bayesian Information Criterion (SBIC), the Hannan-Quinn Information Criterion (HQIC), and the Sequential Likelihood Ratio (LR) methods.After calculation of a specified number of lags, regression is run.After this Johanson co-integration test is used to test the order of integration of the variables.The last step is to identify the required speed to adjust long-run values using Error Correction Term (ECT) which is based on the following cubic formation.

EMPIRICAL RESULTS
It is to make comparative analysis of the selected countries on the basis of urbanization, economic growth and environment degradation, first of all, Unit root for the key variables considered for the study i.e., urbanization, GDPPC and ecological footprint is tested using Augmented Dickey Fuller Unit root test.

ADF Test for Unit Root
It is to test the shape of Environment Kuznets curve for Urbanization-ecological footprint and GDPPC-Ecological Footprint, first of all stationarity of all three variables is tested using Augmented Dickey Fuller Test.Results in table 1 have described the stationarity of the variables at first order of integration.In all three models, no variable was stationary at level.T statistic value for all countries was smaller than critical value in every model at 5% level of significance.Therefore, first difference for each variable was calculated.After testing the stationarity of the variables, it is required to test the co-integration among the variables.To examine the co-integration among the variables, the optimum lags selected for the selected countries are from 1 to 4 which have been selected based on four different information criteria i.e., Likelihood ratio, AIC, HQI and SBIC.Table 2 exhibits the selection criteria for lag length based on the values of log likelihood, AIC and SBS obtained from VAR model.Literature on VAR modelling supports that lag length can be selected on the basis of minimum value of SBC and AIC.In case of any conflict between the values of lag length selection on the basis of AIC and SBC, then SBC should be preferred for lag length selection.In the above table, lag length selected based on minimum value of SBC for all the selected countries is shown.The existence of unit root among the variables necessitates to select appropriate tests of co-integration to test the co-integration among the variables.Therefore, Johanson co-integration test is applied to test country specific co-integration among urbanization, economic growth and environment degradation.Table 3 depicts that there exists co-integration among urbanization, economic growth and environment degradation in all selected countries for this study.The maximum value of R=2 indicates that there exist 3 co-integration equations for all selected countries.But the main focus of the chapter is to compare the selected countries on basis of urbanization, economic growth and environment degradation using environment Kuznets curve, therefore the shape of EKC is tested using ordinary least square method The results of ordinary least square estimations in table 4 shows that the value of R 2 for this model is extremely low which represents that the model is not a good fit.The wide variations between the value of R 2 indicates that the variable GDPPC is not able to explain the variation in EF per capita.Therefore, it is essential to estimate long run ordinary least square to explore the variation in Ecological footprint due to variations in GDPPC in selected Asian countries.Table 5 represented the long run ordinary least square estimation results.In this estimation vector error correction model has converted the variables into first differences automatically.The value of β4 is negative and significant for all countries which indicates that there is presence of long run causal relationship between ecological footprint and GDP per capita in these economies.The error correction term (β4) also indicates the speed of adjustment of any disequilibrium towards a long-run equilibrium state.The value of R2 ranges from 0.70 to 0.97.It indicates that the model has high predictive power for almost all the countries.High value of R 2 indicates that the model highly predictive to estimate the long run relationship between economic growth and ecological footprint.For example, in case of India, the original value of R 2 for its quadratic relationship was 5.00 but when error correct term was considered the R 2 value changes to 0.751.For the countries China, Bangladesh, Thailand, Philippines and Malaysia, the existence of linear relationship is confirmed with β1>0.It indicates that with rise in GDPPC, the size of ecological footprint of the economies is monotonically increasing with the increased pressure of human activities on the land.On the other hand, Nepal, India, Indonesia, Cambodia and Vietnam are the countries that have linear decreasing relationship with β1<0.In these countries, size of ecological footprint is decreasing with rise in GDPPC.The countries China, Bangladesh, Nepal, India and Malaysia hold EKC hypothesis with β1>0, β2<0 which indicates an inverted U-shaped relationship.According to this hypothesis, the size of ecological footprint in China increases with increase in GDPPC and after reaching a particular point, it starts declining.It is required for the government of China to focus on energy policies so that environment deterioration can be avoided after reaching the apex point.It is expected that ecological footprint in the economy would further increase due to the effect of globalization but the inverted U-shaped curve for the relationship between GDPPC and ecological footprint, it is clear that the economy would be able to be decline the ecological footprint.Innovation and technology can help the economy to overcome the negative impacts on environment.
According to World economic outlook of IMF, Bangladesh has stepped forward 14 steps from 58 th to 44 th position in the world's economies from 2014-2018.This development has certainly left tremendous amount of carbon dioxide in the environment.The main issue in the economy of Bangladesh is that urbanization is rapidly increasing but size of land is limited i.e., 148 thousand square km which has resulted into high urban density in the economy.Limited biocapacity and increasing consumption has also made the difference between ecological footprint and biocapacity widened.But adoption of environmentally sustainable technologies which can reduce the burden of global warming and ensure optimal use of natural resources can help in correcting the size of ecological footprint in the economy.
In Nepal, there exists inverted U-shaped relationship between economic growth and environment degradation.The key reason behind this inverted U-shaped relationship is that at the initial stage of development or increase in per capita income, energy consumption increases which results into release of GHG in the environment.(Andrée, et al., 2019).An inverted U-shaped EKC in India depicts that with increase in GDP per capita, energy consumption, waste disposal and emission of gases increase but with further increase in GDP per capita, people start adopting sustainable methods to dispose of the waste materials which results into less emission of GHG in the environment.The inverted U-shaped relationship between economic growth and environment in Malaysia depicts that growing GDP per capita in the economy would be a remedy for environment degradation, it would help in correcting the size of ecological footprint.
According to quadratic model, Thailand and Cambodia have U-shaped relationship between ecological footprint and economic growth.In these rapidly developing economies like Thailand, energy consumption and carbon dioxide emission are continuously increasing and consequently the size of per hectare ecological footprint is decreasing having negative impact on the environment.Therefore, environment of these economies can face extended threats of pollution with economic development as well as with resource depletion in future.
Cambodia is also a low-income economy with uncontrolled and unorganized population where it is difficult to maintain sustainability in the environment.The U-shaped curve of EKC indicates that there can be increase in the size of ecological footprint in long run, therefore, it is essential for the urban policy makers to focus on urban planning through control on the sewage, industrial waste, and solid waste which have become the major reasons of environment deterioration in the cities of Cambodia.
According to cubic polynomial model, there exists Inverted N-shaped relationship between ecological footprint and GDP per capita in Thailand only.At initial stage, the inverted N-shape curve shows the same relationship between the variables as U-shaped curve but after a certain level of growth, it starts showing a positive relationship.This inverted N shape indicates that there may be U-shaped pattern of Environment Kuznets curve at initial level but after a certain level of growth the relationship between economic growth and environment degradation may be positive.In Thailand, improved use of technology in the industry may lead to less negative impact on the environment in the long run which may lead to decline in the curve indicating the relationship between GDPPC and ecological footprint.On the other hand, N-shaped curve indicates the exitance of inverted U-shaped curve at the initial level and after reaching a particular stage of growth, the size of ecological footprint starts increasing with rise in economic growth.No country in selected sample is showing N-shape of EKC.
Though the study finds long run association between EF and GDPPC, but there are substantial variations in the degree of impact of increase in GDPPC on EF.There are several factors responsible for this heterogeneity of the relationship between ecological footprint and economic growth of selected Asian countries.Variations in the environment and energy policies of these economies is the key reason behind this heterogeneity of the relationship.Aydin et al. (2019) claimed that diverse ecosystem and endowment of natural resources of individual countries is responsible for these variations.
From the above ordinary least square estimations in table 6, it is clear that the value of R 2 in EF-URB model has wide variations, therefore, the model cannot explain the effect of variation in urbanization on ecological footprint.Therefore, it is essential to estimate long run estimations for the relationship between urbanization and ecological footprint.
In table 7, coefficient β0 refers to effect of urbanization on Ecological footprint.The value of β0 differs for every selected country for this study.β1>0 indicates that there exists increasing positive relationship between the variables i.e., increasing urbanization in the economies is also resulting into higher ecological footprint.There exists linear relationship between urbanization and ecological footprint for all selected countries.It indicates that with increase in urbanization, there is increase in the ecological footprint due to increasing pressure of human activities on the land.β1>0, β2<0 indicates an inverted U-shaped relationship.This EKC hypothesis is valid for the countries China, Malaysia and Thailand.This hypothesis states that the size of ecological footprint increases with increase in urbanization and after reaching a particular point, it starts declining.Increasing population in the economy is currently putting pressure on the land as well as on environment in China.Increasing population density is not only being a burden on land but has also increased the energy consumption in China.But inverted U-shaped curve indicates that urbanization in the economy would help in decreasing the size of ecological footprint in the long run.Innovation and technology would help the economy to overcome the negative impacts on environment.
There also exists inverted U-shaped relationship between urbanization and economic growth in Malaysia.As Malaysia is a middle-income economy, people in this country are focused on the achievement of high income, improved living conditions and profitability which has also increased consumption and waste emission.But with increasing GDP of the economy, governments are formulating policies for reducing Co2 emission, to control deforestation and for appropriate waste disposal which can reduce the size of ecological footprint in the coming years (Bekhet & Othman, 2017).
In Thailand, due to rise in population, energy consumption and carbon dioxide emission are continuously increasing the size of per hectare ecological footprint which have negative impact on the environment.But inverted U-shaped curve indicates that the Thailand's economy would be able to decrease the size of its ecological footprint in long run with controlled and organized policies for resource utilization and environment sustainability.β1<0, β2>0 indicates quadratic U-shaped relationship.The countries Cambodia, India, Indonesia, Nepal and Bangladesh are showing U-shaped relationship between urbanization and ecological footprint.β1>0, β2<0, β3>0 indicates cubic polynomial relationship and N-shaped relationship between the variables.There is no country in the selected set of countries that have N-shaped and inverted N-shaped relationship between urbanization and ecological footprint.
In Bangladesh and Indonesia, there exists, U-shaped relationship between urbanization and ecological footprint because initially, urbanization brings higher productivity because of its positive externalities and economies of scale, but at later stages, the population density in the urban areas produces negative effects.With increasing urban density, the size of per capita ecological footprint starts declining (Bekhet & Othman, 2017).
The present study also found U-shaped relationship between urbanization and environment in Nepal, Vietnam and Cambodia.Uncontrolled and unorganized manner of urbanization and lack of policies related to migration have resulted into negative impact on environment in the long run (Dong & Karmacharya, 2018).Therefore, After reaching a certain stage, urbanization starts affecting  and inappropriate waste disposal (Chen et al, 2021).Therefore, EKC hypothesis for urbanization and environment is not valid in this economy.

CoNCLUSIoN
The shape of environment Kuznets curve in selected Asian economies reflects how urbanization and economic growth of these economies affect environment of these economies.This chapter has compared the selected Asian economies on the basis of Urbanization-Ecological footprint EKC shape and Economic growth-Ecological Footprint EKC shape.The study found that EKC hypothesis is valid for China, Bangladesh, Nepal, India, Thailand and Malaysia for relationship between economic growth and ecological footprint.The main reason behind inverted U-shaped curve of EKC in these economies is that at initial level of increase in per capita income, the consumption of fossil fuel and other sources of non-renewable energy increases, but after reaching a certain level of per capita income, they become aware about the efficient use of available resources and prefer use of sustainable source of energy which can reduce the emission of GHG gases.For the countries, Philippines, Indonesia, Cambodia and Vietnam, there exists U shaped relationship between economic growth and ecological footprint.At initial stage, the growing GDPPC in the economies has positively affected the ecological footprint because of less ecological deficit in the economies, but growing urbanization, increasing inequalities, growing poverty and unemployment in the economies can negatively impact the ecological footprint in the long run.
For urbanization and ecological footprint relationship, EKC hypothesis is valid for China, Malaysia and Thailand.For the countries Bangladesh, Nepal, India, Philippines, Indonesia, Cambodia and Vietnam, the EKC hypothesis is not valid.The main reason behind this is that at higher level of urbanization, this demand of fossil fuel increases and results into high carbon emission and inappropriate waste disposal.Policies related to energy consumption in the different economies play an important role in changing the shape of EKC in these economies in future.In the economies such as China, Thailand and Malaysia, inverted U-shaped curve of urbanization and ecological footprint indicates that these countries would be able to reduce the size of ecological footprint with better policies related to energy consumption and resource utilization.
It is not only the economic development of the economy that can control the environment degradation, but the study finds that urbanization is the key factor associated with the economic activities.High level of urbanization in the economies would produce more wealth and wealthier people would demand for more energy intensive products.There would be demand for more land results into deforestation which further put pressure on the environment as well as ecological footprint.Therefore, it is required to increased urbanization also brings economies of scale through positive externalities and results into decline in environment degradation.But almost all the selected countries for this study are newly industrialized economies and a large Co 2 is released in the environment due to this industrialization process.Moreover, inequalities of urbanization and concentration of population in a few big cities in the countries such as Nepal, Cambodia, Indonesia and Bangladesh results into high population density in those areas which further increases the impact of human activities on the environment and results into bigger size of per hectare ecological footprint.

Figure 4 .
Figure 4. Possible shapes of the relationship between economic growth & environment and urbanization and environment

Table 2 . Lag selection Country Lag Lag Length Likelihood Ratio Degree of freedom P-Value AIC HQIC SBIC
Note: "Maximum lags are selected according to the AIC, HQIC and SBIC criteria."Source: Author's Computation

Table 3 . Johanson co-integration test
Note: Results shown are based on 5% significance level Source: Author's Computation

Table 6 . Ordinary least square estimations (EF-URB model)
High population density in few regions of Nepal and Cambodia is another leading reason behind this negative relationship of urbanization and environment in the long run.Urbanization in India has U shaped relationship with Ecological footprint.Low level of urbanization in the economy results into efficient use of fossil fuel energy in the residential sector.At higher level of urbanization, this demand of fossil fuel increases and results into high carbon emission