EMISSIONS IN ASEAN COUNTRIES
Pham Xuan Hoan, Nguyen Cam Nhung and Vu Thi Hien Thu' Abstract
The environmental Kuznets curve hypothesis is a theory by which the relationship between per capita GDP and per capita pollutant emissions has an inverted U shape. While impressive growth of ASEAN countries in the last few decades has significantly helped improve the people's standard of living and reduce the poverty rates, it has also exerted tremendous pressure on the environment of these countries.
The question is whether economic growth and higher income levels can eventually lead to a reduction in environmental pollution, as proposed by Environmental Kuznets curve (EKC) hypothesis The paper is to investigate the validity of EKC hypothesis for the case of carbon dioxide emissions in ASEAN countries (excluding Brunei), employing a panel data approach for ASEAN countries, using fixed effect and random effect modeling. It is found that EKC does exist for the case of these countries' carbon dioxide emissions, but with a relatively high turningpoint income (approximately $14000). This suggests that more active policy measures should be taken in the development plans of ASEAN countries so that a decline in carbon dioxide emissions would occur sooner.
'Pham Xuan Hoan, PhD., Director of Planning-Finance Department, Vietnam National University;
Nguyen Cam Nhung, PhD., Lecture and Deputy Head of Intemational Finance Department, Faculty of Intemational and Business Economics, University of Economics and Business, Vietnam National University; Vu Thi Hien Thu, BA., graduated from Faculty of Intemational and Business Economics, University of Economics and Business, Vietnam National University
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Keywords." Environmental Kuznets curve, carbon dioxide emission, ASEAN, economic growth, panel data.
1. Introduction
The Environmental Kuznets Curve hypothesis (EKC) proposes that as the economy of a country develops the degradation of the environment increases, but when the economy reaches a specific level of income per capita, known as the turning point, pollution starts to decline. This hypothesis implies that although in the early stages of development, pollution is imavoidable, in the end economic growth will be one of the solutions to the pollution problem.
In recent years, green-house gas issues have drawn more and more attention in developing ASEAN countiies. The attempts to attract foreign investment and promote intemational trade have led to rapid growth in these countries, while at the same time resulting in increased energy consumption and carbon dioxide (CO2) emissions.
Therefore, it is cracial for pohcy makers to have an informed understanding of the income-C02 relationship m ASEAN countries in the context of recent economic growth. Since little research has been conducted in this field for ASEAN countries, this paper is aimed to investigate empirically the validity of the Environmental Kuznets Curve hypothesis for carbon dioxide emissions for 10 ASEAN countries in the period between 1985 and 2010, using a non-linear model by applying pooled, fixed effect and random effect regressions. It is interesting to know if the EKC does exist in this case, what are possible reasons and what is the -tuming point" income level? This would improve our understanding of flie greenhouse gas emissions to income relationship and allow die observer to precisely know where his/her country is located along the curve, thus enabling necessary policy adjustment.
The rest of die paper is organized as follows: Section 2 reviews theory and past EKC works, section 3 details econometric methodology; Section 4 intetprets empirical findings and conclusion and policy implications are drawn in Section 5.
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2. Theory and Literature Review
EKC hypothesizes the relationship between various indicators of enviroimiental degradation and income per capita. The EKC hypothesis proposes that in the early stages of economic growth degradation and pollution increase, but beyond a certain level of income per capita (which will vary for different indicators) the trend reverses, so that at a tuming point of income levels economic growth actually leads to environmental improvement. In other words, the environmental impact indicator is an inverted U-shaped fiinction of income per capita.
A number of studies have argued that the inverted U-shape relationship is not very likely to be found in carbon dioxide emissions. The first reason is seen from a theoretical point of view: Unlike other air pollutants (such as nitrogen oxide or sulfur dioxide) which have local effects, carbon dioxide emissions cause problems on a global scale, and the social costs of global warming accme across both time and nations.
Therefore, free-rider behavior might lead to a close relationship between carbon emissions and income at all levels of per capita income, and the inverted-U relationship is less likely for carbon dioxide emissions than for the above 'tradifional' air pollutants (Arrow et al., 1995; Friedl, 2003). Moreover, in contrast to air or water pollufion, which can have immediate, identifiable local health effects, carbon dioxide emissions are locally innocuous and only impact the global environment over the long term. This causes the lack of historical regulations or taxes on carbon dioxide emissions. Indeed, until very recently carbon dioxide was not considered a harmful by-product of clean and efficient combustion and efforts to control carbon dioxide emissions have not come into effect until the last few years and have been limited to a few developed countries.
The second reason comes from analyzing consumer behavior. Wealthy consumers in developed coimtries develop a demand for a cleaner environment which leads to more stringent enviroimiental regulations and to the relocation of dirty industries abroad. The result of this is a decline in the levels of pollutants arising from production. However, pollutants arising from consumption, such as solid waste and 69
carbon dioxide emissions (arising fi-om automobile use and the burning of fossil fiiels for the generation of electricity) continue to rise because they are easily externalized and thus not subject to regulations. Carbon dioxide emissions have an impact on flie global environmem, rather tiian the immediate environment. Thus, it is not tiie case that wealthy consumers become mote conscious of the global environment; ratiier, they develop a taste for a cleaner immediate environment, hence tiie regulations tiiat are enforced on finns producing pollutants with local impacts such as sulfur dioxide and particulate matter. This suggests only the levels of these pollutants which cannot be easily extemalized decline with per capita income, whilst the levels of easily externalized pollutants such as solid waste and carbon dioxide continue to rise (Nahman et al., 2005).
Therefore, only the development-induced changes in production seem a plausible driver for a decline in carbon dioxide emissions. Hence, the existence of an inverted U-ciu-ve for carbon dioxide emissions intensity is expected to suggest that pollution reduction might occur as a natural by-product of economic development improving efficiency, especially in the use of energy (Roberts et al., 1997). This special feature of carbon dioxide emissions makes it an interesting case in EKC studies, which can provide implications for not only developed countries, but also for less developed countries.
Many contributions have empirically tested the existence of an EKC for C02.
The first empirical study about CO2 emissions is the work for the Worid Bank by Shafic and Bondyopadhyay in 1992. The authors use ten indicators as environmental quality dependent variables and they set panel regressions using data ftom 149 countries for the period 1960-1990. According to their result, income has a significant effect on all indicators of environmental quality. Most environmental indicators deteriorate initially with rising incomes but tend to improve as countries become richer. One of the
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exceptions to this pattern is carbon dioxide emissions which seem to rise monotonically as income rises.
For the case of Canada, and with respect to CO2 emissions, Lantz and Feng (2006) find that while population size has a positive effect on carbon dioxide emissions, technological or structural changes have switched its influence from negative to positive, favoring CO2 emissions intensity production for the sample period 1970-2000.
For the case of Sweden, Kander (2005) estimates a decline of CO2 emissions after 1970 due to a stabilization of energy consumption which occurred as a result of the slow growth of the economy and a substantial decline in energy intensity within the industrial sector.
Some studies attempt to include forecasts about future trends of CO2 emissions.
Galeotti and Lanza (1999) use a panel data set of 110 countries for the period 1970- 1996. Although the authors find evidence of an EKC-pattem in the case of C02emissions, they forecast that future global emissions will increase, due to the most rapid growth of per capita income in developing countries. According to the authors, income and population play a key-role in carbon dioxide emissions.
Cole (2004) tests the case of CO2 emissions among other air and water pollutants and finds an income tuming point for CO2 outside the sample income range.
Lee et al. (2009) find an evident inverted U- shape relationship between income and CO2 emissions in the case of the middle income American and European countries, but not in the case of the high or low income African, Asian and Oceania counfries for the time period 1960-2000. Aslanidis and Iranzo (2009) examine the case of non-OECD countries for the period 1971-1997 and they find no evidence of an EKC, while two regimes appear: a low income regime, where emissions increase with economic growth, and middle to high-income regime, which is associated with a decrease in enviroimiental degradation.
3. Methodology
3.1. Econometric Methodology
The model used to examine the net effect of income on carbon dioxide emissions for panel data analysis in this paper is an approximated parabolic function, with per capita income and squared terms of per capita income as explanatory variables:
ln(CO,)„ = a, + Y, +/?ilnYi, + /S^ (lnY)^, + £,-, (2)
where ln(C(?2)» represents the logarithm of per capita carbon dioxide emission, InY,, the logarithm of per capita income while 0j^&-02 are the slopes of the model, u^
and y^ are the intercept parameters, i represents the cross-section of coimtries and t denotes the years of time series, E^^ is the error occurred by cross-section (countiies) or by years on time series.
Under the EKC hypothesis, the signs of the coefficients in equation (2) are expected as follows:
ai> 0, a2< 0; D a2C « D a) D. The tuming point is y;,* = exp (— : ^ \ The paper applies the panel data analysis to detect the EKC curve between carbon dioxide emissions and income levels in ASEAN countries. The tuming point of the EKC curve is calculated based on the estimation result. Panel data helps to detect the dynamics of changes in short time series. It provides more powerfiil regression by considering the place (spatial) and the time (temporal) dimensions of the data (Basel et al.,2011).
The primary reason for using panel data is that it offers the opporhmity for controlling unobserved individual and/ or time specific heterogeneity, which may be con-elated witii the included explanatory variables. Both time series and cross-section, when combined, enhance tile quality and quamity of data in ways fliat would be impossible using only one of these two dimensions. Gujarati (2003) listed several 72
benefits for using panel data, such as it increases the precision of parameter estimates, allows us to sort out model temporal effects without aggregation bias, gives more informative data, less colinearity among variables, more efficiency, etc. Hausman and Taylor (1981) revealed that by combining time-series and cross-sectional data, individual-specific unobservable effects (may be correlated with other explanatory variables) can be controlled.
The Hausman test is used to compare between the two estimated models, the fixed effects model (FEM) and random effects model (REM). Under the null hypothesis, both FEM and REM are consistent with REM being more efficient. Under the altemative hypothesis, FEM is more efficient than REM. Therefore, the rejection of the null hypothesis will suggest for the choice of FEM (Yaffee, 2003).
3.2. Data
The panel data utilized in this paper covers the time span between 1985 and 2010, for 10 ASEAN countries (e.g. Vietnam, Laos, Cambodia, Thailand, Myanmar, Indonesia, Malaysia, Singapore and Brunei). All observations are in annual frequency.
The reason for the observation from the year 1985 onwards is that by this year most ASEAN countries have opened to the world market, carried out economic transformation and experience dramatic growth. This is compatible with the purpose of the study that is to examine the impact of economic growth on the environment.
The dependent variable - carbon dioxide emissions (CO2) is measured in mefric tons per capita. The data is collected from "World Development Indicators" on the World Bank website. The proxy of economic growth, real gross domestic product (GDP) per capita is measured by 2005 US dollars. The data on this is taken from the UNCTAD statistics. The missing data on this is obtained from the United Nation statistical databases.
4. Results
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We shall begin the analysis by presenting some descriptive statistics of variables. As can be seen ftom tables below the differences between minimum and maximum values are ratiier big for both carbon dioxide emissions and GDP per capita.
Table 1-1. Summary Statistics, 1985 - 2010, ASEAN countries Variable
Per capita carbon dioxide emissions Observation
Mean 4.1512 5.2075
Std. Dev.
6.3319 8.9440
Min 0.047 0.0792
Max 27.274 44.7037 260
Emissions measured in metric tons. GDP per capita measured in 2005 US dollars.
THE results of regression analysis of the pooled OLS model are presented in Table 1-1, and Table 1-2 represents resuhs of a regression analysis of fixed effect and random effect models. For tire three models, all estimated results reveal that linear term of income per capita and non-linear term of income per capita have positive and negative effects respectively on carbon dioxide emissions at significant levels.
However, resuhs from pooled OLS are inappropriate for discussion, since regular OLS regression does not consider heterogeneity across countries or time, and to use this model, we need to assume homoskedasticity and no serial correlation in the data. Both of these assumptions are too restrictive for the selected model.
Table 1-2. Pooled OLS
C InV (InY)' R-squared F-Statistic
Coefficient -9.7643»"
1.7651*"
-0.0519**
t-Statistic -7.53 5.08 -2.29
P-value 0.000 0.000 0.023 0.8599
487.76***
Note: *** indicates significant at 1% level, indicates significant at 10% level 74
' indicates significant at 5% level,
c
InY (InY)' R-squared
Hausman Test
Table 1-3. Fixed an i Random Effect Models Fixed Effect Model
Coefficient -8.4862***
1.9826**
-0.1039*
t-Statistic -3.69
2.84 -2.00
P-value 0.005 0.019 0.076 0.7850
p = 0.000
Random Effect Model Coefficient
-8.4413***
1.8979***
-0.0936*
t-Statistic -3.40
2.59 -1.77
P-value 0.001 0.009 0.07 0.8201
Note: *** indicates significant at 1% level, ** indicates significant at 5% level, * indicates significant at 10% level.
The result from the Hausman test suggests that the fixed effect model is more apt than random effect model (with p-value = 0.00 < 0.05). From the results of fixed effect model, it can be seen that the linear and square terms of logarithm real per capital income have positive and negative effect on logarithm carbon emissions at significant level of 5% and 10%, respectively, confirming the existence of an inverted U-shaped relationship between economic growth and environmental degradation.
Using the estimated coefficient values obtained from fixed effect model, the income tuming point for CO2 emissions in ASEAN counfries can be calculated as followed:
Y(TP) = e x p ( - ^ ) = ^^p{-7:7^^^= 13917.533 (2005 US dollars) According to this calculation in comparison with data on income per capita of 10 ASEAN countries, it can be seen that only Singapore and Brunei have reached the tuming point and started to see declining carbon emissions. While on the other hand, the 75
other eight countries' carbon emissions are expected to continue to rise until they reach a comparable level of economic development and these countiies might need a long period of growth before they can acmally reduce their carbon emissions.
5. Discussion
The existence of EKC for CO2 in this case is against the idea of Arrow et al.
(1995) and Friedl and Getzner (2003), who propose that since carbon dioxide emissions have an impact on a global scale, not local scale, free-rider behavior might lead to the inverted-U relationship being less likely for carbon dioxide emissions than for the -traditional' air pollutants, such as sulfur dioxide and nitrogen oxide.
In addition, it is worth noting that the existence of EKC for carbon emissions in ASEAN countiies should not be misinterpreted as ajustification for policy inaction, nor lead to a belief that economic growth will inevitably become a solution for all environmental problems. The panel data study is based on the assumption that the income effect is the same for all countries (Aslanidis et al., 2009). Therefore, there is no guarantee for all countries that economic growth will automatically lead to environmental improvement.
The tuming point calculated in this study ($13917.533) is relatively high for most ASEAN countries. This figure suggests that of tiie 10 ASEAN countiies, only Singapore and Brunei are standing on the right hand side of the ciu-ve, which means their carbon emissions are declining with income, while the other 8 countries with much lower income level are progressing on the left hand side of tiie curve. Since tile income levels of most of these countries are still much lower than the tuming point income level (i.e. tiiese coimtiies are standing at the lower left hand side part of tiie curve), it can be expected that their carbon dioxide emissions will continue to rise at high rates if no environmental efforts are made.
It can be seen tiiat Vietnam, in particular, is among die countries that are still progressing on flie left hand side of the U-curve. In 2012, Vietnam's real GDP per 76
capital was $1567 (millions of US dollars at 2005 constant price). Therefore, it might take decades for Vietnam to reach the tuming point of $13917.533 so tiiat the country can reduce its carbon dioxide emissions. However, this should be interpreted as an urge for more environmental awareness among policy makers. Vietnam can be a pioneer in low-carbon development if effective technological transfer policies are implemented and low-carbon investment are encouraged.
6. Conclusions
This study has shown evidence to support the EKC hypothesis for carbon dioxide emissions in the ten ASEAN countries and gives possible explanations for this.
Using the reduced-form of the EKC equation, it is calculated that the tuming point income level of ASEAN countries for carbon dioxide emission Is roughly $14,000 per capita. This result provides a projection that on average, ASEAN counfries may be able to reduce the levels of carbon dioxide emissions - the main gas contributmg to global warming - after they reach the real income per capita of approximately $14,000 - a relatively high income level compared to most of the developing ASEAN countries.
This figure suggests that of the 10 ASEAN countries, only Singapore and Brunei are standing on the right hand side of the curve, which means their carbon emissions are declining with income, while the other 8 countries with much lower income levels are progressing on the left hand side of the curve. Since the income levels of most of these countries are still much lower than the tuming point income level (i.e. these countries are standing at the lower left hand side part of the curve), it can be expected that their carbon dioxide emissions will accelerate at high rates if no environmental efforts are made. Since it takes a long time for these countries to grow to such income levels, there are also possibilities that by the time these countries reach the tuming point income level for CO2, the environmental damage may have surpassed the recovery threshold.
Therefore, these countries should begin to pay attention to reducing carbon dioxide emissions and put in place a policy and regulatory framework for low-carbon growth before damage to the environment becomes irrecoverable.
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Overall, the paper has made a modest effort to investigate the COz-income relationship in ASEAN coimtries. However, it suffers from a number of drawbacks. The major shortcoming is associated with the reduced form of the EKC equation used for this empirical investigation. The reduced-form approach to the investigation of the relationship between income levels and environmental quality has been a useful first step towards answering the question of how economic growth affects the environment.
This approach spared us the more difficult specification of structural equations and the more demanding data requirements of a more analytic approach, while it gave us a better understanding of the net effect of income on the environment. However, it is unclear which factors associated with higher income level actually affect the environment. Therefore, clear-cut pohcy implications for individual coimtries may not be possible using this approach.
Since the existence of an EKC relationship across nations today would not guarantee that global environmental degradation would decline automatically with time and economic growtii (Stem et al., 1996), the existence of an EKC relationship in ASEAN it is not Ukely to guarantee that the carbon emission levels will decline with time and economic growtii for all countries. Moreover, tiie high turning point for ASEAN countries is a warning sign that by tile time these countries achieve this income level, tiie environmental consequences of growth may have become too severe.
Therefore, an active approach toward environmental policies is vital for these countries to achieve more sustainable growth. Witii tiie accessibility of high technology today, developing countiies in ASEAN can leam from developed countries and gradually reduce tiie carbon dioxide emissions while at the same time achieve economic growth.
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