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Study on the Relationship of Economic Growth and Atmospheric Environmental Problems Based on EKC Model in Shandong Province XIE Fuju1, 2, ZHANG Hong1, ZHENG Mingxi1 1. University of Jinan, Jinan, P.R.China.250002 2. Shandong University, Jinan, P.R.China 250100 [email protected] Abstract: The environmental Kuznets curve (EKC) hypothesis in Shandong Province was verified using the statistical data of economic growth and environmental pollution indicators. It was found that relation of SO2 , soot emission intensity and economic intensity accorded with the EKC hypothesis, the turning points were at 315.33 Yuan and 94.00 Yuan unit area respectively, and the turning time were in 1996 and 1991-1996 respectively. Further analysis showed that EKC in Shandong province is the results of synergistic action of a variety of favorable factors, such as advantageous policy environment, economic structure optimization, technology progress and reliability of environment protection investment. Keywords: Environmental Kuznets Curve (EKC), Economic growth, Environmental pollution, Shandong Province 1 Introduction The influences of economic growth on environment have been concerned for a long term. Building econometric models to probe the relationship of economic growth and environmental quality indicators and estimate intrinsic law have been being one of the research hotspot at all times. Grossman and Krueger had found that the relation of pollutant concentration (SO2 and soot) and economic growth accorded with converse U curve, when they studied the influences of North American Free Trade Agreement on environment in 1991[1]. And then Theodore further defined Environmental Kuznets Curve (EKC) for the first time in 1993[2]. Subsequently, Grossman studied 12 environment quality indicators which obtained from 66 countries, and found that the relation of the most of the indicators and national income per capita presented converse U curve characteristics. In other words, with the national income per capita increasing, the pollution degree first increased and then decreased [3]. As soon as EKC was advanced, more and more attention was concerned by economists and environmentalists all over the world, and then large numbers of empirical studies were conducted [4-5]. Now, EKC has already been one of the most important methods in econometric research. EKC study started in the beginning of the 21st Century in China. Early studies concentrated in eastern China, where environment pollution problems are more severe than those in other regions due to rapid economy development [6-7]. In the recent years, more and more studies on Midwest region and countrywide scale were executed, and a lot of valuable results were achieved [8-9]. Because of the large area and significant spatial variation in China, the comprehensive indicator system which can reflect environment deterioration and resource consumption had not been formed, and the research results were very different. With the economy developing rapidly, environment is confronted with the large challenge of deterioration in Shandong province. Due to the terrain declining from south to north in Shandong province, Waste-gas emission is difficult to diffuse, especially in winter, which leads to the atmospheric quality deterioration. In order to probe the relation of economic growth and atmospheric pollutant level, two new indices, of which one is pollutant emission intensity, and the other one is economic intensity, were built to verify EKC in Shandong province. 2 Simulation of relation of economy development and atmospheric pollutant level 2.1 Indices Selection and data source 51 In this paper, two types of indices were selected as study aim, of which one type is economic growth index, and the other type is atmospheric pollutant indices. Per capita GDP was often used as the economic growth index in traditional EKC studies, but it can be affected by regional population density. Therefore, per capita GDP usually inflects neither regional economical growth level nor the pressure of economic growth on environment accurately. In order to overcome these deficiencies, economic intensity (unit area GDP) was calculated and taken as economic growth index. Also, SO2 and soot emission intensity (unit area pollutant emission volume) which can reflect atmospheric pollutant level were taken as atmospheric pollutant indices. Data mainly came from “statistical yearbook of Shandong province” from 1981 to 2008. 2.2 Model of relation of economic growth and atmospheric pollutant indices EKC model hypotheses usually have three types, which are quadratic function, cubic function, and logarithmic function [11]. Model hypotheses are as follow: (1) Ei = α + β1Y + β 2Y 2 + ε E i = α + β 1Y + β 2Y 2 + β 3Y 3 + ε (2) (3) ln( Ei ) = α + β1 ln Y + β 2 ln Y + ε In the formula, Ei was pressure of environment, which can be expressed as atmospheric pollutant indicators at t time. In this paper, E1 was expressed as SO2 emission intensity and E2 was expressed as soot emission intensity, which was the dependent variables; Y was economic output at t time. Here, it can be expressed as per capita GDP, which was independent variable in the EKC model; α was characteristic parameter; β1 ,β2 ,β3 were model parameters; ε was random error. Quadratic function, cubic function, and logarithmic function were conducted regression analysis respectively to find out the optimal one. ( ) 2 2.3 Simulated result and analysis 2.3.1 Simulation of relation of SO2 soot emission intensity and economic intensity The regression results showed that logarithmic function was optimal in the three fitted equation (table 1 and figure 1), and then regression equation were obtained (equation 4, 5). It can be concluded that relation of SO2 soot emission intensity and economic intensity accorded with EKC, which meant that with the improvement of economic intensity, pollutant emission first increased, and then decreased. The turning point of SO2 emission intensity regression equation, which was taken from the derivative of regression equation, presented at 315.33 unit area GDP in 1996, while which of soot emission intensity presented at 94.00 unit area GDP in 1991, and continued for 5 years, then decreased in 1996. Thus it can be seen that relation of economy development and atmospheric pollutant level accorded with EKC, and the turning point of pollutant level decreasing in 1996. (4) ln(E1 ) = −0.12 + 0.955lnY − 0.083lnY 2 2 (5) ln( E 2 ) = −0.208 + 0.927 ln Y − 0.102 ln Y 、 、 Table 1 Logarithmic regression results of SO2 and soot emission intensity and economy intensity Environment Regression results Turning point F value R2 indicators α β1 β2 Unit area GDP (Yuan) Year Ln (E1)) 0.750 38.541 -0.120 0.955 -0.083 315.33 1996 Ln (E2) 0.737 20.585 -0.208 0.927 -0.102 94.00 1996 2.3.2 Result analysis The relation of economy development and atmospheric pollutant level accorded with EKC, and the turning point of pollutant level decreasing appeared in 1996, which can be explained as follows: First, economic structure optimization and technology improvement were the main reasons. Figure 2 showed that there were two different stages of relation of secondary industry percentage and atmospheric pollutant level in Shandong province. The one stage was from 1990 to 1996, during which with increasing of percentage of the secondary industry, pollutant emission intensity had showed upward 52 trend volatility. The other one was after 1996, during which pollutant emission intensity had decreased rapidly with increasing of percentage of the secondary industry. This can be explained that the pollutant emission intensity in the secondary industry was higher than that in the primary industry at the primary stage of industrialization. With the industrialization deepening, technology improving, industrial structure optimization, especially cleaner production technology being used broadly, pollutant emission intensity decreased dramatically. 3 3 3 2 2 ● — Observed ; 2008 2005 2002 1999 1996 1993 1990 1981 2008 2005 2002 1999 1996 1993 1990 0 1987 0 1984 1 1981 1 1987 1 1984 ln E1 ln(E2) )2 (21 — Regress Curve Figure 1 Logarithmic regression results of pollutant emission intensity and economic intensity Secondly, the environment protection mechanics was established, and a series of environment protection policies were published, which can be profitable for atmospheric quality improvement. These policies involved that total control target had been considered to national economic and social development annual plan for the first time, and environment protection work had been brought into the evaluation system of government and leaders, and so on. Through these policies and measures, decision-makers had improved their environment protection consciousness, and environment protection works had been reinforced. In the meantime, investment of environment protection has increased with years. The increasing extent attained to 35% from 1996-2005, which was far higher than that of GDP in the same term. The investment of environment protection had already occupied proportion from 5% of GDP in 1996 to 35% in 2005 [10]. Since “the Eleventh Five-Year (2001-2005) Plan for National Economic and Social Development” was executed, 3.6 hundred billions had been invested to build the ecological province. Main investment projections included sewage treatment plants building in cities, pollution controlling of 1000 heavy polluting enterprises, desulphurization facilities equipping for sixty percent of all the electric power plant in Shandong province. Based on these powerful policies and a large number of investments, atmospheric environment quality had already improved a lot from 1996. Thirdly, according to some research, foreign directly investment (FDI) can play an important role in the relation of economics growth and environment pollutant level [11]. Environment pollutant level first had decreased through importing productions in polluting industries in some nations (usually developed nations), which led to EKC relation of economics growth and environment pollutant level by transfer overseas of their own environment pressures. But status in other nations, where they had to accept the polluting industries (often developing nations), were quite another thing, and typical EKC characteristics can not showed for quite long time. In other converse views, international trade can make “green technology” spread and improve environment quality level in more and more nations. Shandong province locates in the forefront of the eastern coastal areas to attract foreign investment in China. So the influences of FDI especial FDI structure on environment can not be ignored. FDI in Shandong province has increased since reform and opening policies were executed. FDI structure has improved a lot during “the tenth Five-Year (1996-2000) Plan for National Economic and Social 53 、 10 01 97 05 20 20 19 SO2 emission intensity 93 0 Percentage of secondary industry % 20 81 05 01 20 97 20 93 19 89 19 19 19 19 85 0 30 19 10 40 89 20 81 SO2 emission intensity 30 ) ( 50 19 40 60 19 10 8 6 4 2 0 50 ( 85 60 70 9 8 7 6 5 4 3 2 1 0 19 16 t/km 2 ( 1412 )10 soot emission intensity 70 t/km 2 ) 18 percentage of secondary industry % Development”, of which the FDI percentage of three industries were 3.2% 84.7% and 12.1% respectively. Manufacturing had become the important industry of FDI. The agriculture and services industry percentage of FDI, such as manufacture of primary products, communication equipment, and computer and other electronic equipment, textile and garment, and so on, were higher than that of other industries. Thus it can be seen, atmospheric pollutant emission intensity had decreased, with the transferring of FDI from traditional heavy-polluting industries to products manufacture and high-tech industries. The development model, which keeps to FDI inflow, then technology overflow, industrial structure improvement at last, can be expected in Shandong province. Soot emission intensity Percentage of secondary industry Figure 1 Change of pollution emission density and the parentage of the secondary industry 3 Conclusions and prospects (1) The logarithmic regression results showed that relation of SO2 and soot emission intensity and economic intensity accorded with EKC in Shandong Province, and the turning point present at 315.33 Yuan and 94.00 Yuan respectively in 1996. (2) The EKC of economic growth and atmospheric environment quality was the results of synergistic action of a variety of favorable factors, such as advantageous policy environment, economic structure optimization, technology progress and reliability of environment investment. (3) Studies on economic intensity and pollutant emission intensity used to verify EKC, has not still been found in literatures. So the research results lack of comparability, and wait for further validation in regions, where natural, social and economical conditions are different. : Acknowledgments This paper is supported by Social Science Planning Projection of Shandong Province (No. 08JDC053) and Soft Science Projection of Shandong Province (No. 2009RKA089). References [1]. Grossman G M and Krueger A B. Environmental impacts of a North American Free Trade Agreement [A]. National Bureau of Economic Research Working Paper 3914, NBER[C], Cambridge MA, 1991 [2]. Theodore Panayotou. Empirical tests and policy analysis of environmental degradation at different stages of economic development, ILO [M]. Geneva: Technology and Employment Programme, 54 ) ( 1993 [3]. Grossman G M and Krueger A B. Economic growth and environment [J]. The Quarterly Journal of Economic,1995,110(2):353 377 [4]. Cole M A, Rayner A J, and Bates J M. The Environmental Kuznets Curve: an Empirical Analysis. Environment and Development Economics,1997,2:401 416 [5]. Markus P. Technical Progress, Structural Change, and the Environmental Kuznets Curve. Ecolog ical Economics,2002,42:381 389 [6]. Li Rie, Zhang Haiiun. An Empirical Analysis on the Regional Discrepancy and Tendency of EKC in China (1981-2004). Journal of Xi′an Jiaotong University ( Social Sciences),2008,28(4):35 44(in Chinese) [7]. Huang Yaolin, Nong Yanyan and Wu Yuming. Environmental Kuznets Curve Test in China: Positive Analysis Based on Panel Data from 1997 to 2006. Sichuan Environment,2009,28(5):107 115(in Chinese) [8]. Ning Jiangbing, Zhang Chuan and Su Shijun, etc. Case Study of Water Environmental Kuznets Curve in Chengdu City. Environmental Protection Science,2009,35(5):29 32(in Chinese) [9]. Shao Ningping, Liu Xiaopeng and Qu Xiaoyi. Characteristics of Kuznets Cueve of Three Wastes Discharge in Ningxia. Resources and Industries,2009,11(1):105 111(in Chinese) [10]. Li Hongli, Wang Yan and Ge Hu. Test and Analysis of the Environmental Kuznets Curve in Shandong Province. Research of Environmental Sciences,2008,21(4):210 214(in Chinese) [11]. Hu Dan, Xu Kaipeng, Yang Jianxin, etc. Economic development and environmental quality: progress on the Environmental Kuznets Curve. Acta Ecologica Sinica,2004,24(6):1259 1266(in Chinese) ~ ~ ~ ~ ~ ~ 55 ~ ~ ~