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The Effect of Environmental Regulation of ASEAN on China’s Export Trade Shanshan WU State Grid Energy Research Institute [email protected] Abstract- Based on China-ASEAN panel data in the period of 1990-2007, this paper uses the gravity models to analyze the effect of the environmental regulation of ASEAN on China’s export trade. In the paper, we are creatively using energy consumption per capita and carbon dioxide emissions per capita as two proxies to measure the stringency of environmental regulation, which reflects economic characteristics of developing countries. According to the theory of supply and demand, we propose export scale and export structure as two factors which can affect the effect of environmental regulation of trade, after analyzing how the foreign environmental regulation affects China’s export. Finally, we testify “the export scale effect of environmental regulation” and “the export structure effect of environmental regulation” by using the empirical results and listed data. That is: 1. China’s export is less sensitive to environmental regulation of ASEAN member countries when the scale of export is relatively small; 2. China’s export is more sensitive to the environmental regulation of ASEAN member countries when “dirty product” covers a greater proportion. Keywords- Trade; Environmental Regulation; China-ASEAN; Panel Data; Gravity Models Introduction

I.

INTRODUCTION

Chinese government has a friendly cooperation with surrounding countries, especially since its opening to the world. It has made many connections among the Association of Southeast Asian Nations (ASEAN) in political, economic, cultural and other areas. When China established the dialogue partnership with ASEAN in 1991, their relationship has come to a new page. The leaders of both sides had announced the object of establishing the free-trade area in China-ASEAN Summit (“10+1”) on November 2001. In accordance with the ‘ASEAN - China Framework Agreement on Comprehensive Economic Cooperation’ time frame on January 1st, 2010, the ASEAN-China Free Trade Area (ACFTA) was established, which comprises China, Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand and Vietnam. It is the world’s third-largest free trade zone, the most populous free trade area, but also the largest free trade zone among developing countries. The establishment of ACFTA marked an important milestone in the development of ASEAN-China relations. Its start-up not only enlarged market size, but also enhanced trade between China and ASEAN. Besides, it helped to eliminate trade barriers and enhanced economic efficiency in the region. ACFTA will play an active role in promoting world trade and economic recovery. As export trade growing rapidly, China faced a growing number of technical and green barriers of trade. Especially in recent years, many developing countries implemented a more stringent environmental regulation and constraint, which restricted the development of China’s export trade to a certain extent1. For this reason, it’s very important to investigate the relationship between the environmental regulation and trade of developing countries. We choose to use the case of ChinaASEAN to research for two reasons: (1) due to various reasons and constraints, there are little studies on developing countries in the area of environmental regulation and trade. It has a certain theoretical significance for attempting to discuss the export trade effect of environmental regulation by using the case of China and ASEAN, which are the largest developing economies in the world. (2) The trade policies of ASEAN, including the environmental regulation, have a negligible impact on China’s export because the seven in ten ASEAN are bordering with China which is known as “geographical advantage”. In other words, investigating the ASEAN environmental regulation effect on China’s export trade has a real and far-researching significance. II.

LITERATURE REVIEW

[1]

Seitz proposed the importance of environmental regulation research firstly. He aroused the concern of environmental policy, though he was just introduced the environmental regulation into his paper which was the beginning of the academic discussion on the environmental regulation. Magat [2] used the environmental regulation as the argument to investigate its effect on other variables. The research of the environmental regulation effect on the trade should be traced back to the late 1980s. With increasing global trade and pollution, governments and environmental organizations had focused on rules which could restrain international trade to prospect environment. Therefore, the studies on the effect of environmental regulation on the international trade had become more and more.

1

See “Report on China Export Trade Barriers Monitoring and Analysis, 2007~2011”, Editor: Yaxing Wang. China Economic Publishing House.

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As a policy, environmental regulation affects the trade by influencing trade flows, which means imports and exports2. There were many scholars working on it. Jug and Mirza [3] found the environmental regulation would restrain the trade by using gravity models, and this effect could be greater when he took account of the heterogeneity of product and the case of endogenous and exogenous. Mojtahed [4] analyzed the case of trade between American and OECD countries by using the method of panel data with gravity models. Qi, Zheng and Zhao [5] used the co-integration and Error Correction Model (ECM) to test the relationship between environmental regulation and trade pattern. He suggested that environmental regulation had a positive impact on the share of clean products in exports in short time, and in long time there were the same effect on the share of clean products in exports but had a reverse impact on the share of imports, which means the environmental regulation was one of the factors of comparative advantage. Cole, Elliott and Okubo [6] made an empirical analysis by using the net export trade data of Japan to the world, to the non-OECD countries and to China, respectively. He figured out that both industry regulation and environmental regulation were the significant determinant of net trade, and the later one would be more prominent in the case of developing countries. Domestic studies mainly focused on the effect of Chinese environmental regulation on its own trade flows. Liu [7] measured the export cost effect and export innovation effect of domestic environmental regulation by using co-integration method. Wang & Liu [8] made further investigations on two effects mentioned above and suggested the former one was negative and the other positive. Most of these researches above mainly focused on how the domestic environmental regulation affect the trade in which the environmental regulation was treated as a new kind of factor endowment. But the studies on effect of the foreign environmental regulation to the domestic export trade were seldom, and most of them were limited to the case of developed countries. This paper tried to give a full analysis about the effect of environmental regulation in ASEAN on the Chinese export. III. DEFINITION OF KEY VARIABLE AND BASIS OF MEASUREMENT A critical variable in this paper is environmental regulation which has been broadly delimited in the past two decades. Considering its policy characteristics, the measurement of environmental regulation could vary by different counties, even the different times for the same country. Thus, it’s particularly necessary to re-define the environmental regulation and clarify the basis of its quantitative method. A.

Definition of Environmental Regulation

The conception of environmental regulation has been delimited and investigated from many different views by many Chinese scholars, such as Cheng [9], Chen [10], Zang [11] and so on. Based on the descriptions of U.S. Environmental Protection Agency (EPA), the European Environment Agency (EEA), the World Trade Organization (WTO) and many other researchers, this paper defines environmental regulation as follows: due to the negative externalities (i.e. the difference between social and corporate welfare functions), the environmental regulation is a series of rules and regulations issued by government and relative apartment which could control and manage the economic behaviour of enterprises, including kinds of laws, standards, management mechanism, and various forms of international environmental protection conventions, to make sure the environment and social sustainable development while keeping economic growth. There are many researches on the classification of the environmental regulation. Based on the reports of Economic Cooperation and Development (OECD) and the World Band, they generally divided the environmental regulation into three types as the Command and Control (CAC), Market-based Incentives (MBI) and Information-based Voluntary Approaches (or called Open Sourcing the Regulation). Certainly, there were various versions; we are not willing to explain them in detail. This article only deals with two types of environmental regulation, the CAC and MBI, due to our purpose is to figure out the environmental regulation’s impact on the trade. B. The Basis of Measurement and the Quantitative Methods Generally speaking, there are two major basic methods to measure the environmental regulation: qualitative and quantitative. 

The qualitative study about the measurement of environmental regulation is as follows:

Testing the sign of residuals in the HOV models which is not included the environmental regulation to make sure the level of stringency [12]. Using the qualitative variable as the measurement of environmental regulation to denote the level of stringency. Walter and Ugelow [13] use 1~7 to represent the lowest to highest level. Dasgupta et al. [14] developed comparative indices of environmental 2

Hai Et al. suggested that the basic characteristics of various trade policies and other policies which can affect trade is intervening the free trade, which can be trade-restrained or trade-encouraged, and import-influential or export-influential. See “International Trade”，Editor: Wen Hai, P. lindter、Wang, Shanghai People’s publishing House, 2003.

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policy and performance for 31 countries using a quantified analysis of reports prepared for the United Nations Conference on Environment and Development. Van Beers & Van den Bergh [15] also used the weighted method by introducing the inputoriented regulation (mainly caused by pollution abatement costs) and the output-oriented regulation (mainly caused by polluted product taxes). 

The quantitative study about the measurement of environmental regulation is as follows:

The Environmental Sustainability Index 3 (ESI) developed by CIESIN provides the official data of Environmental governmence and Participation in international cooperative efforts. Many researches were working on them [16, 17]. The limitation of this method is that data are not continuous (only the year of 2001, 2004 and 2005), and was only updated to 2005, which means this method would be lack of time effect. Most of the researchers in this area used the share of abatement costs in total production costs to be the measurement of environmental regulation [3, 18, 19, 20, 21, 22, 23]. But considering the differences of production structures and technology level among countries, the abatement costs would lose lots of important information about environmental regulation. Others would employ those indirect variables as the proxies of environmental regulation. They found that there must be some relationship between the economic development degree and the environmental regulation level, that is, more developed countries will have more stringent environmental regulation. Accordingly, they can use the income per capita to be the proxy variable of environmental regulation when the samples have a disparity in their economic development [14, 24, 25]. Costantini and Crespi [26] suggested the carbon dioxide emissions per capita could also be a proxy variable. There are some problems with getting available data of ASEAN since they are developing countries. Based on the availability of data and their characteristic economic structure, this paper will use two variables, the carbon dioxide emissions per capita and the energy consumption per capita, to measure the environmental regulation. The energy consumption per capita could tell the real demand of one country, and the carbon dioxide emissions per capita could reveal the real level of pollution emission. For the same country, when the energy consumption is large but the pollution emission is relatively small, we can say that they have very strong capacity of dealing with the pollutions, which means the environmental regulation is more stringent in this country, and vice versa. IV. THE MODEL AND METHODOLOGY A. The Model The Gravity Model has been widely used and recognized in the recent decades by trade investigation. Tinbergen proposed this model firstly by giving the basic form which was adapted to trade between two countries:

Fij  G

[27]

M i M j Dij

(1)

With:

Fij = the trade flows from country i to county j . M i and M j = the size of two countries, usually depend on Gross Domestic Product (GDP) or population of each countries.

Dij = the distance between this two countries (usually by measuring the capital distance). G = constant value. After the extension by many scholars, the gravity models have a relatively fixed form in various areas. In this research, we take the form proposed by Van Beers and Van den Bergh [15] and make little change to meet our research purpose. The loglinear version of the extended model is:

3

Data source: Centre for International Earth Science Information Network (CIESIN).

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LnExporti ,t   i ,t  1LnGDP _ chnt   2 LnGDPR _ chnt   3LnEnergy _ chnt   4 LnCO2 _ chnt  5i LnGDPi ,t   6i LnGDPRi ,t   7i LnEnergyi ,t  8i LnCO2 i ,t  9i LnEnergyi ,t 1  10i LnCO2 i ,t 1   11iLndisi ,t   12iLnareai ,t   13ilandi ,t  ui ,t

(2)

With:

Ln = logarithmic form;

Exporti ,t = the export value from China to country i at time t . GDP _ chnt , GDPR _ chnt = the GDP and GDP per capita of China at time t , respectively. Energy _ chnt = the energy consumption per capita of China at time t . CO2 _ chnt = the carbon dioxide emissions per capita of China at time t . GDPi ,t , GDPRi ,t =the GDP and GDP per capita of country i at time. Energy i ,t , Energy i ,t 1 = the energy consumption per capita of country i at time t , t - 1, respectively.

CO2 i ,t , CO2 i ,t 1 = the carbon dioxide emissions per capita of country i at time t , t - 1, respectively.

disi ,t , areai ,t = the distance between China and country i , and the area of country i , respectively. landi ,t = dummy variable, represents if country i is an adjacent country of China. ui ,t = the white noise disturbance term.

i  1,2,...,10 = the ASEAN member countries, including Brunei Darussalam, Cambodia, Indonesia, Lao People’s Dem. Rep., Malaysia, Myanmar, Philippines, Singapore, Thailand, Viet Nam, respectively.

t  1991,1992,...,2007 = the year. B. Data Source The data used in this study are comprised of annual measures for 17 years (after adjustments), 1991–2007, on 11 countries (Brunei Darussalam, Cambodia, Indonesia, Lao People’s Dem. Rep., Malaysia, Myanmar, Philippines, Singapore, Thailand, Viet Nam and China). The detailed data source is as follows. The China-ASEAN trade values of each year are provided by China Economic Net4, the unit is U.S. dollar. The GDP and GDP per capita of China and ASEAN come from the United Nations Statistics Division 5 (UNSD), the unit is U.S. dollar. The energy consumption per capita and the carbon dioxide emissions per capita of China and ASEAN are provided by the World Development Index6 (WDI) from World Bank, the unit is kg of oil equivalent per capita and thousand metric tons per capita, respectively. C. The Methodology After processing the raw data mentioned above, we decided to use the fix-effect unrestricted model to estimate the system due to the differences among the economic structures and the social background of ASEAN. Firstly, we do the unit root test, and the results suggest every series don’t exit the unit root, which means all the series are stationary (due to the space reasons, the results will not be listed). Secondly, we do the redundant fixed effects tests to know if the cross-section fixed effect is redundant. Table 1 reveals the null hypothesis is objected with the significance at the 1% level, which ensures we can use the fixed effects model. Since heteroscedasticity is very likely, the Cross-section Weights (GLS) will be used. Table 2 gives the estimated results after deleting the non-significant variables. Again, we only listed the results of key variables, including the 4

See http://db.cei.gov.cn/. See http://unstats.un.org/unsd/default.htm. 6 See http://data.worldbank.org/data-catalog/world-development-indicators. 5

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coefficient of energy consumption per capita, the carbon dioxide emissions per capita, and their lagged one period variable, and so on. TABLE I THE REDUNDANT FIXED EFFECTS TESTS

Redundant fixed effects tests

Statistic Values

Probability

Cross-section F

7.976691

0.0000

Cross-section Chi-square

72.020708

0.0000

TABLE II GLS ESTIMATION RESULTS (PARTIAL)

ASEAN Coefficients

7

BRN -0.38 *** 1.16 *** -2.57 *** 0.72 ***

8 9 10

KHM

IDN

-0.18

0.25

0.39 *** 4.70 *** -0.28 ***

1.00 *** 0.75 -1.34 ***

LAO

MYS

MMR

PHL

SGP

THA

VNM

4.38 *** -1.76 *** -4.49 *** 2.99 ***

1.25 *** -0.96 *** 1.06 *** -1.43 ***

-1.36 *** -0.17 * 0.93 *** -0.91 ***

3.37 *** -0.46 ***

-0.42 ***

6.67 *** -3.86 *** -1.32 ***

1.89 *** -1.27 *** -7.60 *** 0.47 ***

R2 Adjusted

F

0.34 -0.06

0.05 -0.68 *** 0.71 ***

-0.21

0.995788

R2

0.992586 310.9356

Value

D.W . Value

2.198591

Note: a.

***, ** and * indicate significance at the 1 per cent, 5 per cent or 10 per cent level, respectively.

b. The name of ASEAN member countries are simplified writing in the first line according to UN rules. (BRN, KHM, IDN, LAO, MYS, MMR, PHL, SGP, THA, VNM represent Brunei Darussalam, Cambodia, Indonesia, Lao People’s Dem. Rep., Malaysia, Myanmar, Philippines, Singapore, Thailand and Viet Nam, respectively.) V.

THE RESULTS

As the model uses the double logarithmic form, coefficient of the explanatory variables, i , is the partial elasticity which measure the elasticity effect of explanatory variables on dependent variable when other variables are constraint [28]. Thus, the coefficient, 7 and 8 , is the energy consumption per capita elasticity of exports (“energy consumption elasticity” in short) and the carbon dioxide emissions per capita elasticity of exports (“carbon emission elasticity” in short). And the coefficient, 9 and 10 , is the lagged energy consumption and the carbon emission elasticity of exports, respectively. The results indicate the coefficients of elasticity are very significant for all ten ASEAN member countries. Among the ten member countries of ASEAN, eight of them (Cambodia, Indonesia, Lao People’s Dem. Rep., Malaysia, Myanmar, Philippines, Thailand, Viet Nam) have the positive energy consumption elasticity and negative carbon emission elasticity (or their lagged elasticity, respectively) at the same time, which means China will export more to the ASEAN member country who implement the more stringent environmental regulation. From Table 2 we can see the most values of

7

(or

9

) are larger than the values of

8

(or

10

) which means the

effect of increasing energy consumption is much bigger than the effect of decreasing of carbon emission to the China’s export. These results reflect the ASEAN member countries have the characteristic of developing countries that promote the economic development by consuming more and more energy. Furthermore, the gap of elasticity coefficient among these eight countries is large in certain extent, possibly related to the China’s export scale and export structure. According to the theory of supply and demand, when some of ASEAN member countries implement more stringent environmental regulation, the yield of pollution products will be decreased. Because short-term demand remained, the pollution product market will turn to the situation of supply falls short of demand. Then this country will import more pollution product to meet their demand. The more demands, the more they will import. Based on the above analysis, we suggest that there must be two kinds of effects affecting

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the impacts of ASEAN member countries’ environmental regulation to China’s export, namely “export scale effect” and “export structure effect”. This paper will use the HS classified export data of China-ASEAN in confirmation of existing of these two effects discussed above. According to the definition of “Pollution-Intensive Industries” proposed by Mani and Wheeler [29], we can tell that the steel, iron, steel products, non-steel metal products, non-metallic mineral products, petroleum and coal products, pulp and paper products, oil refining industrial products, electronic products, industrial products and chemical products are the “pollution product”. We just list the annul export values (the proxy of export scale) from China to each of those six ASEAN member countries (Indonesia, Malaysia, Myanmar, Philippines, Thailand and Viet Nam) in Figure 1, the share of pollution product in the export values (the proxy of export structure) in Figure 2, and the annual average values of export scale and the export structure of each country after packing up the raw data in Figure 3.

Figure 1 The China’s export values (the export scale) to each country (1995~2010)

Figure 2 The proportion of pollution product (export structure) in China’s export to each country (1995~2010)

Figure 3 The annual average values of China’s export scale and export structure7

According to Figure 1 and Figure 3, China’s export scale to five of them (Indonesia, Malaysia, Philippines, Thailand and Viet Nam) are similar except for Myanmar, which is only 110 billion dollars, about five times smaller than others 8 .

7 8

Data source of Figures 1~3 ：China Economic Net, see http://db.cei.gov.cn/. The export values are the proxies of export scale for each ASEAN country. In Figure 3, the histograms denote the annual average export scale of each country; the values are showed in the histograms.

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Accordingly, the empirical results showed in Table 2 indicate the China’s export to Myanmar is inelastic with

10 =-0.91.

9 =0.93，

The listed data in Figure 1 and Figure 3 and the empirical results both indicate that the export scale is a

very important factor which can be influential to the effect of foreign environmental regulation on China’s export. Therefore, we have testified the existing of “the export scale effect of environmental regulation”. We can see the proportion of pollution product in China’s export to each ASEAN country and its annual average value in Figure 2 and Figure 39. Indonesia, Malaysia, Myanmar and Vietnam are in the same level, between 70% and 73.5%, only Thailand and Philippines are not in line. Thailand has the highest proportion with 79.35%, and the share of Philippines is lowest with 68.24%. Correspondingly, the results in Table 2 show that the largest and the smallest carbon emission elasticity of China’s export (absolute value) are Thailand and Philippines, with -3.86 and -0.46 respectively. According to the above analysis, we can say that there is a relationship between carbon emission elasticity and China’s export structure, that is the larger proportion of pollution product, the larger carbon emission elasticity of China’s export, which means that the export of China is more sensitive to the environmental regulation in that country. Therefore, we have testified the existing of “the export structure effect of environmental regulation”. We will elaborate this view in the case of Thailand. Table 3 shows the details of the Chinese product exported to Thailand. For a long time, China mainly exports pollution products to Thailand, including the electronic products, machinery, steel and steel products and chemical products. The average export scale from China to Thailand is 641 billion dollars with an annual average increasing rate at 26% in past decade, and the proportion of pollution product is relatively large, which we can tell in Table 4. These are consistent with the results in Table 2. TABLE III THE STRUCTURE OF EXPORT TRADE FROM CHINA TO THAILAND (2004-2010)

Unit: 10,000 dollars Year Products

2004

2005

Year Products

2006

Motors, Motors, Electrical Electrical Appliances, AudioAppliances, 2,344.70 3,423.70 4,288.60 visual Equipment Audio-visual and Spare parts Equipment and Spare parts Nuclear Reactors, Boilers, Machinery Appliances and Parts

2008

Year Products

5,469

Motors, Electrical Appliances, Audio-visual Equipment and Spare parts

Motors, Electrical Appliances, 5,386 Audio-visual Equipment and Spare parts

7,311

4,010

4,361

Nuclear Reactors, Boilers, Machinery Appliances and Parts

Nuclear Reactors, Boilers, 4,075 Machinery Appliances and Parts

5,507

2007

Nuclear Reactors, Boilers, 1,811.50 2,519.60 3,170.60 Machinery Appliances and Parts

4,978

2009

Year Products

2010

Steel

658.6

1,148.90

Steel

1,056.20

1,259

1,515

Iron and Steel Products

714

Steel

1,014

Iron and Steel Products

193.5

289.2

Iron and Steel Products

390

582

877

Plastic and Plastic Products

532

Iron and Steel Products

915

Organic Chemical, Precious Metals and other Compounds

219

260.4

Plastic and Plastic Products

331.9

468

596

Steel

427

Plastic and Plastic Products

844

Since Brunei and Singapore have the characteristics of developed economic [30], the situations about these two countries are not analysis. VI. CONCLUSIONS This paper investigates the effect of environmental regulation of ASEAN member countries on China’s export trade by using fixed-effect panel data model. Taking full account of the feasibility, reliability and validity of the data, we utilize the energy consumption per capita and the carbon dioxide emission per capita as the measurement of environmental regulation for ASEAN countries, which could overcome the barriers of data missing. Based on this measurement, we analyze the impact of ASEAN member countries’ environmental regulation on the China’s export by using gravity model. The empirical results show the energy consumption elasticity is positive and the carbon emission elasticity is negative at the same time for eight countries (Cambodia, Indonesia, Lao People’s Dem. Rep., Malaysia, Myanmar, Philippines, Thailand,Vietnam) which could reflect the economic characteristics of developing countries. 9

The line chart represents the proportion of pollution product of export to each ASEAN country in Figure3; the value showed on the top of each country.

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Then we analyze the possible impacts of Chinese export scale and export structure on the results from the view of supplydemand theory and propose “the export scale effect of environmental regulation” and “the export structure effect of environmental regulation”. Then we combine the listed data and empirical results to testify these two effects. Then we draw the conclusion that (1) the smaller export scale to certain ASEAN country, the China’s export is less sensitive to the environmental regulation implemented by that country. (2) The larger proportion of pollution product in export to certain ASEAN country is, the more sensitive China’s export to the environmental regulation implemented by that country is. Finally, we illustrate the two effect mentioned above using the case of Thailand. ACKNOWLEDGMENTS

We gratefully acknowledge the support of National public projects: the Analysis and Countermeasures on Consumer Product Safety Detection, with No. 200910088. We also thank Professor Yaxing Wang, who is the director of project. REFERENCES

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