The relationship between Energy-related emissions and. economic growth: evidences from BRIC countries

Transcription

1 The relationship between Energy-related emissions and economic growth: evidences from BRIC countries

2 Acknowledgments This project would not have been possible without the helpful advice and time given by a number of people. Firstly, I would like to thank Philomena Bacon. During my dissertation period, she gave me suggestions and helpful comments which have greatly enhanced the quality of this paper. Not only the dissertation, I have also learnt lots of other knowledge from her. My English is not very good, thank you for her patient in providing guidance for me. 1

3 Contents Acknowledgments... 1 Abstract Introduction Literature review Data and Methodology Data Methodology The relationship between environmental degradation and economic growth The basic theories of environmental economy The theory of Externalities The theory of material balance Different relationships between environmental degradation and economic growth Data analysis The population and GDP of BRIC countries The World Energy Consumption GHGs emissions CO 2 emissions of EKC in BRIC countries CH4 and N2O Turning point With help of OECD countries CO 2 emissions CH 4 emissions N 2 O emissions Discussion with the help of OECD What can be learned from the BRIC countries EKC The role of national and local policy Make a better green plan Integration of existing environmental plans Structural change and production structure Migration Technological progress Research and development (R&D) Renewable energy

4 6.7 Education The levy of carbon tax Conclusion Table Contends Figure Contents Reference

5 Abstract This study mainly discusses the long-run relationship between economic growth and environmental degradation. Most studies believe that the relationship is shown as an inverted- U shaped, which called Environmental Kuznets Curve (EKC). However, the agreement still not meets. In recent year, with the detection of environmental technology, more high quality emission-related data can be obtained. And this provides us a better opportunity to study EKC. Based on previous literatures and the data of GDP, primary energy use and greenhouse gases, this study analyses the relationship of GDP per capita and energy related emissions (CO 2, CH 4 and N 2 O) in each of the BRIC countries and with OECD countries. The results suggest that it is kind of emergence for BRIC countries to change their energy structure. Also, for each of the individual country, the EKCs are not obvious, actually, it more like follow the linear-shaped. In contrast, with the help of OECD countries, an inverted-u shaped can be seen. There are two ways for OECD to help BRIC countries to balance the environment and economy: R&D investments and technology support. For BRIC countries themselves, measures such as education for energy conservation, renewable energy usage and strict environmental regulations in addition to a carbon tax can be used to protect environment without harming the economy. 4

6 1. Introduction According to the Copenhagen Accord of 2009, the world should recognize that the increase in global temperature should be below 2 C, compared to pre-industrial levels (UNFCCC, 2009). Though efforts have been paid by the world and even all pledges are fully implemented, there is still a significant gap in 2020 between 8-12 GtCO 2 e per year to reach the 2 Ctarget (UNEP, 2013). And it becomes less and less likely that the emissions gap will be closed, especially for developing countries. As a result, the increasing threat of global warming and climate changes lead to cooperation among developed and developing countries in the world. There is no doubt that environment is important to human beings, and it will become even more important in the near future. Since most of the environmental problems are raised with economic development, the relationship between environment and economy has become an important topic for researchers. As mentioned by Cato (p. xvii, 2011) Nothing is more important in the contemporary world than finding a solution to the complex and often conflictual relationship between the operation of the economy and the health of the planet. At first, people think that it is impossible to balance the environment and economy (Meadows, 1975). Choosing either environment or economy is not reality, as environment is the place we live and economic development is an eternal theme. In 1969, the idea of sustainability which suggest that it was possible to achieve economic growth without environmental damage, was raised by the World Conservation Union and it was a key theme of the United Nations Conference on the Human Environment in 1972 in Stockholm (Adams, 2006). However, it is not easy for all countries to develop sustainability. Developed countries have already finished the process of industrialization when caused most of the pollution, and on the path of sustainable development. For most less developed countries, sustainable 5

7 development is difficult, as they are now seeking to economic growth. Take the BRICS (Brazil, Russia, India, China and South Africa) for example, evidence have shown that the BRICS countries will have a large force in the world economy. They will overtake the G6, abbreviation of United States, Japan, Germany, France, Italy, and the United Kingdom, in less than 40 years (Wilson and Purushothaman, 2003). As a result, focusing on economic growth can lead great benefits to these countries. In terms of environment, the environmental issues raised by the BRICS countries rapid growth cannot be ignored. Though the five largest developing countries signed the Kyoto protocol to curb emission levels and announced the 2020 emissions reduction target under the Climate Change Convention, there are still environmental problems hidden behind the economic growth (Pao and Tsai, 2010 and Goldman Sachs, 2007). Journalists, scientists, and professors have discussed the relationship between environmental degradation and economic growth for over the past two decades. However, it still remains controversial. The most popular topic is the Environmental Kuznets Curve (EKC), which is a hypothetical inverted-u shaped relation between environmental degradation and income per capita (Stern, 1996). Previous studies of the EKC will be discussed in the literature review. This paper aims to analysis whether the inverted-u relations between environmental degradation and economic growth really exist in individual country or in a group of countries. Specifically, take the BRIC countries for example to see whether an inverted-u shaped exists in each of the BRIC countries in terms of current policies. Only Brazil, Russia, India and China will be considered in this paper based on the data collected. In addition, what the shape of the BRIC s EKC will be with the help of OECD countries will be discussed as well. It is very important to analysis the relationship between environmental degradation and economic growth in BRIC countries for a long time period. 6

8 This paper is organized as follow. Section 2 presents previous studies for the relationship between environment and economy. Section 3 discusses the data and methodologies used in this paper. Section 4 discusses the relationship between environmental degradation and economic growth in a theoretical way. Section 5 outlines the findings after the data analysis. Section 6 provides a discussion and solutions to the BRIC countries to balance the environment and economy. The final section summarizes the paper. 7

9 2. Literature review It is clear that most pollutants increasing exponentially over time. And it is influences by population, as well as the growth of industry and advances in technology. According to Meadows (1975), the pollutants related to the increasing use of energy which is the process of economic growth. In other words, the environmental quality is related to the economic growth. In this literature review, I aim to review the studies about the relationship between economic growth and greenhouse gas emissions to see what the relationship between a steady increase in incomes and environmental quality. In the past three decades, numerous studies have examined the causal relationship between economic growth and energy consumption. The role of energy in economic growth has been a controversial topic for a long time. Scholars such as Boulding (1996) claims that in the economy system, the more products produced the more natural resources are used. In the meantime, more hazardous wastes will be released in the atmosphere. The results are the same as Meadows et al (1975), who thinks economic activities require larger inputs of energy and material and produce more wastes. In other words, it results more pollution. However most of economists believe that with higher incomes, the demand for goods and service which are less material intensive will increase and more investment can be used to improve less-polluted technic (Beckerman, 1992). An increasing body of literature has assessed the evidence for both developed and developing countries in terms of the relationship between economic growth and environment degradation. In the mid-1960s, Simon Kuznets gave a hypothesis in his research: with the development of our economy, the income gap will become larger at first, and then become smaller. Take the income difference as Y-axis and income per capita as X-axis, the relationship between these two data is an inverted-u. This shape has been approved by a 8

10 large among of studies, and it is known as Kuznets s inverted-u (Kuznets, 1966). The Kuznets s inverted-u was first introduced in the area of environment by Grossman and Krueger (1991). As the advance of environmental monitoring technology, people can get more high quality environmental data. By using these data, they found that there is a relation between environmental degradation and income per capita, and then put forward as the Environmental Kuznets Curve (EKC). In other words, the environmental degradation first rises, as at this time people care more about their income and they are too poor to pay for abatement. With income rises, the effectiveness of environmental regulations, the advanced of technology and enhance their awareness, the pollution will fall with the development of economy (Panayotou, 1993). For example, compared to the data two or three decades ago, in developing countries the level of pollution has become much more serious with the economic grow while in developed countries, the environment has been improved. Reasons are summarized by Andreoni and Levinson (2001) and the World Bank s World Development Report 1992 (IBRD, 1992), (1) It may follow the natural progression of economic development, the composition of production or consumption can significantly influence the environment. (2) As pollution involves externalities, the preference for environmental quality will increase, especially in developed countries. (3) Some constraint becomes non-binding with economic growth, such as cleaner technologies. (4) Increasing returns to scale associated with pollution abatement. However, environmental degradation has many dimensions. Our lives are affected by the environment around us, the air, the water, the diversity of species and the beauty. Each of these dimensions of environmental quality may respond to economic growth in a different way. As a result, the definition of environmental degradation varies from different researches and it still a very current debate. In 1991, by altering the composition of economic activity and by bringing about a change in the techniques of production, Grossman and Krueger (1991) estimated EKCs for SO 2, finer 9

11 and darker matter and suspended particles. They find that there is an inverted-u relationship between income and environmental quality. The turning points are at $4000-$5000 per capita (in 1985$). However, at levels of $10,000-$15,000, the pollutants began to rise again. More evidences about the inverted-u relationship were found by Shafik (1994). By observing for more than 149 countries from 1960 to 1990, they found that as the increase of income the safe drinking water and sanitation have been approved. In contrast, dissolved oxygen in rivers, municipal solid wastes, and carbon emissions are worse steadily. Particulates and SO X follow the rule of an inverted-u relationship. In 1993, by using SO 2, NO X SPM and deforestation rate as indicators, Panayotou (1993) find out there is an inverted-u shaped between income per capita and environmental degradation. However, other researchers think that the data resources seem unreliable. Selden and Song (1994) examine the same two air pollutants studied by Grossman and Krueger (1991), along with NO X and CO. They find that the relationship between per capita emissions and per capita GDP of all four pollutants shows an inverted-u shaped, just similar to the researches done by Grossman and Krueger. However, more recent studies by using better data have a different results, such as Cole, et al (1997), Hannes Egli (2001), Friedl and Getzner (2003), Perman and Stern (2003) and Luzzati and Orsini (2009).Cole, et al (1997) examine the relationship between per capita income and a wide range of environmental indicators, including transport emissions of SO 2, NO 2, traffic volumes and etc. Results suggest that only local air indicators follow the rule of EKC, indicators with more global impacts either increase with income or the turning points are at high level income. In 2001, Hannes Egli uses time series data of eight pollutants for Germany to find that only for two pollutants, nitrogen oxide and ammonia can the EKC be confirmed. All other pollutants have a completely different result. He states that whether EKC really exist for a single country is not answered. Friedl and Getzner (2003) test the relationship between GDP and CO 2 emissions for a single country---austria. An N-shaped relationship is 10

12 more fit the data for the period In the same year, by using cointegration analysis, dataset of sulfur emissions and GDP data for 74 countries, Perman and Stern concluded that the EKC is a problematic concept. The same result was found by Luzzati and Orsini (2009), from estimates based on data from113 countries over the period and with attention to some shortcomings that are encountered within the EKC literature. For example the analysis includes the world as whole and also given at the pattern of single countries and not limited to developed countries. And they use different economic techniques, parametric and semi-parametric. By using three variables, total energy consumption (as an indicator), GDP and population, they find that the potential benefits of economic growth in the nature environment does not show up as there is no evidence for an energy-ekc both at the world level and at the single country level. As for developing world, where income growth is a high priority environmental pollution specially need to be carefully controlled. He and Wang (2012) analyze the impact of economic structure, development strategy and environmental regulation on the shape of EKC. They estimated for three air pollutants, NO X, SO 2 and TSP, by using data from 74 Chinese cities for the year 1991 to 2001 and found that the impacts of policy and structure variables can be nonlinear and at different development stages such policy and structure may have a different impact on environmental quality. In conclusion, there is still no agreement that the EKC exists. The relationship among energy consumption, global energy-related carbon dioxide emissions and global economy also been done by the International Energy Outlook (IEO, 2013). They present an outlook for international energy markets up to By mainly using the World Energy Projection System Plus (2013), the U.S. Energy Information Administration (EIA) predict the energy consumption and production by fuel---natural gas, liquid fuels, and coal, which is the main source of carbon dioxide emissions. The projections are divided into Organization for Economic Cooperation and Development members (OECD) and non- 11

13 members (non-oecd). More specifically, what kinds of energy and how much will be consumed by 2040 in the Business As Usual (BAU) scenario, High Economic Growth and Low Economic Growth cases are discussed. As the combustion of liquid fuels, natural gas, and coal account for much of the world s anthropogenic greenhouse gas emissions, the energy consumption in the future will have a significant influence on the global climate, global energy-related carbon dioxide emissions. However, very little efforts have been made to the EKC of BRIC countries. BRIC, the abbreviation of four countries Brazil, Russia, India and China was first introduced by O'Neill (2001). In September 2010, South Africa who joined and the abbreviation extended to BRICS. As being the largest developing countries, there is no doubt that BRICS countries are the largest energy consumers and CO 2 emitters, the relationship between energy and economic growth in BRICS countries has been a worldwide problem. The BRICS will have a large force in the world economy, as well as the environment. As a result, Forecasts of growth in BRICS energy consumption are important. Firstly, the large among of consumption in these countries will cause demand and supply imbalances which may affect the global energy markets, such as oil and coal. Secondly, the economic growth rate reflects the types of energy consumption, and this will lead to the global energy-related carbon dioxide emissions (Crompton and Wu, 2005). There are separated studies assess these four countries, however it is impossible to just put them together due to the fact that, different studies cover different time period, use different data set and different test models (Yuan et al, 2008). Pao and Tsai (2010) analyze the relationship between pollutant emissions, energy use and real output through a panel cointegration technique by BRIC countries from , expect for Russia ( ). The results are supportive of the EKC hypothesis, the 12

14 emissions increase with real output increase and then decline. They conclude that for the BRIC countries, in order to reduce CO 2 emissions without compromising their country s competitiveness, they need to increase investment in energy supply and energy efficiency. What s more, they need to set polices to encourage industries to use more environmental friendly technologies. However, the level of energy-related GHG emissions with afford of BRICs in the future not be discussed. Another study is made by Tamazian et al (2009), by analyzing not only the relationship between economic development and environmental quality but also the financial development for the period 1992 to They state that financial development may play a deterministic role in the environmental performanceas greater financial sector development can facilitate more financing at lower costs (p. 248). As a result, they selected economic development; financial development and energy control as their variables and find that financial development is associated with decline in CO 2 per capita. In other words, it confirms the EKC for BRIC countries. In conclusion, there are a large number of researches about the relationship between environmental quality and economic growth. The results vary based on the data, the time period and countries. However, for BRICS countries, limits have been done. As the BRICS countries have a substantial integration potential in their respective regions, they should not only cooperate in economics but also environmental degradation and climate change. The cooperation within BRICS can help to solve these global problems (Archive, 2011). Therefore more researches about the EKC for BRICS countries are needed. For previous studies, only a short time period been estimated and they only focus on CO 2 emissions. In my project, I will use historical data from and projection data from to estimate the EKC of CO 2, SO 2 and N 2 O. 13

15 3. Data and Methodology 3.1 Data Take the previous studies as reference, GDP will be chosen as an index of economic growth. And use emissions of CO 2, CH 4 and N 2 O to reflect the environmental pollution of BRIC countries. All of these emissions discuss in this study are energy-related and the analysis period is from 2005 to Since the data of CH 4 and N 2 O are not given directly, by using the method in 2006 IPCC Guidelines for National Greenhouse Gas Inventories, the emission data of energy-related CH 4 and N 2 O can be calculated. The original variables of this study are shown below: Primary energy consumption, including coal (Quadrillion Btu), natural gas (Trillion cubic feet), liquids (millions barrels per day), nuclear energy (Billion kilowatt hours), and renewable energy (Quadrillion of Btu) CO2 emissions from energy consumption, millions of metric tons of carbon GDP, millions of 2005 U.S. dollars Population, millions of persons Here are unit conversions which may be needed in the following section: Coal: 1 quadrillion Btu= TJ Natural gas: 1 trillion cubic feet=1.027 quadrillion Btu= TJ Liquids: 1 million barrels of liquids per day= quadrillion Btu= TJ Nuclear energy: 1 billion kwh = quadrillion Btu 14

16 The history data source (from 2005 to 2010) is the U.S. Energy Information Administration (EIA) which including the International Energy Statistics database and the International Energy Agency. The projections (from 2011 to 2040) are provided by Annual Energy Outlook 2013 (AEO 2013) and the base year for the projection is The projections in AEO 2013 are carried by the National Energy Modelling System (NEMS), which is widely used by government agencies (e.g. the U.S. Congress and Executive Office of the President) and non-government organizations (e.g. Power Research Institute and Duke University). AEO 2013 presents data projections for five cases that differ from each other due to fundamental assumptions concerning the domestic economy and world oil market: the Reference case, the Low Economic Growth case, the High Economic Growth case, the Low Oil Price case and the High Oil Price case. This study only focus on the Reference case which projections are based on existing laws and policies, and it does not assume new policies to limit GHG emissions (EIA, 2013). As mentioned above, the data collection of CH 4 and N 2 O are slightly different from CO 2 emission as there is no directly data about emissions. The emission data of CH 4 and N 2 O are calculated based on 2006 IPCC Guidelines for National Greenhouse Gas Inventories. There are three approaches to calculate the emissions, by considering the data provided Tier 1 approach can be used. Applying a Tier 1 approach estimate requires the following data for each source category and fuel: Data on the amount of fuel combusted in the source category A default emission factor And the equation, 15

17 Emissions GHG, fuel = Fuel Consumption fuel * Emission Factor GHG, fuel Where: Emission GHG, fuel = emissions of a given GHG by type of fuel (kg GHG) Fuel Consumption fuel = amount of fuel combusted (TJ) Emission Factor GHG, fuel = default emission factor of a given GHG by type of fuel (kg gas/tj). To calculate a particular GHG from different fuel, just summed over all fuels: Emissions GHG = Emissions GHG, fuel In this study, CH 4 and N 2 O emissions from coal, natural gas and liquids will be concerned. By using data of amount of fuel combusted from EIA and the default emission factors, total emissions can be calculated. Table 3.1 Default emission factor CH4 (KG/TJ) N2O (KG/TJ) Coal Natural gas Liquids Source: 2006 IPCC Guidelines for National Greenhouse Gas Inventories Most of the studies use the cross-countries cross-sectional data, which presents the countries with different income groups and different levels of pollution. If all the individual countries follow the EKC, there should be an inverted-u shaped relationship for a given acrosscountries cross-sectional data. Such as the pollution of less developed countries rises or start 16

18 to decline and that of developed countries are already falling. However, such cross-country cross-sectional data of the EKC may be misleading, and by using time series data may have a different result (Egli, 2001). Also, based on the data collected in this study, time series analysis will be used. In the following part, the model I used will be described. 3.2 Methodology In this paper, I use two methods to analyze the relationship between environmental degradation and economic growth, in theoretical aspect and in empirical aspect. For theoretical aspect, based on previous literatures I will try to find How the economic growths influence the environmental quality? What is the relationship between environmental quality and economic growth? Whether the relationship is uniqueness? And, What is Environmental Kuznets Curve (EKC)? Which factors influence the shape of EKC? For empirical aspect This aspect is based on data analysis. Firstly, data of environmental variation which influence the EKC should be collected. This includes population, primary energy consumption (coal, natural gas, liquids, nuclear and renewable energy), emissions (CO 2, CH 4 and N 2 O) and GDP for total world, BRIC countries and OECD. And then by analyzing the original data, we can see how significant BRIC countries will contribute to the world climate change in terms of energy-related emissions. After that, to test whether there is a turning point in the relationship between energyrelated emissions and GDP per capita in BRIC countries, several models estimate by the 17

19 study of Richmond and Kaufmann (2006) can be used. Eq. (1) is one of the models used by Richmond and Kaufmann to analyze the effect of income on energy use or carbon emissions. ( ) (1) However, in this study I simplified it as ( ) ( ) ( ) Where, ln is the natural log Y: Per capita energy-related emissions which transfer by primary energy use X: Per capita GDP α, β: Regression coefficients The value of β 1 and β 2 would imply a different relationship between energy-related emissions and GDP per capita. If β 1 0 and β 2 = 0, it would be a linear relationship If β 1 < 0 and β 2 > 0, it would be an U relationship If β 1 > 0 and β 2 < 0, it would be an inverted-u relationship As a result, liner and quadratic function should be considered in this study. By using the SPSS regression analyses the data of CO 2, CH 4 and N 2 O emissions in BRIC countries. And 18

20 get the results of liner, quadratic regression function, by comparing these functions to see which one is most suitable for the BRIC countries. Finally, combine each of the BRIC countries with OECD to see what will happen to the relationship between environmental degradation and economic growth.this study only focuses on a quadratic functionas I only want to know whether the BRIC countries will follow the EKC with the help of OECD countries. For example, combing the CO 2 emissions of China and OECD, the relationship between environmental degradation and economic growth may be in another shape. In this way we can see whether it is possible for the OECD to help the BRIC countries to reduce the pollution without harm the economic growth. 19

21 4. The relationship between environmental degradation and economic growth 4.1 The basic theories of environmental economy Environment is the basic of economic development, as it offers material bases to produce goods and services, as well as bears all the wastes. If people follow the rules of environment and economy, in other words, development economy in a sustainable way, people can gain the beneficial from both the environment and economy in the future. Otherwise, the environment will be seriously destroyed, in turn restricts human beings development. Following are three basic economic sources of the environmental problems The theory of Externalities It was Alfred Marshall (1890) who first introduced the theory of externalities and was improved by Pigou (1924) in the early 20 century. Externality means a consequence of an economic activity that is experienced by unrelated third parties. In terms of the effect it brings, it can be divided into positive externalities and negative externalities (Kolstad, 2011). For example, you built a beautiful garden and your neighbors can enjoy it without paying for it. This is a positive externality. Nowadays, there are more negative externalities, especially for the environmental pollutions. A steel plant produces products along with pollutions such as smoke with sulfur dioxide. The plant earns money and contributes to economy but also seriously influences the health of people live around. Also making noise in public, overdeveloping the natural resources are kind of negative externalities. In order to know better about how externality influences the environment, we should know what public good is. A good that no consumer can be excluded from using if it is supplied, and for which consumption by one consumer does not reduce the quantity available for consumption by any other. definition given by Black et al (2009). Air, fresh water, forest and 20

22 etc. most of the environment are public goods. As producers can use all of these resources for free, and without supervision agency and legislation, plants will use as many as they can in a way which can produce the most profits. In other words, environment will be polluted The theory of material balance In 1966, Boulding published a study The economics of the Coming Spaceship Earth. He says that according to the laws of thermodynamics, during the process of producing and consuming there should be a large amount of wastes. As these wastes will not disappear, they must reappear somewhere else in other forms, while designing an economic activity, people should consider the capacity of environment to absorb the waste. Though recycling and reusing can release the pressure of environmental capacity, 100% recycling is very difficult, or even impossible. In the economic system, production activities and consumption activities are following the rule of the principle of mass conservation (D`arge and Kogiku, 2014). This means after an economic activity, the amount of input from the environmental system to the economic system will be divided into two parts, wastes and accumulation in the long run. Take a zoo for example, while building a zoo, it will generate lots of wastes, and this is kind of pollution. And if we reuse the wastes, they can be back to the economic activities, this is kind of accumulation. Following are equations of the mass flow of economy and environment without recycling. In other words, there is no accumulation. The raw materials input in an economic system will become pollution outputs. R: the amount of input from the environmental system to the economic system 21

23 W: the amount of pollution input from the economic system to the environmental system W i : the amount of waste flow creating in the production sectors W f : the amount of waste flow creating in the consumption sectors F: production consumed by consumers Inputs from the environment Economic system Human Pollution Services Production Consumption Figure 4.1 The process of production and consumption without accumulation However, in the real world, there should be accumulation. As shown in Figure 5.2, the material will be reused. Not all the waste can be reused, such as waste energy which only can be used once. And as a result, any economic activity must always affect the environment (Pearce and Warford, 1993). K: substance accumulation Economic system Human Services Inputs from the environment Productio Consumption Recycling Pollution Figure 4.2 The process of production and consumption with accumulation As a result, the more we are recycling, the less wastes we produced. However, as for producers, public goods such as air, water are worthless as they do not need to pay for it and 22

24 can use as many as they want. And, if they choose to abate or to reduce the pollution, their profits will be reduced. 4.2 Different relationships between environmental degradation and economic growth The relationship between environmental degradation and economic growth has been a controversial issue for a long time. Summarized by Panayotou (1993), there are four different relationships between environmental quality and economic growth. a. Inverted-U Inverted-U is the most common results of the researches. As mentioned in the literature review, the Environmental Kuznets Curve (EKC) shows an inverted-u shaped relationship between GDP per capita and different pollutants. A set of factors responsible to shape the EKC are shown below, summarized by Dinda (2004): (1) Income elasticity of environment demand: Higher income lead people prefer a better environmental quality. People care more about the environment around them, and rich people are willing to pay more to abate the environment. The rich people not only willing to pay more for green products but also force government to set environmental regulations. This can be shown in various way, such as moving to clearer areas, or supervise their government to make more strictly environmental legislation (Selden and Song, 1994 and Carson, 1997). (2) Effect of economic scale, technology and structure: Though the scale effect which results more consumption in resource and energy, and more GHG emissions, plays a leading role at first. In other words, scale effect has a negative impact on environment. With the development of technology, old and pollution technique will be replaced by new and 23

25 clean one. As a result each unit of output consumes less energy and releases less GHG (Carson, 1997). Further, there is no doubt that industry is far more polluted than service industry. With economic structure changes, which means by transferring dirty industry to clean service industry, pollution will be reduced with economic growth (Grossman and Krueger, 1991). (3) International trade: The role of international trade shows a complicated impact on EKC. It has both negative and positive impacts on environment, which means it increases pollution and motivate reductions in it as well. Two hypothesizes can be better to explain the impacts of international trade, one is Displacement Hypothesis and the other is Pollution Haven Hypotheses. Displacement Hypothesis which means developed countries move dirty industries to less developed countries. On the other hand, Pollution Haven Hypotheses meansdirty industries move from countries with stronger environmental regulations to those with weaker environmental regulations. It is poorer countries who have weaker environmental regulations will contain all the dirty industries. Other explanation such as foreign direct investment, race to bottom, diffusion of technology, international assistance and globalization shows that free trade will increase the scale of economy which may increases pollution and it can also improve technology and with the increasing income people are willing to pay more to abate (Dinda, 2004 and Panayotou, 1993). (4) Market mechanism: Market mechanism can release the environmental pressure. This idea can be explained in four aspects. Firstly, price can solve the environmental problems. Given a higher price to natural resource can reduce their exploitation as people may not use it and shift to other cleaner energies. Economic agents play an important role in the relationship between economic growth and environmental quality as well. For example, the banker may refuse to advance credit to those that are polluting industries. In addition, 24

26 some researchers believe that a developing country that shifts from non-market to market energy resources are less polluting (Kadekodi and Agarwal, 1999). As the market rising dirty energy prices, the environment is cleaned up quickly. Finally, products should show more about their quality and production process to people. As in this way, people may refuse to buy products which do harm to our environment. Environmental awareness, education etc. can also determine the environmental quality. (5) Environmental Regulation: According to Kanjilal and Ghosh (2013), technological progress plays an important role in influencing the shape of an inverted-u since environmental impact of economic activity is greatly affected by the rate and direction of technological change. Actually it is environmental regulations that affect the EKC. Because a good environmental policy contributes to technological innovation. Incomeenvironment relationship varies across different environmental regulations. A right regulation can significantly reduce emissions, state by Hettige et al (1995). Effective environmental regulations may help flatten the EKC (Deacon, 1999 and Dinda, 2004). b. Linear relationship The first explanation of this relationship is that it is still in the state of low-economy and the turning points may exist in the future. Secondly, EKC is only suitable for individual countries. It is not for the whole world as the variables are more complicated. While using the IPAT equation, which means Impact of CO 2 emissions= Population * Affluence * Technology (Dietz and Rosa, 1997). It is clear that emissions increase as the income increase (A) which means economy cannot solve the environmental problems. c. U-shaped relationship By analyzing data for 23 countries, including 13 developed countries and 7 developing countries, from 1974 to 1989, the results indicate a U-shaped relation between the 25

27 atmospheric concentration of sulfur dioxide and GDP per capita. It is mainly because of the changes in energy use. The U-shaped relationship can be led by changing in economic activities and policies (Kaufmann et al, 1998). More U-shaped relationship can be found in Khanna (2002). d. N-shaped relationship By using the throughout indicator (TI) which present the environmental pressure, to analysis the EKC of 19 countries, De Bruyn and Opschoo (1997) suggest that in the medium long term, the relationships between environment and economy may be N-shaped. And the N- shaped relationship may implies that due to adoption of new technology, one pollutant may decline but another may rise (Dinda, p. 445, 2004). More evidences of N-shaped relationship can be found in Grossman and Krueger (1991), Grossman and Krueger (1995) and Bruyn and Opschoor (1997). Though EKC is the most common result for most studies, as it is a long run phenomenon, there is still no agreement whether the relationship between economic growth and environmental degradation follow the EKC (Dinda, 2004). In the following section, I discuss the emergency environmental problems that the BRIC countries will contribute to the World, and whether EKCs exist in these countries. 26

28 5. Data analysis 5.1 The population and GDP of BRIC countries In this study, I will only focus on the former BRIC countries, Brazil, Russia, India and China. As the data of South Africa are not included in EIA, using another database may influence the results. The group has a population exceeding 42% of the world s total population and their GDP accounted for more than 10% of world GDP in 2005 (World Bank). For a long time trend, the population of Russia and Brazil stay steadily, around 200 million. In contrast, China will reach at its maximum in 2020 at about 1400 million and in the same year India will overtake China, become the largest population country in the world. After that, the population of India still keeps on increasing and will reach 1600 million before As for GDP, an increasing trend can be seen in all of these four countries, especially in China. Details are shown in Figure 5.1 to Figure 5.3. Many previous studies such as Lee (2005) have shown that high economic growth will always lead to high energy consumption which may results to pollution. What s more, population is another important factor which may lead to high energy consumption. Russia 3% Rest of World 50% China 24% India 20% Brazil 3% Figuer 5.1 The percentage of population,

29 Millions Russia China India Brazil Figure 5.2 The growth of population, BRIC, $ (* 10 5 ) Russia China India Brazil Figure 5.3 GDP growth rate, BRIC, The World Energy Consumption BRICS demand for energy has risen drastically over the past decade years. In 2005, they accounted for 50.2% of the world s coal consumption, 18% of liquid consumption, and 18.1% of gas consumption. From 2005 to 2040, the demand for energy consumption will increase significantly. As shown in Figure 5.4, the total energy demand will rise from Quadrillion Btu to Quadrillion Btu and most of them are contributed by the 28

30 BRICs. At the end of 2040, the BRICs will account for more than 40% of the world total energy consumption. The total energy demand for coal increase significant and most of them are contributed by China. Increasing from approximately 50 quadrillion Btu in 2005 to 120 quadrillion Btu in 2040 though with a slightly decreases in the last five years. The total coal consumption in BRIC countries is far more than the rest of world, rise by quadrillion Btu in the Reference case. Since coal is a dirty fuel which is the most carbon-intensive fuel, the large demand for coal in BRIC countries will lead to a large amount of CO 2 emissions (Kanjilaland Ghosh, 2013). The total demand for liquids, natural gas and renewable energy in rest of world are larger than BRIC countries. Specifically, Russia accounts for the largest amount of natural gas consumption during this whole period compare to other BRIC countries. It may be because Russia has the largest natural gas reserves which account for about a quarter of the world s total reserves (EIA, 2014). However, a rapid increasing trend can be seen in China, rising from only 2 trillion cubic feet to 18 trillion cubic feet, almost overtake Russia. A slightly increase can be seen in both India and Brazil. For liquids consumption, the demand for rest of world almost 3 times larger than BRIC countries, nevertheless, the increasing rate of total BRIC countries is faster than rest of world. For the nuclear energy consumption, the demand for it increase slightly compare to other energy, about 10 quadrillion Btu. However, 66% is contributed by the BRICs that is primary because in 2005, rest of world especially OECD consumed billion kilowatthours while the BRICs account for only billion kilowatthours. It is 10 times smaller than rest of world. China is increasing specifically faster from 2010 to More detail can be seen in Figure 6.4 to Figure

31 Quadrillion Btu Rest of World OECD BRICs Figure 5.4 World total primary energy consumption in the Reference case Renewable energy consumption Nuclear energy consumption Natural gas Liquids Coal OECD BRIC Rest of world Figure 5.5 Increased primary energy demands in Reference case,

32 Trillion cubic feet Quadrillion Btu Russia China India Brazil Rest of World Figure 5.6 World coal consumption Russia China India Brazil Rest of World 0Rest of Rest of World Figure 5.7 World natural gas consumption Million barrels per day Russia China India Brazil REST of World Rest of World Figure 5.8 World liquids consumption 31

33 Billion Kilowatt hours Russia China India Brazil Rest of World rest of world Figure 5.9 World nuclear energy consumption Quadrillion Btu Russia China India Brazil Rest of World Rest of World Figure 5.10 World renewable energy consumption Energy consumption and GHGs emissions has a strong relation. There are studies shows that higher levels in energy consumption increase per capita emissions. In other words, energy has a positive impact on emissions (Tamazian et al, 2008 and Pao and Tsai, 2010). As these energies account for much of the world s anthropogenic greenhouse gas emissions, the energy consumption for them in the future will significantly contribute to the environmental problem of global warming. Though the BRICs have signed the Kyoto Protocol to curb emission levels and announced the 2020 emissions reduction targets under the Climate Change Convention. Under the Kyoto 32

34 Protocol Brazil and Russia committed to reducing its greenhouse gas emissions by to 38.9% and 25% below BAU by 2020 respectively. India reduce emission intensity of GDP by 20 to 25% by 2020 in comparison to the 2005 level and China, which share the largest among of global emissions, committed to lower CO 2 emissions per unit of GDP by 40-45% by 2020 compared to the 2005 level. To achieve this GHG reduction target, the ChineseGovernment s pledge is to increase share of non-fossil fuels in primary energy consumption to around 15%, increase forest coverage by 40 million hectares and forest stock volume by 1.3 billion cubic meters by 2020 from 2005 levels (UNFCCC). There are still environmental problems hidden behind the economic growth. Therefore, the BRICS should take concerted action to relieve the tension of emissions reduction. Plus, the BRICS may become one of the most important bargaining powers in the future climate change meeting and can have a word for the less developing countries. In the following part, I will only focus on the CO 2, CH 4 and N 2 O emissions of three primary energy, coal, natural gas and liquids as they account for most of the sources of energy and release the largest amount of GHGs. By using SPSS regression analysis to see what is the relationship between emissions and GDP for BRIC countries. 5.3 GHGs emissions While estimating EKC, most models use income per capita or purchasing power parity (PPP) as independent variable. Others prefer incomes at market exchange rates. Some models use emissions of a particular pollutant such as Schmalensee et al (1998) and Sachs et al (1999) while others use ambient concentrations of various pollutants. The variations I choose in this study is data of GDP per capita and emissions of GHGs, specifically, CO 2, CH 4 and N 2 O. The main reason why choosing these three pollution is because they are the first three greenhouse 33

35 gases and are released by burning fossil fuels. Furthermore, they are all limited by the Kyoto protocol. By using data of GDP per capita and emissions of GHGs and with the help of SPSS regression analysis, the regression equation of these two variations can be produced. This study aims to analyze three types of GHGs, CO 2, CH 4 and N 2 O CO 2 emissions of EKC in BRIC countries Carbon dioxide emission, which is the most important GHGs, is the primary reason for the global warming. Among several environmental pollutants, CO 2 emissions were held responsible for 58.8% of the GHG (The World Bank, 2007a). It is clear that CO 2 emissions from energy use are dependent on three factors, the carbon content of the fossil fuel, the fraction of the fuel consumed in combustion, and the consumption of that fuel. The economic growth rate which is measured by the growth in GDP is an important determinant of growth in the demand for energy. In other words, high economic growth rate will lead to high demand for energy. And high demand for energy will lead to different levels of emissions. There are many factors influence carbon dioxide emissions, as we can see from the Kaya Identity which is used to explain the historical trends and future projections of energy-related carbon dioxide emissions, expresses total carbon dioxide emissions as the product of (1) carbon intensity of energy supply, (2) energy intensity of economic activity, (3) economic output per capita, and (4) population. The equation is shown below: CO 2 = (CO 2 /E)*(E/GDP)*(GDP/POP)*POP This equation is used in the IEO 2013 to project the energy-related carbon dioxide emissions. As for CO 2 emission, the projection data are from IEO

36 The carbon intensity of energy supply (CO 2 /E) is a measure of the amount of carbon dioxide associated with each unit of energy used. As different energy has different carbon-intensive, it can be easily effect by the changes in energy usage. The most carbon-intensive fuel is coal, and then followed by oil and natural gas. Nuclear power almost has zero carbon dioxide emissions. A decline in the carbon intensity can indicate people use less energy, or they use less carbon-intensive fossil fuels, more renewable energy are being used. If people use more energy with the demand of economic growth, but instead of using coal, they use less carbonintensive fossil fuels, among of CO 2 emissions can be the same. The energy intensity of economic activity (E/GDP) relates energy consumption to changes in economic output. It can be used to measure the energy efficiency. For example, if an old company is replaced by a new one which can supply the same among of electricity by using less energy, it reduces the energy intensity. Energy intensity is affected by structural changes with an economy. Countries with larger service sectors seem to have lower energy intensities while countries with industries which need higher level of energy such as oil and natural gas may have higher energy intensity. The carbon intensity of economic output (GDP/POP) is used in analysis of changes in carbon dioxide emissions. In addition, it sometimes used as a measure for tracking progress in relative emissions reductions. And it is the most primary factor in the Kaya Identity equation. Figure 5.11 shows the Kaya factors of BRIC countries. Identify energy intensity, carbon intensity, GDP per capita and population in 2005 equal to 1. The increasing or decreasing trends compare to 2005 of these four factors are clear. GDP per capita has the sharpest increases. As the population of BRIC countries increasing slightly, we can know that the GDP of these four countries rise significantly. In contrast, both energy intensity and carbon intensity decrease. A decline in the carbon intensity shows us that the BRIC countries may 35

37 use less energy or use less carbon-intensive fossil fuels. As people use more energy with the demand of economic growth, the decline indicates that the BRIC countries use more nuclear energy and renewable energy than before. The index of carbon intensity makes it easy for BRIC countries to monitor emissions and take suitable steps for balancing environmental quality and economic growth (Wang et al, 2012). It may be a more appropriate for developing countries to reduce CO 2 emissions (Jotzo, 2006). The energy intensity can be used to measure the energy efficiency. It is good news to see that the energy intensity will be decreasing compared to 2005 as reduced energy consumption per unit of GDP is environmentally beneficial (Pearce and Warford, 1993). For example, in order to earn the same amount of money developed countries can offer services which do less harm the environment while less developed countries can only build factories to produce products. Or improving technology can also reduce the energy intensity. Therefore, a decline of energy intensity indicates that in the last three decades, BRIC countries will change their economic structures or improve their technologies so that they can produce the same amount of products with less energy Index, 2005= Energy intensity Carbon intensity GDP per capita Figure 5.11 Kaya factors of BRIC countries 36

38 25000 Million metric tonnes carbon dioxide OECD BRIC Rest of World Figure 5.12 World carbon dioxide emissions by region Energy-related carbon dioxide emissions, which produced through the combustion of coal, natural gas and liquids account for most of the world s anthropogenic greenhouse gas emissions. In the Reference case, energy-related carbon dioxide emissions in BRIC will exceed OECD in the year 2013 and the gap between OECD and BRIC will become larger. That is because the BRIC continue to rely on coal to meet their energy demand. Specifically, Increasing from million metric tons in 2005, the energy-related carbon dioxide emissions will reach million metric tons in 2040 in terms of the Reference case. And most of the emissions were contributed by non-oecd nations, with China Million metric tons, Russia 2018 Million metric tons, India 3326 Million metric tons and Brazil 771 Million metric tons in 2040, account for 46.2% of the world total energy-related carbon dioxide emissions. As shown in Figure

39 Billion Kilowatthours BRIC OECD 8000 Rest of World Figure 5.13World net coal-fired electricity generation from central producers by region and country in the Reference case As mentioned above, the energy demand for coal which is the most carbon-intensive fossil fuel, in BRIC is most significant. Coal will become the leading source of world energyrelated carbon dioxide emissions. Surprisingly, as shown in Figure 6.13 base on current policies, in the future most of the electricity generation is reliant on coal-fired facilitiesinbric countries. From only 3000 Billion Kilowatt hours in 2005 to Billion Kilowatt hours in 2040, most of the coal will be consumed to generated electricity. Specifically, China and India dependent on coal for electricity generation, they account for a large amount of percentages. In contrast, the coal consumption which used to generate electricity remains the same for rest of world. In conclusion, though the carbon intensity and energy intensity both reduce in BRIC countries, the amount of carbon dioxide emissions still increases significantly. That is primary because BRIC countries, especially China use a large amount of coal to generate electricity. As a result, to see whether the CO 2 emissions follow the EKC is important. If it follows the inverted-u shape, we need to make new policies or develop new technologies to 38

40 let the peak happen earlier and the amount of emissions smaller. If it follows the liner shape, the world is in a more emergency situation, more efforts should be made in BRIC countries. By using SPSS to analyze the data of CO 2 emission per capita and GDP per capita, the details of regression functions are shown in Table 5.1. And all the data below are in Log. Table 5.1 the regression functions of CO 2 emission per capita and GDP per capita in BRICs Brazil Russia India China Coefficient Std. Coefficient Std. Coefficient Std. Coefficient Std. Error Error Error Error Constant -9, X X N R F Stat Following are the regression functions for each country: Brazil: y = * x Russia: y = * x 39

41 India: y = * x China: y = * x * x 2 As we can see from the Figure 5.14 to Figure 5.17, the CO 2 emissions from 2005 to 2040 in Brazil, Russia and India are growing rapidly, and they all show a linear relationship. The trend in China seems to decline somewhere between 40 thousands GDP per capita. In other word, the turning point occurs at the end of 2040, where GDP per capita is $40,000. For Brazil and India, the turning point cannot be seen maybe is because in this period (from 2005 to 2040), their per capita GDP do not meet 40 thousands. In the estimated period, with 1% increase in GDP, the CO 2 emissions of BRIC countries are increasing 2.853%, 0.375%, 0.310% and 3.107% respectively. Though increasing rate of China is the largest at first, it will slow down in the future. Figure 5.14 The relationship between CO 2 emissions and GDP per capita, Brazil,

42 Figure 5.15 The relationship between CO 2 emissions and GDP per capita, Russia, Figure 5.16 The relationship between CO 2 emissions and GDP per capita, India, Figure 5.17 The relationship between CO 2 emissions and GDP per capita, China,

43 5.3.2 CH4 and N2O CH 4 and N 2 O are the second and third most significant greenhouse gases respectively. The contribution of N 2 O to the climate change can be 300 times larger than CO 2. Table 5.2 and Table 5.3 show the details of regression functions for CH 4 and N 2 O respectively. Table 5.2 The regression functions of CH 4 emission per capita and GDP per capita in BRICs Brazil Russia India China Coefficient Std. Coefficient Std. Coefficient Std. Coefficient Std. Error Error Error Error Constant X * X N R F Stat Following are the CH 4 regression functions for each country: Brazil: y = * x 42

44 Russia: y = * x India: y = * x China: y = * x * x 2 Figure 5.18 The relationship between CH 4 emissions and GDP per capita, Brazil, Figure 5.19 The relationship between CH 4 emissions and GDP per capita, Russia,

45 Figure 5.20 The relationship between CH 4 emissions and GDP per capita, India, Figure 5.21 The relationship between CH 4 emissions and GDP per capita, China, For CH 4 emissions and N 2 O emissions, a quadratic function can be seen in China. Similar to CO 2 emissions, it may reach the peak at around $40,000 per capita GDP. Only a linear relationship is obvious for CH 4 and N 2 O emission in other three countries, a sharp increasing from 2005 to That is primary because the GDP per capita have not meet $40,000 for Brazil and India in the estimated period. However, for Russia, though in 2040, the GDP per capita is around $40,000, the emission of N 2 O is still increasing. With 1% increases in GDP 44

46 per capita, Brazil increases 0.99% of CH 4, Russia increases 0.387% and India increases 0.277%. For CH 4, with 1% increases in GDP per capita, it increases 0.767%, 0.373% and 0.261% respectively. Table 5.3 The regression functions of N 2 O emission per capita and GDP per capita in BRICs Brazil Russia India China Coefficient Std. Coefficient Std. Coefficient Std. Coefficient Std. Error Error Error Error Constant X X N R F Stat , Following are the N 2 O regression functions for each country: Brazil: y = * x Russia: y = * x 45

47 India: y = * x China: y = * x * x 2 Figure 5.22 The relationship between N 2 O emissions and GDP per capita, Brazil, Figure 5.23 The relationship between N 2 O emissions and GDP per capita, Russia,

48 Figure 5.24 The relationship between N 2 O emissions and GDP per capita, India, Figure 5.25 The relationship between N 2 O emissions and GDP per capita, China, Turning point As we can see from the figures, the relationships between emissions and GDP are various. There are three cases for all of these emissions for BRIC countries. Firstly, the increasing rate of pollution is decreasing, and turning point can be seen almost at the end of 2040 with GDP 47

49 per capita around $40,000. Secondly, though the GDP per capita reaches $40,000, the turning point cannot be seen. Thirdly, the emissions are increasing shapely with the GDP grow, and it seems that the turning point will not happen in the near future. All the emissions in China belong to the first case, the turning point will occur when the GDP per capita reaches $40,000 in China. As for emissions in Russia, though the GDP per capita reaches $40,000, the turning point is not happened. However, with GDP grow the emission increasing is slower than before. A turning point can be seen in the near future. As a result, it belongs to the second case. All others belong to the third case as a turning point cannot be estimated in the near future. If there is an EKC for individual country, the results above indicate that the BRIC countries are still in the first stage of EKC which is environmental degradation increasing with GDP growth. However, Egli (2001) by using time series for Germany proves that the EKC not exist in individual country, which is the same as this paper. There is another explanation that the turning point cannot be seen during this period in BRIC countries is because of the income inequitable. The EKC emerges in high income countries if and only if economic growth does not lead to a large increase in income inequality. concluded by Magnani (2000 p, 442). India and Brazil is one of the world s most inequitable societies with 36% and 23% of the population below the poverty line respectively (Peter, 2007). The results show that economic growth has significant impact on per capita GHGs emissions. Emissions do not addressed by GDP growth, instead, GDP lead to a more serious emission. Though for CO 2, CH 4 and N 2 O, it is vary from different countries. Perhaps it is because the relationship of GDP per capita and emissions is influenced by other factors such as education, population or cultural background. 48

50 5.4 With help of OECD countries In this section, in order to see whether the relationship between economic growth and environmental degradation will follow the EKC with the help of OECD countries, the SPSS regression of emissions for each BRIC countries with OECD will be done. And I will simply estimate whether it follows an inverted-u shaped. Following are the regression results for the relationship between economic growth and environmental degradation of each of the BRIC countries with the help of OECD CO 2 emissions Figure 5.26 to Figure 5.29 show the relationship between CO 2 emissions and GDP per capita. Table 5.4 illustrates the details of the regression functions. By doing the quadratic analysis, with the help of OECD, the relationships between economic growth and environment quality follow the EKC. All of the R square of regression functions are more than 0.5, with Brazil and India larger than 0.7. In other words, the results are quite reliable. It is clear that the turning point is around $ $ for all the cases. Figure 5.26 The relationship between CO 2 emissions and GDP, Brazil and OECD,

51 Figure 5.27 The relationship between CO 2 emissions and GDP, Russia and OECD, Figure 5.28 The relationship between CO 2 emissions and GDP, India and OECD, Figure 5.29 The relationship between CO 2 emissions and GDP, China and OECD,

52 Table 5.4 Details of the regression functions, CO 2, with OECD countries Brazil Russia India China Coefficient Std. Coefficient Std. Coefficient Std. Coefficient Std. Error Error Error Error Constant X X N R F Stat CH 4 emissions In contrast, there is a significant difference between each BRIC countries in terms of CH 4 emissions. An inverted-u shaped can be seen in Brazil, Russia and China with the peak around $60,000. However, the R squares of them are not very significant, with Brazil 0.367, Russia and China Compared with these three countries, even with the help of OECD countries, India does not show an inverted- U shaped from 2005 to

53 Figure 5.30 The relationship between CH 4 emissions and GDP, Brazil and OECD, Figure 5.31 The relationship between CH 4 emissions and GDP, Russia and OECD,

54 Figure 5.32 The relationship between CH 4 emissions and GDP, India and OECD, Figure 5.33 The relationship between CH4 emissions and GDP, China and OECD,

55 Table 5.5 Details of the regression functions, CH 4, with OECD countries Brazil Russia India China Coefficient Std. Coefficient Std. Coefficient Std. Coefficient Std. Error Error Error Error Constant X X * N R F Stat N 2 O emissions In terms of N 2 O emissions, all of the BRIC countries are not follow the EKC. The R squares for all of them are smaller than 0.5, with Brazil 0.071, Russia 0.294, India and China As shown in Figure 5.34 to Figure 5.37 and Table

56 Figure 5.34 The relationship between N 2 O emissions and GDP, Brazil and OECD, Figure 5.35 The relationship between N 2 O emissions and GDP, Russia and OECD,