Environmental regulation, Foreign investment behavior, and carbon emissions for 30 provinces in China

Journal of Cleaner Production xxx (xxxx) xxx

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Environmental regulation, Foreign investment behavior, and carbon emissions for 30 provinces in China Wei Zhang a, Guoxiang Li b, *, Md Kamal Uddin c, Shucen Guo c a

School of Economics and Management, China University of Geosciences, Wuhan, 430074, China School of Public Economics and Administration, Shanghai University of Finance and Economics, Shanghai, 200082, China c School of Economics and Management, Dalian University of Technology, Dalian, 116000, China b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 12 March 2019 Received in revised form 2 November 2019 Accepted 6 November 2019 Available online xxx

Using the panel data of 30 provincial-level administrative regions in China (excluding Tibet, Hong Kong, Macao, and Taiwan), a threshold regression model was used to empirically analyze the impact of environmental regulation and foreign investment behavior on the amount and intensity of carbon emissions. The results showed that: First, there is a significant inverted “U”-shaped relationship between environmental regulation and carbon emissions. With improved environmental regulation, the positive effects of environmental regulation in reducing the amount and intensity of carbon emissions are more obvious. Next, foreign investment behavior under environmental regulations can reduce the amount and intensity of carbon emissions. Finally, In terms of regional heterogeneity, foreign investment behavior in the eastern and central regions can curb carbon emissions, the opposite effect is seen in the western region. With improved environmental regulations for relatively higheemission intensity regions, foreign direct investment (FDI) in loweemission intensity regions can significantly reduce carbon emissions. It is necessary to formulate differentiated environmental regulation based on regional development. Foreign investment behavior should be standardized to improve the quality of FDI and avoid making China a “pollution paradise” for FDI. © 2019 Elsevier Ltd. All rights reserved.

Handling Editor: Yutao Wang Keywords: Foreign investment behavior Carbon emissions Environmental regulation Pollution paradise

1. Introduction Environmental regulation boosts carbon reduction. The report of the 19th National Congress of the Communist Party of China pointed out that “the construction of ecological civilization is the millennium of the sustainable development of the Chinese nation. It is necessary to establish and practice the concept that lucid waters and lush mountains are invaluable assets”. Promoting harmonious coexistence between man and nature is an urgent requirement not only for achieving high-quality economic development but also for meeting people’s growing needs for a better life. It is also an important manifestation of fulfilling the responsibility of great power. At the Conference on Climate Change in Paris, the Chinese government stressed that it would respond actively to global changes with green economy development. Carbon dioxide emissions are the main cause of global warming and of global climate change. China is the largest developing country in

* Corresponding author. E-mail address: [email protected] (G. Li).

the world, and it is also the world’s largest energy producer and second-largest energy consumer. China has a huge level carbon emissions and it is extremely important to reduce these carbon emissions (Zhang and Wei, 2014). The key to fulfilling China’s responsibility as a great power is to vigorously promote energy saving, emission reduction, and a low-carbon economy (Pan et al., 2018a,b,c). To solve its increasingly serious environmental problems and fulfill its obligations as a great power, the Chinese government has formulated a series of environmental standards and environmental policies, increasing investment in environmental pollution control from 2.566
1011 RMB in 2006 to 9.220
1011 RMB in 2016. The investment focuses on “three simultaneous” investments in construction projects, urban environmental infrastructure, and industrial pollution source management. With these policy changes, the Chinese government has committed to improving environmental quality, production processes, and the efficiency of utilization of fossil energy (such as coal, oil, and natural gas), reducing carbon dioxide emissions in production (Asici and Acar, 2018). Foreign direct investment (FDI) has played an important role in China’s response to environmental pollution. Although China’s

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environmental regulation has been strengthened, it still falls far short of the environmental standards of developed countries, and the regulation is obviously insufficient (Wu, 2007). In 2015, according to the Analysis of China’s Environmental Protection Industry Development in 2017, China’s investment in environmental pollution control accounted for 1.3e1.5% of gross domestic product (GDP), and there was a big shortfall compared with the proportion of investment (2.5%) of developed countries such as Europe and the United States. The entry of international capital such as FDI has provided certain financial and technical support for China’s economic development, with advanced production technology and management experience (Tang and Tan, 2015). With the continuous deepening of China’s reform and opening up, foreign-funded enterprises have entered the Chinese market through joint ventures and sole proprietorship, the amount of FDI has been increasing, and the overall situation has maintained an upward trend during recent years. According to the National Bureau of Statistics in 2016, the actual use of FDI in China reached 7.813
1010 RMB, the largest FDI was in the manufacturing industry, followed by the real estate industry. To make use of FDI for the high-quality development of China’s economy, on June 14, 2018, the State Council issued the Notice on Several Measures for Active and Effective Use of Foreign Capital for High-Quality Economic Development, committing to promoting a new pattern of comprehensive opening up. Though FDI brings strong capital and advanced technology, the quality of FDI is uneven, due to the low entry barriers. It also brings a series of environmental problems while developing China’s economy, intensifying the extensive use of resources (Li, 2015; Behera and Dash, 2017). What role does FDI play in controlling the carbon emissions and realizing green development? This paper explores this issue indepth. The main marginal contributions are as follows: firstly, the environmental regulation, foreign investment behavior, and carbon emissions have been included in the same analytical framework. The system has been used to analyze the mode of action and the marginal effect between variables. Secondly, considering the actual development of the region, the carbon emissions have been described from aggregate indicators and intensity indicators. A threshold regression model has been used to analyze the threshold effect of foreign investment behavior on carbon emissions. Finally, considering the heterogeneities of regional economic development and pollutant emissions, the differences in effects between variables in different contexts are discussed. The subsequent structure of this paper is as follows: Section 2 introduces the literature review, and Section 3 proposes a theoretical hypothesis. Section 4 explains the research design, including variables’ selection, model construction, data sources, and descriptive statistics. Section 5 describes the empirical analysis, and Section 6 concludes. 2. Literature review Many scholars have studied the relationship between foreign investment behavior and carbon emissions. Lee (2013) and Zhang and Zhang (2018) believed that the inflow of FDI increases carbon emissions, and this effect has not changed either in the long-term or short-term. When FDI promotes the industrial transfer and economy of the host country, a certain amount of carbon emissions is transferred. For developing countries, FDI is an important source of carbon emissions (Hanif et al., 2019). Khalil and Inam (2006), using time series data from 1972 to 2002 in Pakistan, found a positive impact of FDI on CO2 emissions through co-integration tests. This effect is even more pronounced in low-income countries, where FDI mainly increases carbon emissions (Song and Woo, 2008; Perkins and Neumayer, 2009). Some scholars believe that FDI

has significant technological spillover effects; the widespread application of cleaner-production technologies has a significant positive effect on improving the ecological environment (Tang and Tan, 2015). This can suppress regional carbon emissions (Song and Yi, 2011; Pan et al., 2018a,b,c), but it may have a negative effect on carbon productivity in the adjacent areas (Liu and Hu, 2016). According to Li (2015) and Behera and Dash (2017), foreign investment behavior has a significant threshold effect on China’s carbon emissions. With high human capital, R&D investment, and environmental regulation, foreign investment behavior reduces carbon emissions. Some researchers have studied the impact of environmental regulation on carbon emissions, focusing on the relationship between environmental regulation and carbon emissions. Li and Qi (2011) studied the actual development of China, showing that environmental regulation can curb carbon emissions and meet the development requirements of energy conservation, emission reduction, and a low-carbon economy. This is mainly due to the spillover effect of economic agglomeration (Wang et al., 2018a,b). Zhang and Wei, 2014 and Bin Li et al. (2017) believed that the direct impact of environmental regulation on carbon emissions is an inverted “U”-shaped curve. When environmental regulation is strengthened continuously, the impact changes from “green paradox” to “anti-driving emission reduction”. With optimization of both economic structure and industrial structure, the efficiency of utilization of resources improves towards a cleaner transformation (Asici and Acar, 2018). At the same time, the impact of environmental regulations on carbon emissions has significant regional heterogeneity. Berman and Bui (2001) and Wang et al. (2018a,b) found that, when faced with a large scale of enterprise agglomeration, the technology spillover effect is significant. High environmental regulation intensity can improve production efficiency and reduce CO2 emissions (Lanoie et al., 2008; Pan et al., 2018a,b,c). In areas with high industrial agglomeration, the intensity of environmental regulation is increased to reach the inflection of CO2 emissions under a high scale of industrial agglomeration (Wang et al., 2018a,b) and improve carbon productivity (Pan et al., 2018a,b,c). Environmental regulation has an important impact on foreign investment behavior. FDI is a double-edged sword that has a serious effect on China’s economic growth and environmental pollution. Environmental regulation, an effective means to solve environmental pollution, significantly affects foreign investment behavior. Predriksson and Millimet (2002) argued that differences in environmental regulation are important factors in FDI. Liu et al. (2014) also put forward similar views. The increase of environmental regulation reduces the motive of FDI, and the relationship between environmental regulation intensity and FDI has obvious heterogeneity. The impact of environmental regulation on polluting multinational enterprises is particularly pronounced, and the polluting industries tend to invest more in countries with laxer environmental regulations (Chung, 2014). There are significant regional differences in China’s environmental regulation intensity (Pan et al., 2015). The low environmental regulation intensity has attracted new polluting FDI enterprises, leading to the “pollution shelter” hypothesis being established in China (Wu, 2007; Yang et al., 2018; Hao et al., 2018). Environmental regulation has had positive effects on foreign-invested enterprises, promoting their innovation capability (Zhou et al., 2018). The host country’s environmental regulation and transnational environmental management will positively stimulate the technological innovation of FDI enterprises, which promotes the quality of enterprises in the region, attracts high-quality FDI enterprises, and improves environmental performance for FDI enterprises (Jin et al., 2019). By summarizing and analyzing the existing research, scholars

Please cite this article as: Zhang, W et al., Environmental regulation, Foreign investment behavior, and carbon emissions for 30 provinces in China, Journal of Cleaner Production, https://doi.org/10.1016/j.jclepro.2019.119208

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have studied the relationship between environmental regulation and carbon emissions/environmental regulation and foreign investment behavior/foreign investment behavior and carbon emissions, focusing on the role of variables. Although some studies hold that environmental regulation affects foreign investment behavior, there is no systematic mechanism analysis and empirical test of how this behavior changes, and how it affects carbon emissions. In view of this, this paper expands the research scope of the existing literature. 3. Mechanism analysis The impact of environmental regulations on carbon emissions is temporally heterogeneous. This paper mainly describes the environmental regulations and measures the environmental regulation intensity of a region based on the investment in environmental pollution control. The investment in environmental pollution control includes investment in urban environmental infrastructure, investment in old industrial pollution source control, and “three simultaneous” investments in construction projects. Environmental regulation is one of the important factors affecting carbon emissions. The short-term impact and long-term impact of environmental regulation on carbon emissions are significantly different. In the short-term, local governments tend to change the investment structure to avoid the fact that environmental regulations have a great inhibitory effect on regional economic development. Investment in environmental pollution control is used for urban environmental infrastructure construction, with decreased investment in old industrial pollution source control and decreased “three simultaneous” investments in construction projects, which reduces the costs of enterprise pollution control and production. Urban environmental infrastructure construction increases energy and resource consumption, which has a positive effect on carbon emissions. According to the “green paradox” theory, the supply of primary energy sources, such as coal, oil, and natural gas will increase with increasingly strict environmental regulation policies. The fossil energy prices are reduced with the energy demand stimulated in the short term and the increased carbon emissions (Sinn, 2008). In the long-term, under the ecological civilization construction, it is the general trend to reduce pollution intensity and improve environmental quality. To improve the regional green technology innovation, the government will continue to increase the investments in environmental pollution control and the old industrial pollution source control, and the “three simultaneous” investments in construction projects, which are long-term effective projects with obvious technological innovation effects. The support for green technology innovation of manufacturing enterprises should be increased to solve the insufficient enterprise innovation, improving the energy resource utilization and reducing carbon emissions. Hypothesis 1. Environmental regulation may increase carbon emissions in the short-run, but it will have a significant inhibitory effect on carbon emissions in the long-run. Environmental regulation affects foreign investment behavior, which plays an important role in carbon emissions. FDI under environmental regulations will significantly reduce carbon emissions. As China’s environmental regulation increases, the quality of FDI is increasing. The environmental regulation policy is an important threshold for FDI, technology introduction, and industrial transfer, and the foreign investment behavior changes due to the influence of environmental regulation. The improved environmental regulation increases the environmental governance cost of polluting foreign-invested enterprises, and screens the FDI. To a

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certain extent, the entry of polluting foreign capital has been inhibited. The cleaner-production FDI has been motivated to promote the green transformation of China’s industry and the utilization of energy resources and to reduce carbon emissions during the production. Improving environmental regulation has played a role of “decontamination and clearing” in FDI, and their interaction stimulates reduced carbon emissions. The introduction of foreign advanced green production management can optimize the production processes of enterprises, improve management efficiency, and bring spillover effects to Chinese enterprises. Improved awareness of environmental protection on the part of enterprises can promote environmental protection and carbon reduction in the country. Hypothesis 2. With the improved environmental regulation, foreign direct investment will have a significantly inhibitory effect on carbon emissions. The interaction between environmental regulation and foreign investment behavior can reduce carbon emissions, but the impact may have significant regional heterogeneity. In the developed eastern region, the environmental regulation is relatively high, and the strict environmental policy (Gregmar et al., 2018) has led to a gradual increase in the production costs of polluting foreigninvested enterprises. This creates a good entry for cleanerproduction FDI, which will reduce the carbon emissions in the eastern region in the long-term. In the underdeveloped central and western regions, economic growth is emphasized due to promotion-based incentives. While improving environmental regulation, it may change the investment structure of environmental pollution controldreducing the investment in old industrial pollution source control and the “three simultaneous” investments of construction projects, reducing the supporting expenditure of enterprises and the enterprise production cost. The central and western regions have become the “pollution shelters” of polluting foreign investment, losing the survival advantages of cleaner-production foreign capital, which increases carbon emissions in the central and western regions. In the regions with low emission intensity, economic development has a path dependence on cleaner-production methods. Market-incentive environmental regulation provides financial support for the foreign-invested enterprises to carry out green technology innovation, which attracts high-quality, cleaner-production foreign capital. The multiplication effect of technological innovation is easier in loweemission intensity regions, which curbs carbon emissions. The opposite effect may occur in the regions of high emission intensity. Hypothesis 3. Influenced by environmental regulation, foreign direct investment in loweemission intensity regions and developed regions is more conducive to reducing carbon emissions.

4. Study design 4.1. Variables’ selection and sample selection (1) Explained variables. Carbon emissions (ce) and carbon emission intensity (ci) have been selected as absolute and relative indicators to measure carbon emissions, and the primary energy (coal, oil and natural gas) consumption in 30 provinces (excluding Tibet) has been converted to standard statistics. The converted coefficients as shown in Table 1. Using the correlation coefficients as shown in Table 1, the primary energy consumption has been converted into carbon emissions. The specific conversion process is as as shown in Eq. (1) and Eq. (2):

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W. Zhang et al. / Journal of Cleaner Production xxx (xxxx) xxx Table 1 Converted coefficients of primary energy. Converted standard coal coefficient (kg standard coal)

Carbon emission coefficient (t(c)/t)

Coal: 0.714 Oil: 1.429 Natural gas: 1.330

Coal: 0.748 Oil: 0.583 Natural gas: 0.443

Data source: Energy Research Institute of National Development and Reform Commission.

Table 2 Portion of the investment in urban environmental infrastructure in eastern, central and western regions (%). Year

Eastern region

Central region

Western region

2014 2015 2016

0.597 0.545 0.583

0.639 0.588 0.609

0.617 0.626 0.616

Data source: 2015e2017 China Statistical Yearbook On Environment.

Eirt ¼ Qirt ,dr CO2it ¼

X ðEirt , rr Þ

(1) (2)

where Qirt is the physical quantity of r-type energy use in i province in the t-th y; Eirt is the standard quantity (104 t) of r-type energy use in i province in the t-th y; dr is the coefficient of standard coal converted from the physical quantity of r-type energy; rr is the coefficient of carbon emissions of r-type energy; and CO2it is the carbon emissions (104 t) in i province in the t-th y.(See ) With the rapid economic growth, China’s energy consumption and CO2 emissions have increased year by year, which has an important impact on the ecological environment. To promote highquality economic development, meet the needs of people’s improved lives, and achieve international carbon emission reduction targets, China has made unremitting efforts in controlling carbon emissions in recent years. For example, remarkable results have been obtained in accelerating the adjustment of industrial structure and energy utilization structure, developing new energy and renewable resources, and improving relevant laws and regulations. In 2017, China’s coal consumption accounted for 60.4% of total energy consumption, with a year-on-year decrease of 1.6%. The proportion of clean energy consumption, such as hydropower, nuclear power, and wind power in the total energy consumption has increased year by year, reaching 20.8% in 2017, with a year-onyear increase of 1.3%. The structure of energy utilization has been optimized. China’s carbon emission intensity has shown a downward trend. In 2017, the CO2 emissions of national ten thousand RMB GDP fell by 5.1% on a year-on-year basis, with a decrease of 46% compared with 2005 (data is obtained from Statistical Bulletin on National Economic and Social Development in 2017). (2) Explanatory variables. Firstly, environmental regulation is the threshold of this paper. Environmental pollution control investment (erl) has been selected to measure environmental regulation, including the investment in urban environmental infrastructure, the investment in old industrial pollution source control, and “three simultaneous” investments in construction projects. The higher investment in environmental pollution control indicates greater environmental regulation. Environmental regulation is an important factor affecting carbon emissions. Many scholars at both home and abroad regard emissions’ taxes, environmental pollution control investment, sewage fees, and energy intensity as the indicators for measuring the intensity of

environmental regulation (Ma et al., 2014; Li, 2015). But the investment indicators of environmental pollution control are used widely in the literature. Based on the indicator suitability and research characteristics, this paper has adopted environmental pollution control investment as the measurement indicator for environmental regulation variables. In recent years, the amount of investment in environmental pollution control in China has been increasing. In 2016, it reached 9.220
1011 RMB, of which the investment in urban environmental infrastructure was 5.412
1011 RMB, accounting for 58.7% of the total investment in environmental pollution control (data is obtained from National Bureau of Statistics of China in 2016). As shown in Table 2, in the current environmental pollution control investment, the investment in urban environmental infrastructure accounts for the largest proportion in all regions, and the proportion of investment is more than 50% in the eastern, central, and western regions. The proportion of investment is relatively small for the old industrial pollution source control and the “three simultaneous” investments in construction projects, which contributes to green technology innovation, energy conservation, and emission reduction. There is also a certain difference between the regionsdthe investment in urban environmental infrastructure construction in the eastern developed regions is lower than that in the central and western regions. The eastern region spends more on the old industrial pollution source control and the “three simultaneous” construction projects to reduce carbon emissions from the source and promote regional green development. Secondly, foreign investment behavior. This paper takes foreign investment behavior as the explained variable of the model; it is expressed by the amount of FDI (fdi). The relevant data of FDI are obtained by multiplying the actual amount of FDI by the exchange rate of the US dollar and the RMB in that year. Foreign investment behavior is investment behavior carried out by either a foreign enterprise or a foreign individual in China for profit, which affects economic activities and carbon emissions. With the opening up of China’s foreign investment policy, the investment environment has improved, and FDI has progressed steadily. In 2016, China’s actual use of foreign investment reached 8.132
1011 RMB. FDI from Asia accounts for the largest proportion of FDI sources, but it has been declining in recent years. FDI from developed economies in Europe and the United States has shown accelerated growth. In 2016, investment in China from the EU and North America increased by 40.44 and 19.47%, respectively. The foreign investment in industrial structure has been significantly optimized, and the FDI in services, high-tech industries, and advanced manufacturing industries has maintained good growth. In 2016, the actual use of foreign capital in tertiary industry other than the financial industry was 5.399
1011 RMB, with a year-onyear increase of 2.18%. The number of high-tech industries and advanced manufacturing industries attracting FDI also maintained a growth rate of more than 2%. The proportion of FDI of the manufacturing industry in the total FDI has shown a downward trend since 2005. From the perspective of regional distribution, the data comes from the 2008e2017 Report on Foreign Direct Investment in China revealed that the proportion of FDI in the

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eastern region has been maintained at approximately 80% of the total FDI, whereas that in the central and western regions has remained at approximately 20%. (3) Control variables. The status of green technology innovation is measured by the number of green technology innovations (et) in the provinces of China. The number of green technology patent applications and authorizations indicates that more green technology innovations mean stronger regional technological innovation capability as well as a greater inhibitory impact on carbon emissions. Industrial structure (tia) is also an important factor affecting carbon emissions, and industrial structure changes have led to changes in energy utilization. This paper has selected the proportion of tertiary industry in GDP to indicate changes in industrial structure. The per capita GDP has been used to measure the absorption capacity of a region (pgdp). The stronger the ab-

Based on the theoretical model analysis, a corresponding measurement model has been established to empirically analyze the impact of environmental regulation and foreign investment behavior on carbon emissions and intensities. The relationship between variables may be non-linear. The panel threshold regression model is a nonlinear econometric model, whose essence is to consider the threshold value as an unknown variable in the empirical model; construct a piecewise function of the regression coefficient of the explanatory variable; estimate the threshold value endogenously, including single, double, triple thresholds and so on; and then estimate the parameters of different threshold intervals (Yang et al., 2019). In view of this, first of all, without considering the moderating effect of foreign investment behavior, the threshold regression model has been used to analyze the effect of environmental regulation on carbon emissions. Referring to Yu and Qian (2017), the following model has been established:

      lnYij ¼ a0 þ x1 lneriij lnerlij  q1 þ x2 lneriij q1 < lnerlij  q2 þ / þ x3 lnerlij lnerlij > qq þ x4 lngrij þ x5 lnetij þ x6 lnriij þx7 tiaij þ x8 lnpgdpij þ x9 lnecij þ x10 lneriij þ x11 lnfdiij þ 9ij

sorption capacity, the easier it is to accept advanced management experience and production technology, which is another important factor affecting carbon emissions. Higher resident income (ri) means stronger spending power and greater consumption of energy resources, which, in turn, generates more carbon emissions. It is expressed by the per capita disposable income of urban residents. In areas with high government receipts (gr), the special expenditures on pollution control and technological innovation are relatively high, and they are more capable of controlling carbon emissions. The standard of energy consumption (ec) is a direct factor affecting carbon emissions. A larger standard quantity of energy consumption means higher carbon emissions.

The functional relationship between each factor and carbon emissions has been established to analyze the impact of input factors on carbon emissions. Based on the Kaya model of energy carbon emissions by, some adjustments and supplements have been made, as shown in Eq. (3):

(3)

where Z is the function of Xh (h ¼ 1, 2, …, n). Assuming that gz is the average rate of change of Xh over a certain period, and gz is the rate of change of explained variable Z, Eq. (3) can be changed into Eq. (4):

Z0 expðgz tÞ ¼ PXh0 ðgz tÞ

(4)

where Z0 and Xh0 are the initial values of the corresponding variables. It can be found that the sum of the rates of change of the explaining variables is the rate of change of the explained variables. The factor analysis is simplified as shown in Eq. (5):

gz ¼ g1 þ g2 þ / þ gn

(6)

where Y is the explained variables, including carbon emissions (ce) and carbon emission intensity (ci); i is the time dimension; j is the regional latitude; q1 ; …qq are the threshold values of the model; a0 is the intercept term; x is the regression coefficient; and 9ij is the error term. Secondly, considering the moderating effect of foreign investment behavior, its possible nonlinear relationship has been verified. Here, FDI has been used as a threshold variable to analyze the impact of foreign investment behavior on carbon emissions under environmental regulation. The following model has been established.

  lnYij ¼ a0 þ x1 lneriij ,lnfdiij lnfdiij  q1   þ x2 lneriij ,lnfdiij q1 < lnfdiij  q2 þ /   þ x3 lneriij ,lnfdiij lnfdiij > qq þ x4 lngrij þ x5 lnetij þ x6 lnriij þ x7 tiaij þ x8 lnpgdpij þ x9 lnecij þ x10 lneriij þ x11 lnfdiij þ 9ij

4.2. Model construction

Z ¼ PXh ¼ X1 ,X2 /Xn

5

(5)

(7)

4.3. Sources of date and descriptive statistics The data of 30 provinces, autonomous regions, and municipalities (excluding Tibet, Hong Kong, Macao and Taiwan) in China from 2008 to 2016 have been used to analyze the effects of foreign investment behavior on carbon emissions under environmental regulation. Primary energy consumption data are from the 2009e2017 China Energy Statistics Yearbook, and investment in environmental pollution control, research and development expenditure, FDI, tertiary industry GDP, and relevant data on GDP are from the 2009e2017 China Statistical Yearbook and the China Statistical Yearbook on Science and Technology. STATA14.0 software is used for regression analysis in this paper. The software has powerful functions with data processing and analysis, and also can better solve the studied problems. As shown in Table 3, the descriptive statistics of variablesdthe basic characteristics of the mean, standard deviation, and minimum and maximum values.

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Table 3 Descriptive statistics of variables. Variable

Mean

Standard deviation

Minimum Value

Maximum values

Observations

ce ci fdi erl ri gr tia et pgdp ec

1.136 0.822 334.527 240.909 2.326 1,520.004 0.427 874.000 4.247 1.254

0.790 0.605 432.409 197.171 0.841 1,418.447 0.091 1,240.757 2.224 0.848

0.101 0.089 0.210 12.200 1.097 55.900 0.283 1.000 0.990 0.138

3.726 2.915 2,485.86 1,416.200 5.769 8,098.630 0.802 7,781.000 11.813 4.513

270 270 270 270 270 270 270 270 270 270

5. Empirical analysis 5.1. Regression results of environmental regulation on carbon emissions Before discussing the transmission effects of FDI, this paper has analyzed the relationship between environmental regulation and carbon emissions. From the absolute and relative indicators, the carbon emissions have been described fully. The threshold regression method has been used to analyze the nonlinear effects of environmental regulations on the amount and intensity of carbon emissions. A test of the threshold effect of environmental regulation on carbon emissions has shown a single threshold effect, with a threshold of 2.272 and a significance level of 5%. The regression results as shown in Table 4. According to the regression results of environmental regulation on the threshold effect of carbon emissions, there is a significant inverted “U”-shaped relationship between environmental regulation and carbon emissions. When the environmental regulation intensity is lower than the threshold of 2.272, environmental regulation will significantly increase carbon emissions. When the environmental regulation intensity is higher than the threshold, environmental regulation will significantly inhibit carbon emissions. That is, the impact of environmental regulation on carbon emissions shows the trend of decline after rising, basically consistent with the research of Zhang and Wei, 2014 and Xu and Yang (2015). In the case of relatively low environmental regulation, environmental regulation increases carbon emissions, because, in the early stage of environmental regulation, the effect of environmental pollution control investment is limited. It plays a role in urban environmental infrastructure construction (gas, central heating, etc.), causing energy resource consumption and pollutant emissions in this process. The “three simultaneous” investment

Table 4 The threshold regression results of environmental regulation on carbon emissions. Variable

Regression coefficient

Standard error

lnerl q1 lnerl >

0.017** 0.013*

0.009 0.007

0.009* 0.011*** 0.026** 0.014* 0.012** 0.079* 1.062*** 0.096 0.976 689.440

0.005 0.003 0.013 0.008 0.006 0.045 0.311 0.143

cycle of the old industrial pollution source control and construction project is relatively long, the pollution control effect is difficult to appear in the short run. With the improvement of environmental regulation, the breadth and depth of environmental pollution control have been extended. With the increased proportion of investment in old industrial pollution source control and the construction projects of the “three simultaneous”, the effect of governance has appeared gradually, and the cumulative effect is becoming more obvious, with declining carbon emissions. In terms of the impact of control variables, green technology innovation and regional absorption capacity have a significant positive effect in reducing carbon emissions, due to the increasing green innovation capability and increasingly rich corporate management experience in the region. Each additional unit of energy consumption, household income, fiscal revenue, and industrial structure will significantly increase carbon emissions. Local financial expansion and industrial structure optimization do not control the carbon emissions. In the future economic development process, the industrial structure needs to be adjusted urgently, and both the scale of pollution control expenditure and the effectiveness of environmental pollution control of local government need to be improved further. The impact of environmental regulations on carbon intensity will be further studied to determine if there is a nonlinear relationship between them. It shows as follows. As shown in Table 5, the double threshold effect of environmental regulation on carbon emission intensity is significant, but the triple threshold effect does not pass the test. Results also indicate that the impact of environmental regulation on carbon emission intensity is non-linear, and there are double thresholds effect, with threshold values of 1.878 and 2.282. There is a significant negative correlation between environmental regulation and carbon intensity. In other words, environmental regulation can reduce carbon emission intensity. As shown in Table 6, when the environmental regulation intensity is lower than the threshold value of 1.878, its influence coefficient on carbon emission intensity is 0.107. When the environmental regulation intensity is between 1.878 and 2.282, the influence coefficient is 0.136. When the environmental regulation intensity is higher than 2.282, the influence coefficient is 0.115. Under certain conditions, although environmental regulation cannot reduce carbon

q1 lnfdi lnri lngr tia lnet lnpgdp lnec cons R2 F value

Note: ***, **, and * indicate significance levels of 1, 5, and 10%.

Table 5 Threshold effect test and threshold value of environmental regulation on carbon emission intensity. Threshold quantity

F value

P value

Threshold value

Single threshold Double threshold Triple threshold

23.610 6.320 1.470

0.053* 0.072* 1.632

1.878 2.282 2.376

Note: ***, **, and * indicate significance levels of 1, 5, and 10%.

Please cite this article as: Zhang, W et al., Environmental regulation, Foreign investment behavior, and carbon emissions for 30 provinces in China, Journal of Cleaner Production, https://doi.org/10.1016/j.jclepro.2019.119208

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Table 6 Regression results of threshold effects of environmental regulation on carbon emission intensity. Variable: lnerl is the threshold variable

Regression coefficient

Standard error

lnerl q1 q1 q2 lnfdi lnri lngr tia lnet lnpgdp lnec cons R2 F value

0.107* 0.136*** 0.115** 0.062** 0.188 0.370** 0.359 0.053 1.951*** 1.146*** 4.525*** 0.818 103.500

0.058 0.035 0.058 0.031 0.202 0.191 0.401 0.117 0.276 0.311 0.621

Note: ***, **, and * indicate significance levels of 1, 5, and 10%.

emissions, there is always a significant negative effect on carbon emission intensity. When the current environmental regulation intensity is between 1.878 and 2.282, the marginal utility of the unit environmental pollution control investment reaches the maximum. The environmental regulation intensities of most provinces in China are lower than 1.878, and only the environmental regulation intensities in Beijing, Ningxia, Inner Mongolia, and Xinjiang are in the second or third interval. The environmental regulation of each region needs to be strengthened. 5.2. Analysis of the moderating effect of FDI 5.2.1. Full sample regression The environmental regulations have been used as threshold variables, and this paper has investigated the moderating effect of foreign investment behavior. The full-sample regression analysis shows that the threshold effect of FDI is not significant. From a national perspective, FDI under environmental regulations may have a linear impact on carbon emissions due to the differences in regional factor endowments. The linear regression results of the fixed effect model as shown in Table 7. The cross-terms of environmental regulation and foreign investment behavior have a significant negative impact on carbon emissions. As shown in Table 7, environmental regulation reduces carbon emissions by affecting foreign investment behavior. The impact coefficient of cross-terms is 0.023. The reason is that environmental regulation has a “screening” effect on FDI. Higher environmental regulation has increased the entry barrier for FDIdrestricting the entry of some high-energy, high-pollution enterprises and improving the overall quality of FDI. Affected by environmental regulation policies, the direction of FDI has changed,

Table 7 Regression results of the impact of cross-terms on carbon emissions. Variable

Regression coefficient

Standard error

lnerl*lnfdi lnerl lnfdi lnri lngr tia lnet lnpgdp lnec cons R2 F value

0.023* 0.354*** 0.060** 0.188*** 0.041* 0.233*** 0.001 0.158*** 1.055*** 0.486** 0.986 1,911.100

0.013 0.037 0.030 0.021 0.023 0.102 0.062 0.058 0.231 0.531

Note: ***, **, and * indicate significance levels of 1, 5, and 10%.

and funds have shifted gradually from pollution-intensive industries to high-tech industries, advanced manufacturing industries, clean energy industries, and other capital- and technology-intensive clean production industries. The capital utilization and effect are improved, which makes foreign investment behavior under the environmental regulation reduce the emissions of pollutants such as carbon dioxide. According to the National Bureau of Statistics of China in 2017, the manufacturing industry had the largest FDI, accounting for 30e50% of the total FDI. But the FDI of the manufacturing industry has decreased from 3.36
1011 RMB in 2010 to 2.263
1011 RMB in 2017, showing a continuous decline. The capital inflows in the real estate industry have also shown a steady and slightly declining trend, whereas the FDI in tertiary industry, such as wholesale and retail, leasing and business services, and the software industry, has continued to rise.

5.2.2. Regional heterogeneity The difference in factor endowments, such as regional economic development level and pollution emission intensity, may lead to significant regional heterogeneity of environmental regulation and FDI impact on carbon emissions. The following is a sub-regional discussion of the relationship between variables. The results show that, although the environmental regulation is used as a threshold variable from the national perspective, the threshold effect of FDI on carbon emissions is not significant, and the national threshold is not significant and will not be stated because it does not affect the logic of this paper. The threshold effect of sub-region in China is more significant. The results of the threshold effect test in the eastern, central, and western regions are as follows as shown in Table 8: As shown in Table 8, affected by environmental regulation, FDI in the eastern, central, and western regions has a single threshold effect on carbon emissions, and the double threshold effect is not significant. This paper only shows the single threshold value of variables and the P value of the significance level. The regression results of the threshold effects in the eastern, central, and western regions as shown in Table 9. As shown in Table 9, in the long-term, foreign investment behavior under environmental regulation can significantly reduce carbon emissions in the eastern and central regions, whereas it has the opposite effect in the western region. The threshold regression results show that, in the eastern region, foreign investment behavior under the environmental regulations has played a role in increasing carbon emissions and then suppressing. In the central region, there is a significant inhibitory effect, that is, the foreign investment behavior under the environmental regulations reduces the carbon emissions in the central region. In the western region,

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Table 8 Threshold value of environmental regulation in eastern, central and western region. Threshold quantity

Eastern region

P value

Central region

P value

Western region

P value

Single threshold

2.016

0.013

2.380

0.073

2.239

0.017

Table 9 Sub-regional regression results of the threshold effect of FDI on carbon emissions under environmental regulation. Variable

Eastern region

Central region

Western region

lnfdi,Iðlnerl  q1 Þ lnfdi,Iðlnerl > q1 Þ lnri lngr tia lnet lnpgdp lnec lnerl

0.018* (0.010) 0.003*** (0.001) 0.163** (0.065) 0.033 (0.046) 0.025* (0.015) 0.007*** (0.001) 0.011 (0.088) 1.133*** (0.000) 0.010 (0.011) 0.0680 (0.263) 0.989 99 140.070

0.019*** (0.004) 0.018*** (0.004) 0.009 (0.033) 0.057*** (0.019) 0.009 (0.026) 0.009** (0.004) 0.055* (0.031) 1.066*** (0.014) 0.005 (0.005) 0.345*** (0.074) 0.986 72 1,619.880

0.015*** (0.005) 0.008* (0.005) 0.295*** (0.066) 0.026 (0.039) 0.137** (0.064) 0.023*** (0.006) 0.256*** (0.063) 1.037*** (0.025) 0.032** (0.013) 0.354* (0.179) 0.981 99 685.540

cons R2 Observations F value

Note: Standard error is in (); ***, **, and * indicate significance levels of 1, 5, and 10%.

foreign investment behavior mainly promotes carbon emissions. The eastern region has a developed economy and high environmental standards, and local governments have implemented environmental policies more vigorously. In the long-run, strict environmental regulation policies have led to the polluting and low-quality foreign capital being replaced gradually by cleanerproduction and high-quality foreign capital. This has played a significant positive role in carbon emission reduction. To reduce costs and maintain the original profits, those low-quality FDIs will shift gradually to the central and western regions, which have lower economic development and lower environmental regulation, taking the central region as their new “pollution shelter”. In the central region, the density of polluting enterprises is much higher than is that in the eastern and western regions. With the increase of environmental regulation, the crowding-out effect of environmental regulation on the polluting FDI is particularly obvious, significantly reducing carbon emissions. In the western region, the proportion of urban environmental infrastructure investment in environmental pollution control investment is generally higher than that in the eastern and central regions (data is obtained from the 2009e2017 China Statistical Yearbook On Environment). The binding of urban environmental infrastructure investment to environmental pollution is significantly lower than that of the investment in the old industrial pollution source control and the “three simultaneous” investments in construction projects, which makes polluting FDI transfer to the western region. This brings not only new production technology and advanced management experience but also more carbon emissions. This paper has grouped the samples according to the differences in pollution emission intensity. Taking the average emission intensity of pollutants in various regions of 156,300 (t/100 M RMB) as a boundary, data is obtained from the 2009e2017 China Statistical Yearbook On Energy. The survey regions have been divided into

loweemission intensity and higheemission intensity regions, based on which the regression analysis was performed. The results of the threshold effect test were as shown in Table 10: As shown in Table 10, in regions with low/high emission intensity, the environmental regulations have been used as threshold variables to test the threshold effect. The results show that the single threshold effect was significant, whereas the double threshold effect was not; thus, the latter has not been displayed in this paper. The threshold regression results for low/high emission intensity regions as shown in Table 11. As shown in Table 11, with the improved environmental regulation, foreign investment behavior can significantly reduce carbon emissions in loweemission intensity regions but increase carbon emissions in higheemission intensity regions. In the regions with low emission intensity, foreign investment behavior in different environmental regulation provinces can reduce carbon emissions, and the carbon emission reduction of foreign investment behavior is more obvious with the improved environmental regulation. In regions with high emission intensity, FDI in environmental regulations increases carbon emissions, which will weaken gradually. This may be due to the cleaner production in the regions with low emission intensity and the wide application of cleaner-production techniques. With the improved environmental regulation, loweemission intensity regions may pay more attention to the quality of FDI while introducing foreign capital with relatively high technologies into the strategic emerging industries to improve the quality of FDI and the economic development in the region. They should avoid becoming a “pollution shelter” for foreign multinationals and reduce regional carbon emissions, making the green technology spillover effects and carbon emission reduction effects of environmental regulation more obvious. In regions with high emission intensity, there is a strong path dependence on extensive production and development, and there are more environmental pollution control investments in the urban environmental infrastructure with weaker environmental constraints. While improving the urban environment, environmental pollution control investments bring new carbon emissions and reduces the effectiveness of environmental regulations. 5.2.3. Further discussion Exploring the relationship between variables, this paper has excluded the influence of the outliers of the explained variables and has observed the impact of foreign investment behavior on carbon emissions. The quantile regression method has been used to perform regression based on the quantiles (0.10, 0.50, and 0.90) of the explained variables. The regression results as shown in Table 12. As shown in Table 12, the emission reduction effect of foreign investment behavior under environmental regulation is weakened after being enhanced. With the increase of quantiles, the absolute value of the regression coefficient of the interaction between environmental regulation and foreign investment behavior shows a

Table 10 Threshold value of environmental regulation in different emission intensity regions. Threshold quantity

Low emission intensity regions

P value

High emission intensity regions

P value

Single threshold

2.637

0.045

2.255

0.010

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Table 11 Threshold regression results for low/high emission intensity regions. Variable

Low emission intensity regions

High emission intensity regions

lnfdi,Iðlnerl  q1 Þ

0.054*** (0.008) 0.094*** (0.008) 0.112** (0.046) 0.129*** (0.033) 0.035 (0.051) 0.209*** (0.063) 1.072*** (0.031) 0.017** (0.009) 0.007 (0.010) 0.456*** (0.148) 126 0.986 370.500

0.012*** (0.010) 0.005 (0.005) 0.246*** (0.062) 0.141*** (0.033) 0.028 (0.059) 0.384*** (0.056) 0.998*** (0.022) 0.022*** (0.006) 0.039*** (0.010) 0.188 (0.179) 144 0.963 617.780

lnfdi,Iðlnerl > q1 Þ lnri lngr tia lnpgdp lnec lnet lnerl cons Observations R2 F value

Note: Standard error is in (); ***, **, and * indicate significance levels of 1, 5, and 10%.

Table 12 Quantile regression results. Variable

Quantile 0.1

Quantile 0.5

Quantile 0.9

lnerl.lnfdi lnerl lnfdi lnri lngr tia lnpgdp lnec lnet cons R2

0.034*** (0.012) 0.105*** (0.031) 0.035 (0.029) 0.026 (0.072) 0.023 (0.031) 0.319*** (0.055) 0.133*** (0.037) 1.033*** (0.020) 0.056*** (0.013) 0.042 (0.221) 0.904

0.044*** (0.009) 0.127*** (0.022) 0.066*** (0.021) 0.158*** (0.051) 0.039* (0.022) 0.190*** (0.039) 0.153*** (0.026) 1.047*** (0.014) 0.004 (0.009) 0.236 (0.156) 0.892

0.014 (0.009) 0.060*** (0.023) 0.012 (0.022) 0.114** (0.053) 0.006 (0.023) 0.059 (0.041) 0.134*** (0.027) 1.044*** (0.015) 0.020** (0.009) 0.104 (0.163) 0.907

Note: Standard error is in (); ***, **, and * indicate significance levels of 1, 5, and 10%.

Table 13 Threshold effect test and threshold value of environmental regulation on carbon emission intensity. Threshold quantity

F value

P value

Threshold value

Single threshold Double threshold

12.800 11.940

0.020 0.032

2.282 2.461

trend of decreasing after rising. In regions with relatively low carbon emissions, the emission reduction effects of FDI in environmental regulations are more pronounced. This is basically consistent with the results of the previous analysis. To ensure the comprehensiveness, accuracy and robustness of the regression results, this paper has used the relative indicator of carbon emission intensity to measure carbon emissions, and has analyzed the impact of foreign investment behavior on carbon emission intensity under environmental regulation conditions. As shown in Table 13. As shown in Table 13, foreign investment behavior under the environmental regulation has a double threshold effect on carbon emission intensity, with the single threshold of 2.282 and the double threshold of 2.461. There is a significant nonlinear relationship between the variables, but the triple threshold effect test of the model is not significant.(See Table 14)

Table 14 Regression results of the threshold effect of foreign investment behavior on carbon emission intensity under environmental regulation. Variable

Regression coefficient

Standard error

lnfdi,Iðlnerl  q1 Þ lnfdi,Iðq1 < lnerl  q2 Þ lnfdi,I(lnerl >q2 Þ lnerl lnri lngr tia lnet lnpgdp lnec cons R2 F value

0.062** 0.028 0.086*** 0.163*** 0.105 0.390** 0.647*** 0.093*** 1.779*** 1.273*** 3.316*** 0.901 105.860

0.028 0.037 0.028 0.046 0.244 0.160 0.258 0.031 0.278 0.122 0.760

Note: ***, ** and * indicate significance levels of 1, 5, and 10%.

This shows that there is a significant negative correlation between foreign investment behavior and carbon emission intensity under the environmental regulation. The regression results show that the double threshold effect of the model is significant, and, under the environmental regulation, foreign investment behavior reduces the carbon emission intensity. In the three regions divided by the threshold, the carbon emission intensity will decrease by 0.062, 0.028, and 0.086 units, respectively, when the FDI increases by 1 unit. Under the condition that other factors remain unchanged, FDI will significantly reduce carbon emission intensity and improve resource utilization efficiency with the improved environmental regulation. The effects of foreign investment behavior under environmental regulation on carbon emissions and carbon emission intensity are basically the same, and the negative correlation is significant in the long-term.

6. Conclusions Foreign direct investment (FDI) is an important driving force for sustained and healthy economic development, and environmental regulation is an important guarantee for the carbon emission

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reduction effect of FDI. By studying the impact of foreign investment behavior on carbon emissions, the following conclusions have been obtained. First, there is an inverted “U”-shaped relationship between environmental regulation and carbon emissions. Next, the interaction between environmental regulation and foreign investment behavior has a significant negative impact on the amount and intensity of carbon emissions. Finally, from the regional heterogeneity, in the eastern and central regions, foreign investment behavior under the environmental regulations can reduce carbon emissions, whereas the opposite effect is evident in the western region. With improved environmental regulation, foreign investment behavior can reduce carbon emission in loweemission intensity regions but increase carbon emissions in higheemission intensity regions. Based on this, this paper makes the following points: First, guiding and regulating the investment behavior of foreign-funded enterprises improves the quality of FDI gradually. Reform and opening up should be deepened to attract FDI and expand business opening. FDI should be guided from secondary industry such as low-end manufacturing to high-tech industry and productive service industry, then the extent of opening-up in service industry has to be improved. For FDI with advanced production technology and management experience, government should formulate preferential supporting measures and give policy support. Second, with the accelerated adjustment of industrial structure, the transformation of production mode is forced to promote regional green development. The adjustment of industrial structure should be enhanced to accelerate the construction of the industrial structure with high technologies and low resource consumption, forcing the transformation of investment structure. Improving the investment of old industrial pollution source control and the “three simultaneous” investments in construction projects. Supporting enterprise independent innovation and technological transformation. Finally, formulating different environmental regulation strategies for different areas in China. The government should formulate different environmental regulation strategies for different areas, improve the environmental regulation in the central and western regions, and improve the quality of FDI while promoting the economic development of the central and western regions. For the eastern region, guiding more capital into high-end manufacturing, productive service industry. Improving regional green technology innovation capability, giving full play to the spillover effect and radiation effect of green technology, and reducing carbon emissions and intensity. This paper studies the relationship among environmental regulation, foreign investment behavior and carbon emissions from the provincial-level administrative regions, but without considering the heterogeneity of urban-level. In the future, it is very meaningful that considering the relationship between variables under the differences of urban economic scale, population scale and industrial scale from the urban-level. Acknowledgment This paper was funded by the Humanities and Social Sciences Research Fund Project of the Ministry of Education of the People’s Republic of China, “Capitalization Operation Research of Enterprise Energy Savings” (Grant No.: 15YJAZH110); Major Project of National Social Science Fund, "China Natural Resources Capitalization and Corresponding Market Construction Research" (Grant No.: 15ZDB163). References 2009-2017 China statistical yearbook. http://tongji.cnki.net/kns55/Navi/HomePage.

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