本文是一篇Paper代写范文，题目为The Association between the Economic Growth and the Air Pollution:A Case Study of China，主要讨论了中国经济增长与空气污染的关系。范文内容和格式仅供留学生参考学习，不得抄袭，如有Paper代写需要，请联系网站客服。
I Introduction引言
The environmental damages due to the human activities have become a significant concern. The survival and development of humans are highly dependent on the natural resources and the ecological systems that are provided by the planet. The debate between economic activities and the environmental quality has been standing for a long time. A great many of the literature concentrate on this topic. Economists gathered large sample data about the environment of different countries, finding that the environmental quality initially deteriorated and the then improved as the levels of income and consumption increase. The correlation between the economic growth and the quality of the environment is still controversial.
人类活动对环境的破坏已成为人们关注的重要问题。人类的生存和发展高度依赖于地球提供的自然资源和生态系统。经济活动与环境质量的争论由来已久。许多文献都集中在这个问题上。经济学家收集了大量关于不同国家环境的样本数据，发现随着收入和消费水平的提高，环境质量先是恶化，后是改善。经济增长与环境质量之间的关系仍有争议。
Environmental pollution mainly occurs in the process of the industrialization and the urbanization. Because of the detriments of the environmental pollution (such as air pollution), humans are increasingly realizing the importance of the environmental quality. China, as one of the most fast-growing countries in terms of the economic development, has not done well in the protection of the environment. The growth of economy is across the country, but the growth of cities in China is at the expense of the environmental pollution (e.g. air pollution). The growth of China has shocked the rest of world, but the pressure on environment due to the rapid growth is enormous.
人类活动对环境的破坏已成为人们关注的重要问题。人类的生存和发展高度依赖于地球提供的自然资源和生态系统。经济活动与环境质量的争论由来已久。许多文献都集中在这个问题上。经济学家收集了大量关于不同国家环境的样本数据，发现随着收入和消费水平的提高，环境质量先是恶化，后是改善。经济增长与环境质量之间的关系仍有争议。
. Thus, the main goal and the motivation of this paper are to provide empirical evidence on this topic. Moreover, this paper attempts to examine the Environmental Kuznets Curves (EKC) hypothesis. A wide variety of empirical studies on the relationship between prosperity and the environmental quality leads to heterogeneous outputs. The results from one country may vary from another one. It is not sure that whether the EKC is applicable for every country, especially for the emerging countries such as China which presents a different growth pattern. In short, the research on China in this topic will contribute to the existing EKC researches. More specifically, the research questions of this paper are presented as the following:
· What is the association between the economic growth and the air pollution in China?
· Whether EKC depicts the relationship in China?
In addition, this research pays the close attention to the period of 2001 -2010 in which China demonstrated tremendous growth. The structure of this paper is shown as the following. Chapter 1 introduces the motivation and the research questions of the paper; Chapter 2 presents the background information about China; Chapter 3 presents the literature review about the theme of this research; Chapter 4 describes the methodology of the paper, including the data selection and the model specification; Chapter 5 presents the results from data analysis; Chapter 6 is the conclusion.
II Background背景
2.1 Chinese Economic Growth中国经济发展
During the past decade, the average annual GDP of China is over 10% due to the effective economic policies. The overall increase in the national economic significantly improves the living standard of Chinese people. Along with the development of the economy, the infrastructure is also developed. The industrial structure of China has been experiencing changes as well, from the emphasis of manufacturing to the services and information industries. In response to the most recent financial crisis, China adopted a bundle of measures to promote the domestic demand and contribute to the recovery of the world’s sluggish economy. The following table gives a more direct depiction of the economic development of China.
| Year | Agriculture | Industry | Service | per capital GDP (Yuan) |
| 2001 | 14.30% | 45.20% | 40.50% | 8622 |
| 2002 | 13.70% | 44.80% | 41.50% | 9398 |
| 2003 | 12.80% | 46.00% | 41.20% | 10542 |
| 2004 | 13.40% | 46.20% | 40.40% | 12336 |
| 2005 | 12.10% | 47.40% | 40.50% | 14185 |
| 2006 | 11.10% | 47.90% | 40.90% | 16500 |
| 2007 | 10.80% | 47.30% | 41.90% | 20169 |
| 2008 | 10.70% | 47.40% | 41.80% | 23708 |
| 2009 | 10.30% | 46.20% | 43.40% | 25608 |
| 2010 | 10.10% | 46.80% | 43.10% | 29992 |
Source: China Statistic Year Book 2006-2010
It can be seen from Table 1 that the proportion of agriculture in the total GDP of China decreased over time while the contribution of service industry to the GDP increased over the period. The contribution of industry sector to the GDP of China increased at first and then showed a slight decline and remained stable later. This indicates the shift of industrial structure in China. In addition, the GDP per capital in China presented the overall upward trend from 2006 to 2010, indicating the significant achievement of China in the economic fields.
3.2 Air Pollution
Along with the development of economy in China, environmental quality has been improved than before. But the environmental pollution has become serious in the major cities of China. The dispatch between the economic growth and the environmental quality becomes obvious since the government of China has not paid enough attention for the environmental problems. More specifically, the airborne pollution in China comes from the emission of coal combustion and the particulates. In China, the air quality monitoring is conducted in main counties and cities, including the monitoring of sulfur dioxide, particulate matters and Nitrogen Dioxide. Let’s take the acid rain for an example. On the basis of the China Environmental Statistic Book (2012), there are more than half of the 494 cities in China that experienced the acid rain. In addition, more than thirty percentages of the cities reported that the frequency of the acid rain was more than 25% and about 11% of the cities reported that the frequency of the acid rain was more than 75%. In addition, in the past years, China has done limited efforts to protect the environment.
III Literature Review文献综述
3.1 Empirical Studies on EKC
Many studies identify the correlation between the growth of income and the environmental quality. More specifically, when the environmental quality deteriorates at the initial process as the economy rises, but the pollution in the environment eventually declines with the continuous increase in the prosperity (Grossman and Krueger, 1995; Hilton and Levinson, 1998; Shafik, 1994). This implicates that the deterioration in the developing countries could be temporary and probably due to the less advanced technology in production and the in the environmental protection. This implication comes from two aspects: on the one hand, along with the increase in the income, people are becoming more and more care the quality of the environment where they live in; on the other hand, as the development in economy, the change in the industrial structure from the focus on manufacturing industry to the services and information industries also contribute to the recovery of the environmental quality.
The study of Harbaugh et al. (2002) is an expansion of the study of Grossman and Krueger (1995). In their study, they point out that the selection of the sample countries will affect the relationship depicted in EKC. More specifically, they find that the choice of data and model production would affect the results of EKC and thus, they recommend that the future research on this topic should be narrowed into countries with similar characteristics rather than to achieve a universal outcome towards the relationship between the economic growth and the environmental quality (the environmental pollution).
The central of the EKC is the association between the income level and the environmental quality. But the study of Torras and Boyce (1998) find that the income inequality has the similar effect in the equality of environment. In their study, they replaced the quadratic function with cubic function. By doing so, the downturn in pollution followed by later upturn is allowed. Their study implies that the high income would have the opposite effect on the environmental quality when the level of income reached a certain level. The advancement in technology may explain the downturn in pollution followed by later upturn.
But there is a problem in the study of Torras and Boyce (1998): the ambiguity between the income inequality which is measured by the Gini coefficients and the environmental quality. The study of Boyce (1994) identify the adverse effect of income inequality on the environmental quality while the study of Scruggs (1998) point out that the equality hypothesis of Boyce (1994)’s study is questionable and suggests that the income inequality is not correlated with the environmental pollution. Thus, with this kind of consideration, the income inequality is not taken as an explanatory variable in the present study.
Moreover, the study of Borghesi (1999) points out that the stage of the development in the economy will also affect the use of the natural resources and thus shows the influence on the EKC. More specifically, Borghesi (1999) argues that countries engage in the significant exploitation of the natural resources at their initial development phase. Thus, the pressure on the environment is enormous and the quality of environment is exposed to the negative effect of the exploitation of the natural resources. Along with the development, the increase in the costs of the use of natural resources results in a reduction of the exploitation and accelerates the shift towards the industries environmentally friendly.
In addition, the study of Yandle et al. (2004) also put efforts in the explanation of the shape of EKC. The explanation under their study is very interest. They argue that the pursuit of environmental quality is a luxury good as the income goes up. They point out that “the income elasticity of demand for environmental resources varies with the level of income”. It is apparent that the income elasticity in the early development phase is much lower than that in the latter development stage. After a certain level, the demand of high quality environment for people is higher than that of the demand for higher income. The increasing demand for high quality environment reduce the deterioration of the environment and hence the improvement in the environment.
The shape of EKC varies in the empirical studies. In contrast to the traditional bell shape, Peters and Murray (2006) identify a “L” shaped EKC. More specifically, their study collected the data of air quality and Gross National Income (GNI) for Asian cities and the proxies of quality include PM-10, CO, SO2, and NO2. Their study may be indicative that the “pre-pollution” stage is not appropriately applicable to the countries in Asia. The presence of SO2 decreased at GNI of $ 520 US dollars per capita but the presence of NO had no significant impact on the EKC. The PM-10 and CO both decreased when the GNI reached $ 500 US dollars per capita. This study may imply that Asian countries might not follow the typical EKC shape.
3.2 Empirical Studies in China
The study of Ma and Li (2006) use the data from 1986 to 2003 to analyze the EKC of industrial wastes, including the water, gas and solid wastes. Their study reached a conclusion that the pollution of environment in China will not automatically decrease when the economic growth of China goes up over time period when they applied the time series method. The conclusion of their study is associated with the conclusion that is achieved by Zhang et al. (1999), which argues that the relationship between the economic growth and the environmental pollution only shows the very weak EKC characteristics. This indicates that the examination about whether the relationship between the economic growth and the environmental pollution in China follows the EKC through using the updated data.
Peng and Bao (2006), on the basis of the panel data on 30 provinces in mainland China during the period of 1996-2002, investigate the correlation between the environmental quality and the income per capita. In their study, they find that the correlation between the environmental quality and the income per capita is highly sensitive for the choice of the pollution indicators and the functional forms. In addition, their model takes social factors into consideration. They suggest that the change in population density and the trade openness and environmental policies and laws all affect the EKC. Fu (2008) also reaches the same suggestion that the change in industrial structure will affect the characteristics of EKC.
3.3 Summary
On the basis of the literature review, the correlation between the economic growth and the environmental pollution might not follow the pattern assumed by EKC. Thus, this paper has two main tasks: first of all, it will examine whether the EKC model exist in China and secondly identify where the pollution begins to decline in China. More importantly, this paper utilized more recent data (the period of 2006-2010) and the data set is more correlated with the economic growth in China. Since 2006 when China joined the World Trade Organization, the country has experienced tremendous growth. The urbanization and the industrialization develop into a new level and the income of Chinese people also experience tremendous increase. It will be able to test the correlation between the economic growth and the environmental pollution in China.
IV Methodology方法论
4.1 Data
4.1.1 Variables
The dependent variables in the present study are Particulate Matters (PM), Sulphur Dioxide (SO2) and Nitrogen Dioxide (NO2) in milligram/cu.m. The explanatory variable is per capita income. Moreover, the cubic functional form is adopted in this research which is similar to the study of Grossman and Krueger (1995) and the study of Shafik(1994). The cubic functional form of per capita income allows the presence of U –shaped relationship as well as the second turning point.
4.2.2 Data Set
The three air pollution variables: Particulate Matters (PM), Sulphur Dioxide (SO) and Nitrogen Dioxide (NO) are retrieved from the China Statistics Yearbook from 2006 to 2010. So does the data about the per capita income in the same period. The data include pollution data and income data of 31 provinces and municipalities in China. Thus, all of these data are location-specific.
4.2 Model Specification
The model presented in this section is the simplified model that is used by Torras and Boyce (1998) but the present research does not include the inequality variables in the model at all because of the ambiguity between the income inequality which is measured by the Gini coefficients and the environmental quality. The model is applied to 31 provinces and municipalities. The theoretical foundation of this model has been discussed in the literature review.
This simplified model does not take the effect of trade, technology advancement, the regional difference and so forth into consideration. The model for this research is presented as the following:
POLit = α + β1 *Yit + β2* Yit^ 2+ β3 *Y it^3 +ξit
Where POL refers to the three pollution variables, Y = per capita income, i is province signal (i= 1, 2, 3, 4, 5…N) and β1, β2, and β3 are coefficients.
Thus, the three models can be written as:
PML = α + β1 *Yit + β2* Yit^ 2+ β3 *Y it^3 +ξit (Equation 1)
SO= α + β1 *Yit + β2* Yit^ 2+ β3 *Y it^3 +ξit (Equation 2)
NO= α + β1 *Yit + β2* Yit^ 2+ β3 *Y it^3 +ξit (Equation 3)
All three equations are estimated under ordinary least squares (OLS). The panel data analysis and the fixed model will be utilized in the model in order to control the province specific variables. In addition, the STATA 12 will be used to conduct the data analysis.
V Results结果
5.1 Descriptive Statistics
Table 1 summarizes the descriptive statistics of dependent variables as well as independent variables. The total number of observations is 155. The average value of per capita GDP in China from 2006 to 2010 is 25670.01 Yuan with the range from 5787 Yuan to 76074 Yuan. The mean of the PM is 0.099426, and the mean of SO2 is 0.047324 and the mean of NO2 is 0.041155.
Table 1 Descriptive Statistics
In addition, the data set is panel data. Thus, this research also described the data in regions. The Table 1 b presents the summary of descriptive statistics of variables by province.
Table 1 b Descriptive Statistics of Variables by Province
Moreover, the correlation among variables is presented in Table 2. It can be seen from Table 2 that per capita GDP is positively correlated with the NO2 and PM as well as SO2. The results for quartic per capital GDP and cubic per capita GDP is same to that of per capita GDP. It needs to notice that the correlation does not naturally indicate the association between these variables. The following section will present the results of regression analysis within fixed effect.
Table 2 Correlation Among Variables
5.2 Results of Regression
5.2.1 Dependent variable- PM
Table 3 present the regression results of the Equation 1. The overall model is statistically significant at critical level of 1% but the within R square is 0.1805 which suggests that only 18.5% of the variance among variables can be explained by Model 1. All coefficients of the independent variables are statistically significant at critical level of 1%. Moreover, by interpreting the coefficients, PM is negatively correlated with per capita GDP and the cubic per capita GDP but positively correlated with quadric per capita GDP. However, the coefficients of the cubic per capita GDP and quadric per capita GDP are not statistically significant. Thus, the coefficients of Model 1 can be interpreted as β1<0, β2> 0, β3 = 0 (very close to zero). The relationship between the PM and the per capita GDP could be interpreted as an adverse “U” shape, which support the EKC hypothesis. When the income reaches certain level, the environmental pollution will go up as well. This result may indicate that China now may in the development phase and the deterioration of the environment increase as the income level goes up.
Table 3 Regression Result of Model 1
Figure 1 presents the relationship between per capita income and PM. It is apparent that the curve is “u” shaped. Along with the increase in the economic growth, the emission of PM decreases. Then the emission of PM increases after the turning point. It can be seen from Figure 1 that the turning point is around 20000 Yuan then the PM will go up.
Figure 1 The Fitted- ValueRelationship between Per Capita Income and PM
Table 4 present the regression results of the Equation 2. The overall model is statistically significant at critical level of 1% but the within R square is 0.2106 which suggests that only 21.06 % of the variance among variables can be explained by Model 2. Only the coefficient of the per capita GDP is statistically significant at critical level of 5%. Moreover, SO2 is negatively correlated with per capita GDP but there is no statistically significant relationship between the cubic per capita GDP and SO2 as well as between quadric per capita GDP and SO2. Thus, the coefficients of Model 2 can be interpreted as β1<0. The relationship between the SO 2 and the per capita GDP is a decreasing linear line, and this is different from the EKC hypothesis. This result may also indicate that China now may in the post development phase and the deterioration of the environment decrease as the income level goes up. In addition, the efforts paid by Chinese government may show the effect as well.
Table 4 Regression Result of Model 2
Figure 2 presents the fitted-value relationship between per capita income and SO2. It is apparent that the curve is linear line. Along with the increase in the economic growth, the emission of SO2 decreases at all. It can be seen from Figure 2 that the estimate relationship between per capita GDP is linearly correlated with SO2. In addition, as the economic growth continues, the pollution of SO 2 will constantly decrease over time.
Figure 2 The Fitted- Value Relationship between Per Capita Income and SO2
Table 5 shows the regression results of the Equation 3. The overall model is statistically significant at critical level of 1% but the within R square is 0.077 which suggests that only 7.7% of the variance among variables can be explained by Model 3. Only the coefficient of the quadric per capita GDP is statistically significant at critical level of 5% while the coefficients of per capita GDP and cubic per capital GDP are statistically significant at critical level of 10%. Moreover, NO2 is positively correlated with per capita GDP and the cubic per capita GDP but negatively correlated with quadric per capita GDP. Thus, the coefficients of Model 1 can be interpreted as β1<0. The relationship between the SO 2 and the per capita GDP is a decreasing linear line, and this is different from the EKC hypothesis. This result may also indicate that China now may in the post development phase and the deterioration of the environment decrease as the income level goes up. In addition, the efforts paid by Chinese government may show the effect as well.
Table 5 Regression Result of Model 3
Figure 3 presents the fitted-value relationship between per capita income and NO2. It is apparent that the curve is linear line. Along with the increase in the economic growth, the emission of NO2 increases accordingly. It can be seen from Figure 3 that the estimate relationship between per capita GDP is linearly correlated with NO2. In addition, as the economic growth continues, the pollution of NO2 will constantly increase over time. This may indicates that China is still in the rapid development phase since the emission of NO2 is related to the industrial production.
Figure 3 The Fitted- Value Relationship between Per Capita Income and NO2
VI Conclusion结论
6.1 Conclusion
The main goal of this research paper is to investigate the relationship between the environmental pollution and the economic growth in China. Moreover, this research also tends to examine whether the relationship in China follows the EKC hypothesis. On the basis of EKC hypothesis and the previous literature, there are three pollutants selected in this research as dependent variables to test the relationship between the air pollution and the economic growth in China. Three pollutants are Particulate Matters (PM), Sulphur Dioxide (SO2) and Nitrogen Dioxide (NO2). The economic growth is in terms of per capita GDP and the environmental pollution is presented by the emission of the three pollutants. In addition, this research used panel data analysis to conduct the study and the data is based on the economic and environmental data from 31 provinces and municipalities from 2006 to 2010. More specifically, the fixed effect model is applied to all three estimate equations.
The results in this study were controversial. The relationship between the PM and the per capita GDP could be interpreted as an adverse “U” shape, which support the EKC hypothesis. When the income reaches certain level, the environmental pollution will go up as well. But the estimate relationship between per capita GDP is linearly correlated with NO2. As the economic growth continues, the pollution of NO2 will constantly increase over time. In addition, the relationship between the SO 2 and the per capita GDP is a decreasing linear line, and this is different from the EKC hypothesis. This result may also indicate that China now may in the post development phase and the deterioration of the environment decrease as the income level goes up.
When using the fitted- value estimate, this research finds that the relationship between per capita income and PM is “u” shaped. Along with the increase in the economic growth, the emission of PM decreases. Then the emission of PM increases after the turning point. The turning point is around 20000 Yuan then the PM will go up. On the basis of this research, Chinese government might pay close attention to the emission of NO2 and reduce its effect on the environment of China.
6.2 Limitations
Of course, there are limitations in this research. First of all, the validity and the reliability of the data might be questioned. All of the economic data and environmental data derive from the China Statistical Yearbook. The official data of the China Statistical Yearbook might be biased because of the less transparent in the data system. Secondly, the span of the data is small. With the time increases so as the data, the model will be improved. Thirdly, the model used in this research is a simplified model that did not take the effect of trade, technology advancement, the social factors and so forth into consideration. Thus, the results might be less accurate.
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