University of Groningen Master Thesis
Does international trade moderate the relation between Environmental Regulation and Economic Growth in developing economies? Evidence from
China (2007 - 2012)
SUPERVISOR: Dr. Sathyajit Gubbi
CO-ASSESSOR: Dr. Mariko Jasmin Klasing
STUDENT NAME: Tsung En Tseng
STUDENT NUMBER: s3441245
SUBMISSION DATE: June, 2018
MAJOR: MSc International Business and Management
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ABSTRACT
Recent debates between the Porter hypothesis and Pollution Haven hypothesis have been focused on the context of developed economies. While the developing economies nowadays are increasingly concerned about environmental issues, an understanding of how environmental regulation and economic growth, as well as how the context of foreign trade affect this relationship is needed. This paper provides research on the moderating effect of the proportion of trade with strict environmental-regulated countries on the relationship between environmental regulation and economic growth of China. A total of 12 provinces are studied by means of a two-period panel regression analysis. A negative but insignificant relationship between environmental regulation and economic growth in China can be found, however there is a positive and significant moderating effect from the extent of trade with strict environmental-regulated countries. Keywords: Environmental Regulation, Economic Growth, Trade, China
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TABLES OF CONTENTS
INTRODUCTION ... 5
LITERATURE REVIEW... 10
ENVIRONMENTAL REGULATION AND ECONOMIC GROWTH ... 10
THE EFFECT OF TRADE ON ENVIRONMENTAL REGULATION AND ECONOMIC GROWTH ... 16
METHODOLOGY... 21 RESEARCH MODEL ... 21 DATA SAMPLE ... 22 INDEPENDENT VARIABLE ... 23 DEPENDENT VARIABLE ... 23 MODERATOR ... 24 CONTROL VARIABLE ... 25
VARIABLES DESCRIPTION AND DATA ACCESS ... 27
ANALYSIS APPROACH ... 28
STATISTIC MODEL ... 28
HETEROSKEDASTICITY AND COLLINEARITY TEST ... 29
RANDOM OR FIXED EFFECT ANALYSIS ... 29
EMPIRICAL RESULTS ... 30
DESCRIPTIVE STATISTICS ... 30
REGRESSION RESULTS ... 30
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DISCUSSION AND CONCLUSION ... 35
CONTRIBUTION ... 38
LIMITATION AND FUTURE RESEARCH ... 39
REFERENCE ... 41
APPENDICES ... 53
APPENDIX A-SELECTION OF SAMPLE PROVINCES ... 53
APPENDIX B-CODING FOR COASTAL PROXIMITY CONTROL VARIABLE ... 54
APPENDIX C.1-2007ENVIRONMENTAL REGULATION STRINGENCY (RELAXATION) ... 55
APPENDIX C.2-2012ENVIRONMENTAL REGULATION STRINGENCY (RELAXATION) ... 56
APPENDIX D–HAUSMAN TEST ... 57
APPENDIX E- SCATTERPLOT ... 57
APPENDIX F–STRINGENCY OF ENVIRONMENTAL REGULATION (WORLD) ... 58
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Introduction
Environmental regulations are needed to resolve negative externalities drawn by economic activities since these externalities cannot be settled merely by market mechanisms (Stavropoulos, Wall, & Xu, 2017). The concerns that environmental degradation may become a brake on economic growth have brought policy makers, specifically those of developing economies, into a dilemma of balancing between economic development and environmental preservation (Wang, 2010). However, despite increasing amounts of research studying the effect of environmental regulation and its influence on economic growth, the actual effects are inconclusive.
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(Démurger, 2001). Consequently, it is important to study whether environmental regulations influence economic growth in the context of developing economies.
Developing economies, in general, have a strong emphasis on foreign trade and investments to supplement market failure (Coase, 1960). Understanding that trade increases economic growth by facilitating the diffusion of knowledge and technology (Baldwin, Braconier, & Forslid, 2005) and allowing them to create comparative advantages by leveraging labors and natural resources (Stern, Common, & Barbier, 1996), it is particularly important for developing economies to utilize trade to compete with economically advanced countries.
Trade also stimulates the spillover of environmental regulation (Vogel, 1997). Critics argue that international trade spurs a “race-to-the-bottom” on environmental regulation, due to the increasing global flow of goods and services (Dong, Gong, & Zhao, 2012), and to gain comparative advantages (Copeland & Taylor, 2004). Others believe that trade facilitates a “race-to-the-top.” Regulation spillover from strict environmental-regulated countries to less regulated ones could create ecological and economic incentive for governments to strengthen their environmental regulations (Vogel, 1997).
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hypothesis however argues that stricter environmental regulation could stimulate economic growth by generating innovation offsets and creating early mover advantages (Ambec et al., 2013; Porter & Linde, 1995; Stavropoulos et al., 2017). The roles of trade in both theories are firmly rooted in the context of environmental regulation. In both theories, the premise is that there are regulatory differences between countries, and this difference will affect their interaction and performances. As Perkins and Neumayer (2009) stated, what really matters is with whom to trade. The environmental regulation of the trade countries is critical to testify to the theories.
Given the importance of international trade to the development of developing economies. This thesis proposed the following research question:
“Does trade countries’ environmental regulation contexts moderate the influence of environmental regulation on economic growth?”
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Recent statistics (see Table 1 on page 22) have shown that the overall environmental regulation stringency of China has gradually increased (OECD, 2018). This shows that the Chinese government has actively improved their environmental regulations. However, due to the geographic disparities and unequal development between provinces, the enforcement of environmental regulation differs significantly between provinces even though they are following uniform environmental standards (Jin, Andersson, & Zhang, 2016; Lian, Ma, Cao, & Wu, 2016; Liu et al., 2017; Wang & Wheeler, 2005). This “implementation gap” provides an opportunity to measure the relationship between environmental regulations and economic growth in developing economies.
To simplify the observation, this thesis only considers a one-way connection from environmental regulation to economic growth instead of the interaction in between. Furthermore, understanding that both Porter hypothesis and the pollution haven hypothesis emphasize how strict environmentally regulated countries affect those with lax regulation, I will be using the proportion of trade from strict environmental regulation countries to test the moderating effect.
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Literature Review
Environmental Regulation and Economic Growth
The relationship between environmental regulation and economic growth has aroused great academic interest. Scholars holding the traditional view have argued that strengthening the environmental regulations will increase production cost (Shadbegian & Gray, 1994), limit productivity, and restrain innovation (Stavropoulos et al., 2017). While innovation is believed to be the key to environmental conservation, this implies that an increase in environmental regulation stringency does not only hamper economic growth but will also do no good to the environment. However, Porter (1991) challenged that traditional scholars often hold a static view on environmental regulation. He argued that traditional scholars have assumed all firms made choices with intend of minimized cost and that all technology and process are fixed. Environmental regulation will raise additional costs and has a further impact on economic growth under these assumptions. Porter and Linde (1995) further argued that in the real world, decisions were made based on how firms interpret their current status and their institutional context, technology and processes are unfixed and companies struggle to find out the best way of structuring their business. Environmental regulations could then serve as an important route sign for the direction of innovation.
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create a safer production process, and it is also believed to bring higher process yield and lower leading time due to close monitoring and maintenance (Porter & Linde, 1995). Given the vast potential of developing economies, great attention has turned to the bottom-of-pyramid (Prahalad, 2006). The emphasis of maximizing functionality and minimizing price (Govindarajan & Ramamurti, 2011) have leveled the effect of innovation offsets. While environmental regulation strengthened, it draws a clearer path for locals to develop and innovate (Porter & Linde, 1995). It increased the likelihood for the spillover of reverse innovation by lowering distance between countries (Ghemawat, 2001). Following this argument, scholars have stated that environmental regulation could affect economic growth by triggering innovation, which could also lead to better competitiveness and productivity (Ambec et al., 2013). An example is the BYD electronic cars produced in China. It was not until the Chinese government rolled out intense environmental regulations (i.e. road space rationing1) to reduce the national dependence on imported oil and to reduce pollution before the company started to develop their own electronic vehicles and expand globally.
Empirical studies point out that companies have now realized that embracing environmental regulation could generate better performance (Hajer, 1995). Scholars also found that companies are even willing to comply with stricter environmental regulation through a voluntary regulatory system such as the ISO14001 (Prakash & Potoski, 2006). According to Lyon and Maxwell (2004), companies are likely to gain
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extra surplus and can cut cost by integrating environmental issues into business practices.
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Nie (2009) also found positive effects of environmental regulation on innovation in the Chinese provinces.
In sum, Porter’s theory has claimed that pollutions are the waste of resources, and that strict environmental regulations could create innovation offsets which enables better efficiency (Ambec et al., 2013). This is particularly critical to the contemporary development of developing economies. The shift of orientation from simple pollution control to optimized resource productivity (Porter & Linde, 1995) is perhaps the only hope for developing economies facing severe environmental degradation to balance between environmental preservation and economic growth.
Given that provinces with strict environmental regulations are likely to generate better economic growth due to better innovation possibility, competitiveness, and a lower distance between developed economies, this study hypothesizes:
Hypothesis 1a. There is a positive effect of Environmental Regulation on Economic Growth within the context of Chinese provinces
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development in these economies. Traditional scholars argue that such outcomes are the results of the pollution haven hypothesis (Copeland & Taylor, 1994, 2004, Grossman & Krueger, 1991, 1995).
The pollution haven hypothesis is grounded from the well-known Heckscher-Ohlin model (Stavropoulos et al., 2017), which proposed that due to the natural differences regarding resource endowment and production requirement, the more a country can leverage from its’ environmental context, the more possibility that it could gain a comparative advantage (Jones, 1956). Grounding up from this doctrinal basis, scholars argued that the ecology factors are seen as the input of production and that environmental regulation are the counteract of market failure (Coase, 1960), which force businesses to pay the social cost of their pollutions. The cost of environmental factors depends on how stringent the regulation is (Stavropoulos et al., 2017).
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On a provincial level, the significant difference between states also encouraged the pollution haven hypothesis (Greenstone, 2002). Provinces with lax environmental regulation are more likely to attract dirty industry, and become a pollution haven (He, 2006; Lian et al., 2016). It is also found that the regulation difference between provinces will affect labor demands. Private companies in less environmental-regulated areas perform better regarding labor employment (Liu et al., 2017).
Scholars supporting the pollution haven theory are skeptical of Porter's assumption that eco-friendly innovation would provide high profits and return. If Porter's argument stands correctly, businesses should have invested heavily. Nevertheless, this was often not the case in real life business practices. An OECD (2011) report explained that it was not until the environmental impacts were priced (i.e., through environmental regulation) before firm’s benefited significantly from these innovations. Furthermore, the spillover of such an underdeveloped market is way larger than other innovation.
Other scholars who rejected the pollution haven hypothesis argued that the cost to comply with the regulation only accounts for a little portion of the total production cost (Jaffe, Peterson, Portney, & Stavins, 1995; OECD, 2011; Walter, 1973). The innovation generated may have offset the compliance cost (Levinson, 2009; Porter & Linde, 1995). However, as most of these counter-arguments were studied on the basis of developed economies, the applicability to developing economies are yet to be verified.
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Hypothesis 1b. There is a negative effect of Environmental Regulation on Economic growth within the context of Chinese provinces
The Effect of Trade on Environmental Regulation and Economic Growth
Trade is often seen as one of the most important factors related to economic growth and environmental pollutions (Copeland & Taylor, 2004; Grossman & Krueger, 1991). Scholars have found that it has a positive impact on environmental issues (Dietzenbacher & Mukhopadhyay, 2007; Harrison, 1996; Kavoussi, 1985; Sachs & Warner, 1995). While trade activities induce income, it raised the demand of better environmental quality, also increased the government’s ability to afford the investment of costly environmental preservation (Copeland & Taylor, 2004).
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since it enables developing economies to draw on both global and local resources (Govindarajan & Ramamurti, 2011; Ramamurti, 2009; Williamson & Zeng, 2009). Furthermore, the global demand brought by trade also facilitates this innovation (Govindarajan & Ramamurti, 2011).
However, supporters of the pollution haven hypothesis do not see trade in the same way. They argued that since trade brings about the movement of a country producing goods for the use of another (Suri & Chapman, 1998), it encourages certain pollution-intensive goods to move toward areas with lax environmental regulations, which in turn stimulates the economic growth of those regions (Grossman & Krueger, 1995). The counter-argument of Low (1996) contended that it is not because of the lax environmental regulation but because of the relative labor cost and the resource endowment that attracts these industries. The author also argued that certain high-polluting industries might have predominated the region in their early stage of development, thus international trade is not the one to be blamed of worsening the pollution haven hypothesis.
Scholars also found that developing economies with better trade activities generally experience less pollution-intensive growth than those without (Low, 1996). While trade increased income, it allows local governments to better deal with environmental problems (Copeland & Taylor, 2004). It is also found that economies with better trade flows hold better real GDP growth then those without (Sachs & Warner, 1995).
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growth differs accordingly. However, the net effect of trade does have a positive effect on the relationship between environmental regulation and economic growth.
In sum, this thesis argues that international trade favors the Porter hypothesis over the pollution haven hypothesis in the context of developing economies. What really matters is the degree of trading with strict environmental-regulated countries. Provinces that hold better trading activities are likely to gain more following the Porter Hypothesis.
Conceptualizing spillovers via imports from strict environmental context
It is not the total volume of trade but whom to trade with that matters (Perkins & Neumayer, 2009). Several authors have recognized that the environmental regulation of trade partners’ is also critical to the relationship between environmental regulation and economic growth since it is likely to spillover through trade activities (Baumol & Oates, 1988; Schram, 2000). Vogel (1997) purposed that it is the commitment of the rich countries, particularly those who are strictly environmentally regulated, that are most critical to effective environmental regulation at both regional and global level.
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new technologies that were implemented in the import countries (Perkins & Neumayer, 2009). Trade with strict environmentally regulated countries may also stimulate firms from developing economies to upgrade their manufacturing process and technology to a more modern design due to the pressure of price or quality (Jenkins & Barton, 2002).
On the other hand, a region or country could also import resources and products and export environmental impacts to other nations through trade (Baumol & Oates, 1988; Stern et al., 1996). The pollution haven hypothesis states that the more developing economies trade with strict environmentally regulated countries, the more it could leverage their lax environmental regulation to create a comparative advantage (Copeland & Taylor, 2004). The standard trade theory states that the developing economies are likely to leverage labor and natural resource under the assumption of free trade because they would specialize towards their advantage and natural endowments (Stern et al., 1996). However, technologies with better efficiency brought by strict environmental-regulated countries via imports can increase the resource productivity without sacrificing the specialization of the region.
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understanding of environmental-preservation organizational practices, trade with these countries allow developing economies to learn from their green technology, progressive environmental policies and less-polluting organizational practices (Perkins & Neumayer, 2009).
All in all, both the Porter hypothesis and the pollution haven hypothesis looks upon how environmental regulation from developed economies flows to developing countries. If provinces in China correspond to the theory of the Porter hypothesis, the more a province trades with highly environmentally regulated countries, the more it can leverage environmental regulation and stimulate economic growth. However, if the Chinese provinces have become pollution havens, the more a province trades with highly environmentally regulated countries, the more it could modernize their technologies to achieve better efficiency.
Given that trade could facilitate the Porter hypothesis and weaken the pollution haven hypothesis in the Chinese provinces, the relationship between environmental regulation and economic growth could be positively moderated by the trade with strict environmentally regulated countries. Accordingly, the following hypotheses is proposed:
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Methodology
Research Model
The conceptual model of this research is presented as below (Figure 1).
Figure 1. Conceptual model of the Research
Figure 1 shows the hypotheses of this research and indicates that the proportion of trade imports from strict environmentally regulated countries would moderate the relationship between environmental regulation and economic growth. Considering that economic growth is also affected by other variables, these variables are set as the control variables. Further details will be address in the following section.
Hypothesis 2 Hypothesis 1a & 1b IV: Provincial Environmental Regulation DV: Provincial Economic Growth Moderator:
Proportion of Trade imports from strict environmental-regulated Countries
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Data Sample
This research will be using provinces from China, and measure in two different periods. Considering data availability, the sample will be limited to a number of 12 provinces (See Appendix A). All measurements will be using two-year panel data from the years 2007 and 2012.
The years 2007 and 2012 are especially good samples for analysis because of the significant increase of environmental regulation (as shown in Table 1). There are also significant differences among the 12 selected provinces during this period of time.
Table 1. China Environmental Regulation Stringency 1990 ~ 2015 Data Source: OECD environmental regulation stringency index (OECD, 2018) 0 0.5 1 1.5 2 2.5 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
China Environemental Regulation Stringency 1990 ~2015
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Independent Variable
The environmental regulation stringency of each province is the independent variable of this research. The data for provincial regulation stringency used in this study is taken from the work of Lian et al. (2016). The authors use a comprehensive methodology instead of the traditional single indicator approach for environmental regulation stringency. As mentioned in the research of Lian et al. (2016), instead of measuring single pollutants, the comprehensive methodology they adopted has included the discharge of water, gas emission, and solid waste. The calculated output was shown in the form of “environmental regulation relaxation (ERR)”. A lower ERR score stands for higher environmental regulation stringency and a higher score of ERR stands for lower environmental regulation stringency (see Appendix C.1, C.2).
Dependent Variable
This study uses economic growth as the dependent variable. I will measure the economic growth by using the percentage of Gross Provincial Product (GPP) collected from the Chinese Statistic yearbook and the National Bureau of Statistic of China
National Database (Yearbook, 2007, 2012). This is referenced from the research of
Meyer (1992). To control the size difference between each province, I will use the Gross Provincial Product per capita to factor out the effect. The currency unit of my research will be using Chinese Yuan (¥). The calculation of economic growth will be using the following form,
𝐆𝐫𝐨𝐰𝐭𝐡 ＝ ( 𝑽𝒂𝒍𝒖𝒆𝒕
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Moderator
To test the effect of foreign trade, specifically on how the environmental regulation stringency of trade’ partner affects the relationship between provincial environmental regulation and economic growth, I will be targeting the proportion of trade with high stringency countries from each province.
As mentioned in the literature review, the trade inflows from strict environmentally regulated countries allow provinces to learn from their green technology, progressive environmental policies and less-polluting organizational practices (Perkins & Neumayer, 2009). While also supported by Vogel's (1997) argument, “The key to effective environmental governance at both the regional and global level is the commitment of rich countries”, it is particularly the spillover from strict environmentally regulated countries that matters. In this case, even though a province might have high level of imports from both strict and weakly regulated countries, how trade affects the relationship between environmental regulation and economic growth within a province still depends on the strict countries.
First, to identify the environmental regulation stringency of foreign trade partners, I will be using the environmental regulation stringency index provided by World
Economic Forum Global Competitive report (Schwab, Porter, López-Claros, & Forum,
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high rates of environmental regulation stringency. I will collect the top 20 countries with the strictest environmental regulation (see Appendix F) from the year 2007 and 2012 respectively.
Next, I will be using the Total Value of Import Commodities through Custom (by region) data provided by each provincial bureau of statistics and provincial port
authority. Such data provides a detailed information of the countries each province
trade with. I will then divide the total trade by the trade from the 20 chosen countries; this will provide us the proportion of trade from strict environmental-regulation countries of each province. Last, I will standardize this moderator data and then multiply it by the standardized value of the independent variable, provincial environmental regulation. The calculated figures will be used to measure the moderating effect of environmental regulation on economic growth.
Control Variable
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Variables description and Data access
Variables Description where to access?
Independent Variable
Provincial environmental regulation
§ Following the research of Lian et al. (2016).
Dependent Variable
Provincial Economic Growth § Calculated using the growth formula, using Gross
Provincial Product (GPP) per capita from 2006-2007,2011-2012 as data. § Regional data retrieve from
the statistical bureau of each province
Moderator Percentage of Trade imports from strict environmental regulation countries.
§ Total value of import commodities through custom (by region) retrieved from provincial bureau of statistics and provincial port authority. § Environmental Stringency
index retrieve from World Economic Forum
Competitiveness Report Control § Coastal proximity
§ Number of Patent applied and approved
§ Illiteracy rate (education) § Life expectancy
§ Previous year GPP per capita growth
§ Total foreign-funded investments
Collected from:
§ National bureau of statistics of China
§ Statistics bureau from each province
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Analysis Approach
The data will be analyzed through STATA using a two-period panel regression analysis. I will run two regressions. The first regression is to measure the relationship between environmental regulation and economic growth (hypothesis 1 & 2), and the second regression is to measure the influence of trade’ environmental regulation context on the relationship between environmental regulation and economic growth (hypothesis 3).
Statistic Model
The following formula will be used for testing the hypotheses: 𝑌78 = 𝛽;+ 𝛽=𝑋?@+ 𝛽A(𝑋?@𝑋CD) + 𝛽FGH𝑋FGH+ 𝜀
The 𝑌78 is the provincial economic growth (dependent variable), 𝛽 as the slope of the parameters while 𝛽; stands for the intercept. 𝑋?@ is provincial environmental regulation and 𝑋CD is the moderator, foreign trade’ environmental regulation stringency. The cvi are the control variables which includes cv1, coastal location; cv2, patents applied and approved; cv3, illiteracy rate; education level; cv4, life expectancy;
cv5, previous year economic growth; cv6, foreign-funded investments; 𝜀 are the residual errors.
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Heteroskedasticity and Collinearity Test
It is essential to make sure that the variance of residuals is equal at all values, this assumption is also known as homoskedasticity. Given that most research tests for heteroskedasticity to examine that the model of analysis fulfilled homoskedasticity. A White’s test for heteroskedasticity is performed, showing a result of p = 0.4038, denying the alternative hypothesis of existing heteroskedasticity. The scatterplot in Appendix E also shows that the data are randomly dispersed. Hence heteroskedasticity does not exist in this case. I also test the correlation coefficient to make sure there is no multicollinearity. The Variance inflation Factor (VIF) test showed one control variable, the foreign-funded investment, have reached a score of 7.7, however as Hair, Black, Babin, Anderson, and Tatham (1998) suggested, a VIF below 10 is in general acceptable. Multilinearity does not seem to be a problem. All other variables scored below 5.
Random or Fixed Effect Analysis
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Empirical Results
Descriptive Statistics
The following Table (Table 2) provides the descriptive statistics for the 12 Chinese provinces in this study. Appendix G provides the correlation table of the variables.
Variables Std. Dev. Mean Min Max
Economic Growth 0.07 0.149 .0340 0.337
Provincial Environmental Regulation 0.03 0.979 0.885 1 High ER Import * ER 0.68 -0.051 -1.178 1.918 Previous Year Economic Growth 0.04 0.156 0.085 0.250
Coastal Proximity 0.48 0.666 0 1
Illiteracy Rate (Education) 1.86 3.257 1.7 8.34
Life Expectancy 1.89 76.78 74.7 80.26
Foreign-Funded Investment 166005 166366.8 17787 625000 Patents Applied and Approved 99550 70337.46 3333 472656
Table 1. Descriptive Statistics
Regression Results
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several scholars support this effect. Acemoglu and Johnson (2007) found that while the increase in life expectancy has significantly increased population, the increase is mainly seen at the young age. Since the working age population did not change, GDP per capita are likely to decrease due to the increased in the denominator. It is also found that the previous economic growth is negatively related to the economic growth. This is supported by Upreti (2015) argument stating that the previous GDP per capita will have an adverse effect on economic growth due to the catching up (convergence) effect.
The second model includes the independent variable of provincial environmental regulation stringency. The F-value (P < 0.02) remains significant, the R-square has slightly increased by 2% and reached 0.5868. This shows that with the inclusion of environmental regulation stringency, the explanatory power has increased. The significance of the control variable coastal proximity has slightly increased (P = 0.107), as well as another control variable foreign-funded investment reaching a p-value of 0.089. Hypothesis 1a suggests a positive effect of environmental regulation on economic growth. The coefficient shows that there is a negative effect (𝛽 = −0.43) but far from significant (P = 0.331). Hypothesis 1a is rejected.
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In Model 3, I included the moderator variable (proportion of trade from strict environmentally regulated countries). The F-value (P < 0.00) showed strong significance of the model, and the R-square has increased 9% and reached to a score of 0.6428. The coefficient of the moderator is positive (𝛽 = 0.038) and significant (P = 0.06), supporting the hypothesis 2, stating that there is a moderating effect that would positively affect the relationship between environmental regulation and economic growth. The results also showed that with the inclusion of the moderator variable, Coastal proximity became significant (P = 0.027) with a positive effect on economic growth 𝛽 = 0.077. Foreign-funded investment are also significant (P = 0.016) and negatively affect GDP per capita growth (𝛽 = −0.00). The results and direction of life expectancy and previous economic growth remain the same; both are strongly significant. The effect of patents applied and approved, provincial environmental regulation and illiteracy rate on economic growth are all insignificant (P > 0.3). The insignificance of patent applied and approved is supported by Brunnermeier and Cohen (2003), which states that there is no evidence found that the increase of regulation enforcement affects innovations.
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Table 2: Regression Results Robustness Test
In this thesis, the moderator is calculated by using the standardized value of provincial environmental regulation and standardized value of the proportion of trade from strict environmental-regulated countries. As mentioned above, the strict environmentally regulated countries were chosen from the list provided by World Economic Forum
Competitive report, and the cut-off for our original design is the top 20 of the list. To
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The results using the top 12 countries (R-square: 0.6428, F-value < 0.00) did not significantly differ from my original model using the top 20 countries (R-square:0.6349, F-value < 0.00). Moreover, all observed effects remain similar in coeffeciency and significance. The model is not sensitive to alternative standard for trade from strict environmentally regulated countries.
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Discussion and Conclusion
A stream of research has concentrated on the issue of environmental regulation and economic growth. However, the majority of these researchers studied the issue from the perspective of developed economies. For this reason, it is essential to examine how developing economies differ. This thesis focused on the study of the moderating effect from international trade’s environmental regulation context on the relationship between environmental regulation and economic growth within the Chinese provinces.
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(1997) also argued that the increase in environmental regulation might have little effect on the economic growth, this is because the compliance cost of a stricter environmental regulation is simply too low to force local governments to choose between economic development and environmental preservation.
Second, the results of our study found that coastal proximity, foreign-funded investment, life expectancy, previous year economic growth do have an effect on the relationship between environmental regulation and economic growth, while illiteracy rate and numbers of patents applied and approved do not.
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a positive moderating effect on the relationship between environmental regulation and economic growth within Chinese provinces.
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Contribution
This thesis is among the first researches studying the moderating effect of the degree of trade with strict environmentally regulated countries on the relationship between environmental regulation and economic growth. Specifically, this study attempts to capture the exact effect of foreign environmental regulation from trade without tangling other complex issues.
Furthermore, apart from most research done on a country-level, this study focused on the provincial level in China. I believe by the exclusion of significant institutional differences (i.e. culture) it allows us to control country-specific factors. Thus, such a sampling approach provides a better view of the environmental regulation – economic growth relationship in China.
Along with the rising awareness of environmental issue, several researchers have recognized that the institutional differences (Cuñat & Melitz, 2012; Hukkinen, 1998;
Levchenko, 2007; Vogel, 2007), environmental regulation specifically in this case,
enable companies to leverage the differences and to earn surplus from the foreign
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Limitation and Future Research
The lack of data availability is one of the biggest issues as we can only retrieve data for two years (2007 and 2012) due to the data unavailability of provincial trade details. Even though several provincial statistics bureaus and the Chinese statistic yearbook have provided detailed information, over half of the provinces in China do not provide detail and complete data. The results of our research remain tentative until better data and resources become available.
Furthermore, the provincial environmental regulation data is collected from the work of Lian et al. (2016), which includes waste emission, water discharge and solid waste. However, environmental regulation could be more complicated if other aspects were taken into consideration, such as energy consumption and forestry preservation. Research on developed economies may also have different benchmark compared to developing economies. As Low (1996) argued, developing economies may have a strong emphasis on global issues such as climate change, developing economies in general worried more about domestic health and pollution issues. Due to such considerations, environmental regulation may be different and would require careful interpretation. Another limitation is that we see provinces as independent units. In this case, we do not consider the leakage of environmental regulation between provinces. Future research could consider studying how environmental regulation between provinces interacts and make sense.
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Appendices Appendix A - Selection of Sample Provinces
Province Data for Environmental
regulation stringency (2007~2012)
Gross Regional product per capita
(2007~2012) (including industrial details)
Foreign Trade import and export index according to country (2007~2012) *Beijing O O O *Shanghai O O O *Jiangsu O O O *Tianjin O O O *Anhui O O O *Guangdong O O O *Shandong O O O *Fujian O O O *Hunan O O O *Chongqing O O O *Liaoning O O O *Shanxi O O O Tibet O O X Xinjiang O O X Qinghai O O X Shaanxi O O X Ningxia O O X Inner Mongolia O X X Guizhou O O X Hebei O O O Heilongjiang O X X Hainan O O X Guangxi O O X Yunnan O O X Jilin O X X
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Appendix B - Coding for Coastal Proximity Control Variable
Coding for the control variable coastal proximity
Picture were modified for the academic use of this paper only. Original photo retrieved from Wikimedia.
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Appendix C.1 - 2007 Environmental Regulation Stringency (Relaxation)
Province Environmental regulation relaxation Province Environmental regulation relaxation Shanghai 0.000972 Heilongjiang 0.019452 Beijing 0.001595 Hainan 0.020321 Tianjin 0.001270 Anhui 0.025542 Henan 0.001289 Shaanxi 0.029594 Zhejiang 0.001323 Gansu 0.034664 Jiangsu 0.00148 Chongqing 0.036243 Hebei 0.002989 Liaoning 0.045477 Shandong 0.003069 Sinkiang 0.056426 Fujian 0.008044 Yunnan 0.059805 Jilin 0.009522 Guizhou 0.093366 Sichuan 0.014296 Shanxi 0.114291
Inner Mongolia 0.015088 Guangxi 0.124063
Hunan 0.015714 Guangdong 0.129222
Jiangxi 0.016251 Ningxia 0.246192
Hubei 0.017674
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Appendix C.2 - 2012 Environmental Regulation Stringency (Relaxation) Province Environmental regulation
relaxation Province Environmental regulation relaxation Shanghai 0.000326 Anhui 0.013201 Beijing 0.000916 Hebei 0.015604 Guangdong 0.001137 Sichuan 0.024208 Shandong 0.001896 Gansu 0.029038 Fujian 0.001921 Chongqing 0.031082 Hubei 0.002294 Jiangxi 0.034042 Zhejiang 0.002889 Shaanxi 0.038308 Jiangsu 0.003629 Yunnan 0.040243
Tianjin 0.004461 Inner Mongolia 0.044709
Jilin 0.007029 Sinkiang 0.049154 Heilongjiang 0.00909 Ningxia 0.055144 Liaoning 0.010725 Guangxi 0.058043 Hainan 0.014015 Guizhou 0.073110 Hunan 0.014702 Shanxi 0.080537 Henan 0.012302
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Appendix D – Hausman Test
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Appendix F – Stringency of Environmental Regulation (World)
2007 2012
Rank Country ERS Rank Country ERS
1 Germany 6.7 1 Germany 6.4 2 Denmark 6.6 2 Finland 6.4 3 Austria 6.6 3 Switzerland 6.3 4 Sweden 6.5 4 Austria 6.3 5 Switzerland 6.5 5 Denmark 6.1 6 Finland 6.4 6 Sweden 6.1 7 Norway 6.3 7 Luxembourg 6.1 8 Netherlands 6.2 8 Netherlands 6
9 New Zealand 6.2 9 New Zealand 6
10 Luxembourg 6.2 10 Japan 5.9
11 Belgium 6.1 11 Norway 5.9
12 Japan 6 12 Rwanda 5.9
13 United Kingdom 5.9 13 Belgium 5.8
14 France 5.8 14 Australia 5.8
15 Canada 5.8 15 Seychelles 5.8
16 Australia 5.8 16 Ireland 5.6
17 Iceland 5.7 17 Puerto Rico 5.6
18 Singapore 5.7 18 Singapore 5.6
19 Czech Republic 5.5 19 Iceland 5.5
20 Taiwan 5.4 20 Oman 5.5
97 China 3.0 67 China 4.7
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