The,Impact,of,Environmental,Regulation,on,FDI,Spillover,Effects:,A,Cross-Provincial,Study|on The bank of

　　Abstract: Using correlated data from thirty Chinese provinces for the years between 2000-2009, this paper examines the impact of FDI spillover and environmental regulation on the progress of industrial technology in China as well as the impact of environmental regulation on the marginal effect of FDI. Empirical results show that while FDI spillover has a negative effect, enhanced environmental regulation has a positive effect. Environmental regulation also has a significant impact on the marginal effect of FDI spillover on industrial technology development. Separate studies on state-owned and private enterprises suggest that environmental regulation has a heterogeneous effect on industrial technology progress and the marginal effect of FDI spillover on industrial technology progress.
　　Key words: FDI spillovers, environmental regulation, technological progress
　　JEL Classifications: F21, L24, O19
　　1. Foreword
　　Many developing countries have adopted favorable policies to attract FDI with the expectation that it will facilitate technology transfer and generate positive spillovers. Theoretical and empirical studies, however, have failed to reach a consensus on technology spillover effects from FDI for host countries. While some studies indicate that FDI creates substantial, positive spillover effects (Sadik and Bolbol 2001; Barrell and Pain 1999), and while most policy makers believe that FDI brings positive technology spillover effects to the host country, certain empirical studies weaken this view. In spite of using both macro- and micro-level data, these studies identified no technology spillover effects from FDI in host countries, particularly in developing countries. In these studies, technology transfer from foreign investors generated very limited, and sometimes even negative, spillover effects (Aitken and Harrison 1999; Veugelers and Cassiman 2004).
　　FDI has been a key driver of China’s sustained economic growth since the early 1980s. Policies on foreign capital inflows demonstrate that China expects foreign firms to introduce not only capital flows but also advanced technologies and managerial experience, Chinese enterprises can acquire the advanced technologies and managerial techniques with the entries of FDI (Lu 2008). However, the verdict of FDI spillover effects on China’s enterprises is mixed. Some studies believe that FDI creates a definite spillover effect for China’s economy (Xie 2006). Others suggest that such effects are insignificant (Zhao, Zhang 2006). Finally, other studies show that instead of contributing to indigenous technological development, FDI actually impedes innovation in China’s indigenous enterprises (Chen, Lin 2009). 　　Inconsistent results indicate that the relationship between FDI spillover effect and technology progress of local firms is not monotone. It also means that FDI does not automatically produce spillover effects. Increasing evidence suggests that institutional factors play a significant role not only on FDI inflow and outflow but also on whether FDI can generate spillover effects (Alfaro et al. 2004; Alfaro et al. 2009; Kwon and Chun 2009). Given the unique nature of China’s economic transition, the spillover mechanism is severely constrained by institutional and other factors (Jiang and Zhang 2008). Hence, a desirable institutional environment is conducive not only to the attraction of FDI but also to the realization of its technology spillover effects. Increasing economic globalization, also intensifies the role of policy and institutional factors. For instance, the strictness of environmental regulation is, now more than ever, highly correlated with a country’s competitive advantage. Environmental regulations increase costs by forcing firms to adopt pollution mitigation technologies, restricting the production of pollution-intensive goods, and reducing the input of specific factor portfolios (Xing and Kolstad 2002).
　　Given their underdeveloped economy, developing countries normally attach less value to environmental regulation and set lower environmental standards compared with developed countries. In order to keep their competitive capabilities and bypass strict environmental standards in their home countries, pollution-intensive manufacturers have relocated to developing countries, where they face looser environmental standards (this is known as the “Pollution Haven” Hypothesis). At the same time, developing countries with strict environmental standards have incentives to lower their environmental standards for pollution-intensive industries to attract more foreign capital inflows (the “Race-to-the-Bottom” Hypothesis).
　　As China’s foreign capital inflows have increased, industrial pollution has escalated. Deteriorating environmental quality has focused a spotlight on the issue of whether China has become a “pollution haven”. Using data from twenty-eight Chinese provinces for the years from 1999 to 2004, Liu and Chen (2008) identified a restrictive effect of stricter environmental standards on foreign capital and a significant impact of environmental standards on the regional distribution of China’s foreign capital inflows. In a similar study using provincial panel data from 1994 to 2006, Chen (2009) examined the relationship between regional distribution of foreign capital and environmental standards and also identified a significant restrictive effect. This indicates that local governments deliberately relaxed environmental standards to attract FDI. Dean et al. (2009) found that pollution-intensive industries from Hong Kong, Macau, and Taiwan were attracted to the mainland’s relaxed environmental policies, though the study did not explore how this affects investment decisions by other countries. Again, however, not all studies agree that China is a “pollution haven.” According to Zeng (2010), while environmental regulation negatively affects FDI inflow, it does not appear to be the primary factor affecting volume of FDI inflows. 　　While these studies have focused on the impact of environmental regulation on FDI inflow, few studies have explored the effect of stringent environmental regulations on FDI spillover effects. Nonetheless, we argue that China’s increasingly strict environmental standards have an impact on corporate performance and may also affect whether FDI can generate positive spillover effects. Using relevant data for thirty Chinese provinces, autonomous regions, and municipalities from the years 2000 to 2009, this paper studies the impact of environmental regulation on regional industrial development and on FDI’s marginal spillover effects. Results indicate that (1) FDI spillover impedes regional technological development, (2) that enhanced environmental regulation promotes regional technological progress, and (3) that the intensity of environmental regulation has a significant impact on the marginal effect of FDI spillover. Separate analyses on state-owned and private enterprises across regions show that environmental regulation intensity may have a varied impact on technological development and FDI spillover, depending on the type of industry.
　　This paper is structured as follows: Part I explains the estimation model, Part II identifies data sources and defines variables; Part III presents results; Part IV compares empirical results for different types of enterprises; and Part V offers conclusions.
　　2. Estimation Model
　　In order to examine the relationship between productivity, FDI inflows, and environmental regulation, this paper defines the following estimation model:
　　(1)
　　Here, i and t respectively denote region and time, and TFPit denotes the productivity of region i at time t; and FDIit-1 is the indicator of spillover effects from FDI in that region. Given the potential time lag of technological spillover effects from FDI, the numerical values of FDI with a one-phase lag are used. EPit is the indicator of regional environmental regulatory intensity; is vector, which denotes other relevant control variables for various regions, and is the corresponding coefficient vector. denotes unobservable regional heterogeneous effects, while denotes the random error term. The model also includes the fixed effect term , which is used to reduce deviations in the estimate caused by measurement errors and omitted variables.
　　In order to identify whether the marginal effect of spillover on productivity () is subject to the degree of environmental regulation (), we assume that regional FDI spillover, marginal productivity, and degree of environmental regulation have the following dynamic relationship: 　　(2)
　　Here, represents same-phase interactions between FDI spillover effects and degree of environmental regulation. When , there is a complementary effect between spillover and the impact of environmental regulation on technological progress. When , there is a supplementary rather than complementary effect. reflects the impact of environmental regulation intensity on the marginal effect of technology progress derived from positive spillover. When , stricter environmental regulation enhances the marginal effect of FDI spillovers. On the contrary, when , the marginal effect is diminished. The overall impact of increased environmental regulation on the marginal effect of technological development can be assessed using the expression .
　　Substituting equation (2) into equation (1) gives us:
　　(3)
　　In which ,
　　.
　　Equations (1) and (3) can be turned into dynamic equations by including the lag terms of explanatory variables. Lag terms of explanatory variables are useful for reflecting the dynamic features of technological development and act as a proxy for omitted variables.
　　(4)
　　
　　(5)
　　In which is the order of lag of inserted explanatory variables.
　　OLS estimation of equations (4) and (5) will cause deviations and inconsistencies. This paper mainly uses GMM, which can process endogenous explanatory variables in the model. Given the two-way feedback between FDI spillover effect and productivity, FDI spillover effect variables and cross terms of FDI spillover effect variables are processed as endogenous variables in this paper.
　　3. Data Source and Variable Definition
　　Sample data for calculating regional productivity and FDI spillover effects are from China Statistical Yearbooks (2001-2010). Data for Tibet are missing, and data for private enterprises span only 2005 to 2009. These data primarily include industrial value added, fixed asset net value, total number of employees, gross industrial output (including foreign-funded and foreign-cooperative enterprises), and product sales revenue.
　　Environmental regulation intensity indicators are compiled using the following data: total volume of industrial waste water discharge, volume of industrial waste water discharge meeting discharge standards, volume of industrial sulfur dioxide emissions, and volume of industrial sulfur dioxide removed. Statistics for calculating regional technology level and input are from the China Science and Technology Statistical Yearbooks (2001-2010). For this input, we use the following data: full-time or full-time equivalent R&D staff and regional R&D spending. In order to increase data comparability, industrial value added and fixed asset investment for all regions are based on the constant prices of the year 2000, and the industrial value added deflator and fixed asset investment price deflator are all calculated using data from the China Statistical Yearbook. Definitions and calculation methods for variables are provided below. 　　3.1 Regional Productivity Index (the Solow residual, TFP)
　　Our calculation uses the Cobb-Douglas production function and assumes that the production function has constant returns to scale. The Solow residual is calculated using through the equation below:
　　(6)
　　Equation (6) contains the unknown parameter to control economies of scale in the production function. is the logarithm of industrial value added (RMB 100 million) for all state-owned and large non-state-owned industrial enterprises across regions (after applying the year 2000 constant-price deflator). is the annual average balance ( RMB 100 million) of net fixed assets of all state-owned and large non-state-owned industrial enterprises. Again, this uses the 2000 constant-price deflator for figures across all regions. Finally, is the annual average number of employees (unit: 10,000 people) from state-owned and large non-state-owned industrial enterprises across regions. Estimation of equation (6) is conducted using variable coefficients of the panel data cross section.
　　Lastly, when evaluating the productivity of state-owned vs. private enterprises, we used data from provincial-level state-owned and state-controlled firms and provincial-level private firms.
　　3.2 FDI Spillover Effect (FDI present rate)
　　The spillover effects from FDI are measured by the ratio of product sales revenue of industrial enterprises with foreign investments (including those from Hong Kong, Macau, and Taiwan) to that of all state-owned and non-state-owned industrial enterprises above designated size.
　　3.3 Environmental Regulatory Intensity
　　Wastewater discharge compliance (WA) ratio is measured by the ratio of regional wastewater discharge in compliance to the total discharge of industrial wastewater.
　　The industrial sulfur dioxide removed ratio is measured by the ratio of regional industrial sulfur dioxide removal to production (which in turn is the sum of industrial sulfur dioxide removal and discharge).
　　3.4 Control Variables
　　Proportion of R&D staff (RDP) is measured by the ratio of regional R&D staff (RTE) to total employees.
　　R&D expenditure (RDE) is the ratio of regional R&D spending to regional GDP.
　　Since China’s economy is to a significant extent managed by the government, this indicator GOV represents the ratio of general budgetary spending to GDP within a given region .
　　Finally, we calculate trade openness (TRADE) as the ratio of total import/export in regions of destination and origin divided by regional GDP. 　　4. Results
　　Table 1 shows the results of GMM estimation using equations (4) and (5). The explanatory variable is the productivity calculated using equation (6), whose lag order is 2, i.e. P=2. The variable of FDI spillover effects is FDI existence rate, which is defined as an endogenous variable. The variable of environmental regulatory intensity is the current-phase and one-phase-lag numeric values of the industrial wastewater discharge compliance ratio and the industrial sulfur dioxide removal ratio. In the model, we find that all Sargan statistics cannot disprove the original assumption that instrumental variables are valid. The m1 term, representing the existence of first-order autocorrelation in the residual error of the test difference equation, is significant at level of 1 percent. The m2 term, representing the existence of second-order autocorrelation, is not significant at the 10 percent significance level. Hence, we can assume that our model configurations are valid.
　　Column (1) of Table 1 shows the regression results of equation (4) when the industrial wastewater discharge compliance ratio is taken as the indicator for evaluating environmental regulatory intensity. Coefficients of the lag terms of explanatory variables (TFP (-1) and TFP (-2)) are significant at the 1 percent level, and the coefficients of the industrial wastewater discharge compliance ratio in both the current phase and with a one-phase lag are all significantly positive. This indicates that stricter industrial wastewater regulation is favorable to technological development across regions. Column (2) shows results when the industrial sulfur dioxide removal ratio is taken as the indicator for evaluating environmental regulatory intensity. The coefficient of variable FDI (-1) remains significantly negative, suggesting a negative impact of FDI spillover on regional industrial development. The coefficient for the industrial sulfur dioxide removal ratio with one-phase lag is negative but not significant, while the coefficient for the current phase term is significantly positive, which suggests increased regulation of sulfur dioxide emissions is conducive to regional industrial development.
　　Columns (3) and (4) show results for equation (5), which examines the impact of environmental regulatory intensity on the marginal effect of FDI spillover. This paper defines the FDI spillover effects variable and its cross term setting the evaluation indicator of environmental regulatory intensity (EPFDI (-1) and EPFDI (-2)) as endogenous variables. Column (3) shows results for industrial wastewater discharge compliance. The coefficient of variable EP is positive but not significant, suggesting that stricter regulation of current-phase industrial wastewater discharge can be a driver of regional industrial development (although the effect is not very significant). The coefficient of EP (-1) is negative but not significant, the coefficient of variable FDI (-1) is significantly negative at the 1 percent level, and the coefficient of cross term EPFDI (-1) is significantly positive at the 1 percent level, indicating a mutually complementary effect of increased industrial wastewater FDI spillover on regional industrial progress. The coefficient of EPFDI (-2) is significantly positive at the 1 percent level, indicating that increased regulatory intensity of industrial wastewater discharge has enhanced the marginal effect of FDI spillover on regional industrial development. In other words, enhanced wastewater regulation contributes positively to the marginal effect of FDI spillover effects on regional industrial development. This indicates that enhanced environmental regulation will encourage foreign-funded enterprises to adopt more advanced, energy-efficient, and low-pollution technologies when establishing operations in China. 　　Column (4) shows results when sulfur dioxide is used as the primary indicator. The coefficient of variable EP is significantly positive, indicating that, as for wastewater, stricter regulation of industrial sulfur dioxide emissions in the current phase are conducive to technological development across regions. Coefficients of EP (-1) and FDI (-1) are all significantly negative at the 1 percent level, and the coefficient of EPFDI (-1) is positive but not significant, suggesting that the complementary effect of enhanced regulation on marginal FDI spillover effects is insignificant. The coefficient of EPFDI (-2) is significantly positive at the 10 percent level, indicating that enhanced environmental regulatory intensity of industrial sulfur dioxide also promotes the marginal effects of FDI spillover on regional industrial development.
　　Among the control variables included in the equations, the coefficient of R&D staff proportion (RDP) is significantly negative under all circumstances except those in column (3), indicating that the R&D activities across regions impeded rather than promoted regional industrial technology progress. A possible reason is that foreign-funded and foreign-cooperative enterprises import technologies from parent companies for their in-house R&D teams to learn. Hence, “R&D” activities may merely be training. The coefficient of the R&D spending ratio is significantly positive in both Columns (1) and (2) and positive but not significant in Columns (3) and (4), which suggests that a higher proportion of R&D spending is conducive to regional technological development. A significantly negative coefficient for government economic intervention (GOV) suggests that local government’s intervention is unfavorable to regional industrial progress. On the other hand, a significantly positive coefficient for trade openness (TRADE) indicates that regional technological progress may increase with a region’s openness.
　　The above analysis shows that FDI impedes regional technological progress while increased environmental regulation promotes it. Environmental regulatory intensity is shown to have a significant impact on the marginal effect of positive spillover effects from FDI. Increased environmental regulation of industrial wastewater discharge and sulfur dioxide emissions not only have a mutual complementary effect on regional technological progress, but enhanced regulation also contributes positively to the marginal effects of regional technological development. 　　5. Results for State-owned vs. Private Enterprises
　　Table 2 shows results for equations (4) and (5) when SOE productivity across regions is taken as an explanatory variable. Columns (1) and (2) show results when industrial wastewater discharge compliance and industrial sulfur dioxide removal are used as environmental regulatory intensity indicators in equation (4). Here, the coefficient of the FDI spillover effect variable is significantly negative at the 1 percent level, indicating that technology spillovers from FDI impede the technological development of Chinese enterprises across regions. Aside from the coefficient of industrial sulfur dioxide removal with one-phase lag, coefficients of regulation intensity indicators are all significantly positive, which indicate that increased environmental regulation is conducive to the Chinese enterprises’ technological development across regions.
　　Columns (3) and (4) show results for equation (5). In all regression results, the coefficients of variable EP are all significantly positive, which suggest that increased, current-phase environmental regulation promotes the technological development in state-owned industrial enterprises. When the environmental regulatory intensity indicator is the wastewater discharge compliance ratio, coefficients of EP (-1) and FDI (-1) are all significantly negative, and coefficient of EPFDI (-1) is significantly positive, which indicate a mutually complementary effect between increased regulation of industrial wastewater and the effect of FDI spillover on the technological progress of state-owned enterprises across regions. In addition, the significantly positive coefficient of EPFDI (-2) suggests a positive influence on marginal positive spillover effects from FDI. When sulfur dioxide emissions is used instead of wastewater compliance, the coefficient of FDI (-1) is significantly negative and the coefficients of EP (-1) and EPFDI (-1) are all negative but not significant, which indicates that regulation in this area does not have the same positive effects as that of wastewater.
　　For state-owned enterprises, FDI is shown to impede technological development within Chinese state-owned enterprises, while increased environmental regulation is shown to have a positive effect. The degree of environmental regulation also has significant impact on FDI spillover. We observe a mutually complementary effect between an increased degree of industrial wastewater regulation and the marginal positive spillover effects of FDI inflows. However, we simultaneously observe that an increased degree of sulfur dioxide emission regulation does not produce the same effects, indicating that positive returns may be limited to certain areas of regulation. 　　Table 3 shows results for equations (4) and (5) in private enterprises. Columns (1) and (2) show results of current-phase and one-phase-lag industrial wastewater and sulfur dioxide compliance ratios in equation (4). Here, the coefficients of FDI spillover effect variables are all significantly negative, which indicates that spillover effects from FDI inflows negatively influence technological progress in private industry. Except for a significantly positive coefficients in the current-phase term of the industrial sulfur dioxide removal ratio, coefficients for other environmental regulatory intensity indicators are all significantly negative. As the coefficient of the one-phase-lag term for industrial sulfur dioxide compliance (negative) is higher than the current-phase term(positive), we can deduce that increased environmental regulation is unfavorable to technological development in private enterprise.
　　Columns (3) and (4) show results for equation (5). Here, the coefficient for the current-phase term of sulfur dioxide compliance is significantly positive and the current-phase term for wastewater compliance is positive but not significant, which suggest that increased current-phase environmental regulation promotes technological development within private enterprises. When industrial wastewater is used as an indicator of environmental regulatory intensity, the coefficient of EPFDI (-2) is significantly negative, which indicates that increased environmental regulatory intensity of industrial wastewater discharge reduces the marginal positive effects of FDI spillover on technological development. When sulfur dioxide emissions are used as the indicator, the coefficient of FDI (-1) is positive but not significant, the coefficients of EP (-1) and EPFDI (-1) are all significantly negative, and the coefficient of EPFDI (-2) is positive but not significant, which indicate that increased current-phase environmental regulatory intensity of sulfur dioxide and FDI spillover are all unfavorable to technological development within private enterprises
　　The above results indicate that FDI has negative spillover effects for technological development across regions in China. Despite the mutually complementary effect between increased current-phase environmental regulation of industrial wastewater and the impact of FDI spillover on technological development in private enterprises, increased current-phase industrial wastewater regulation is a contributor to reduced marginal effect of positive spillover effects from FDI. The same is true for current-phase sulfur dioxide regulation. Therefore, from an overall perspective, increased environmental regulatory intensity is unfavorable to technological development in private enterprise 　　In short, separate analyses on state-owned and private enterprises across regions show that spillover effects from FDI inflows impede rather than promote progress. Enhanced environmental regulation promotes technological development within state-owned enterprises but slows it for private enterprises. In addition, degree of environmental regulation has a heterogeneous effect on FDI spillover. There is a mutually complementary effect between increased regulation of industrial wastewater and the marginal effect of FDI spillover for both state-owned and private enterprises. Increased wastewater discharge regulation contributes positively to the marginal effect of FDI spillover for state-owned enterprises, but it also reduces the marginal effect of FDI spillover for private enterprises. Increased regulation of industrial sulfur dioxide, on the other hand, does not significantly affect FDI spillover for either kind of enterprise. Finally, stricter current-phase regulation of sulfur dioxide is unfavorable to technological development within private enterprises.
　　6. Conclusions
　　Our findings show that spillover effects on technological development from FDI inflows are negative across regions, while increased environmental regulation promotes such development. Environmental regulatory intensity, too, has a significant effect on the marginal effect of FDI spillover.
　　Separate analyses on state-owned and private enterprises across regions also reveal that FDI not only fails to promote technological development of state-owned and private enterprises but in fact may even impede such development in private enterprises. In addition, environmental regulatory intensity has a heterogeneous effect on FDI spillover, and increased current-phase environmental regulation of industrial wastewater has a mutually complementary effect with the impact of FDI spillover on state-owned industrial enterprises and private enterprises. Increased regulation of industrial wastewater discharge is a contributor to the marginal effect of FDI spillover on technological development within state-owned enterprises but is a detriment to the marginal effect of FDI spillover on technological development within private enterprises. Increased regulation of sulfur dioxide emissions has a small but insignificant promotional effect on the impact of FDI spillover on technological development within state-owned enterprises, and increased current-phase regulation of industrial sulfur dioxide emissions is shown to be unfavorable to the technological development of private enterprises. 　　In conclusion, our analysis shows that FDI does generate positive technology spillover effects for China’s industries, regardless of region. Therefore, Chinese enterprises should rely predominantly on independent innovation rather than on technology transfer from foreign-funded enterprises. In addition, China should encourage the introduction of advanced foreign technologies and managerial experience in the fields of environmental protection and clean production. From the policy side, the government should enhance oversight of environmental laws and regulations and create policies that give full play to the positive role of enhanced regulation on industrial technological advancement. Finally, China should enhance environmental supervision for foreign-funded enterprises and heavily restrict low-technology, resource-intensive, and highly-polluting foreign-funded projects. This should be complemented by efforts to encourage the entry of foreign-funded firms focusing on environmental impact mitigation, promote foreign investments in high-tech and environmental protection industries, and mandate that foreign capital inflows provide environmental protection. These policies will maximize positive spillover effects from FDI on industrial technology.
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