1. Introduction
At present, the concept of green innovation has become a hot topic because of a tense practical need for sustainable development. Generally speaking, green innovation is equivalent to ecological innovation, or environmental innovation, among others, and is considered to be an innovative activity involving process, system, and service, through which sustainable development aims can be achieved by reducing environmental damage and natural resource consumption. Green innovation plays a role in achieving sustainable development goals (EIO [
1]). In other words, green innovation is not just about new green technology, it covers various kinds of innovations, such as new products, new processes, new services, new business models, and so on (Kemp and Arundel [
2]; Rennings [
3]; Kemp and Pearson [
4]). Accordingly, green innovation of the manufacturing industry can be defined as “green innovation of technology, product, and processes, and corresponding organizational, management, and institutional innovation processes”. It is a systematic and open innovation of behavior and process aiming at green development of the manufacturing industry. From the perspective of input–output, efficiency refers to “the ratio between the input and output of human behavior”. Combined with the definition of manufacturing green innovation, the manufacturing green innovation efficiency can be simply defined as “the ratio between input and output of manufacturing green innovation in a certain period of time”. It is a relative relationship between the input of human, finance, materials, technology, information, and so on, and a certain amount of green innovation output.
The Yangtze River Economic Belt covers 11 provinces and municipalities in eastern, central, and western China. Along the belt, 44% of China’s total industrial output, more than 50% of the total output value of emerging industries, and one-third of China’s universities/research institutions are clustered. Moreover, there are a number of internationally competitive clusters in electronic information, high-end equipment, automobiles, home appliances, textiles and clothing manufacturing, and so on. Therefore, the Yangtze River Economic Belt is considered to be the most strategically supporting and the strongest manufacturing economic belt. However, at the same time, the discharge of industrial sewage and energy consumption account for more than 40% of the total amount in China. Especially, the discharge of chemical oxygen demand, ammonia nitrogen, total nitrogen, and total phosphorus in industrial sewage is close to 50% of the national total. With the economic growth in the Yangtze River Economic Belt, the heavy chemical manufacturing structure also leads to a series of resource and environmental problems. Faced with severe resource and environment constraints and relatively limited innovation resources, how can the manufacturing industry in the Yangtze River Economic Belt achieve more and higher quality green innovation output under certain green innovation input? That is, how to improve the manufacturing green innovation efficiency (hereinafter referred to as “MGIE”)? It is the key scientific and practical problem that needs to be solved for the sustainable development of China’s manufacturing industry.
The driving factors of MGIE are generally discussed from internal and external aspects. Many researchers prefer to use internal factors such as technology push (Horbach [
5]), Research and Development (R&D) input (Baumol [
6]), governance level (Amore and Bennedsen [
7]; Bernauer [
8]), application of new enterprise software and new equipment (Demirel and Kesidou [
9]), and so on. However, there are many other studies using external variables to discuss the driving factors of MGIE. They are market pull (Horbach [
5]), government behavior (Liao [
10]), foreign direct investment (Andonova [
11]), industrial agglomeration (Carlino et al. [
12]), social culture (Huang and Li [
13]), pressure of regulators (Huang et al. [
14]), and so on. What should be noted is that the externality of green innovation activities, market failure, and path dependence of technological innovation make it more difficult for enterprises to obtain benefits from green innovation activities and improve MGIE (Marin [
15]; Rubashkina et al. [
16]) to a certain extent. Consequently, it is urgent to improve MGIE with the help of government. As such, government R&D subsidies and environmental regulations are important tools of government intervention.
First, most scholars believe that government support for R&D activities is conducive to improving MGIE (Hud and Hussinger [
17]). R&D subsidies from government can fill the gaps in R&D funds of enterprises, stimulate R&D initiatives because of profit maximization (Seitz and Watzinger [
18]), and further promote green innovation behavior (Wang et al. [
19]). However, Guan and Chen [
20] had a different idea. They found that, compared with corporate capital itself, the role of government funds in improving MGIE is likely to be weaker or even invalid. Wallsten [
21] even found that government R&D subsidies had a crowding-out effect on the R&D input within enterprises. As a result, there was a significant negative relationship between government R&D subsidies and MGIE.
Second, environmental regulations have been regarded as an important variable in investigating MGIE. On the one hand, environmental regulations have a “follow-the-cost effect” (Greenstone [
22]). In the short term, the “hard” conditions imposed by the government will increase the cost of green innovation activities, consequently reduce the input of enterprises in green innovation activities, and thus hinder the improvement of MGIE (Christainsen and Haveman [
23]; Gray et al. [
24]). On the other hand, some scholars point out that environmental regulations have an “innovation compensation effect” (Rio et al. [
25]), which implies that the compliance cost incurring from environmental regulations can be shared and MGIE be improved in consequence. The goal of improving the competitiveness of manufacturing enterprises while protecting the environment can be achieved (Simpson and Bradford [
26]). However, some scholars think that the relationship between environmental regulations and MGIE is not simply linear. The relationship between the two can be affected by pollution intensity (Li and Tao [
27]), regional heterogeneity (Zhang et al. [
28]), regulatory tool type (Shen et al. [
29]), and other factors.
In general, there are still some deficiencies in the study of the impact of government intervention on MGIE. First, the current studies on government R&D subsidies and environmental regulations on MGIE generally focus on the impact of individual government intervention on MGIE. However, some scholars have noticed that the government R&D subsidies have a regulatory impact on the relationship between environmental regulations and green innovation, but they fail to reach a consistent conclusion. Therefore, this paper introduces the interaction between government R&D subsidies and environmental regulations for further consideration. Second, the non-linear relationship between environmental regulations and MGIE has not been properly considered, which means whether or not a turning point exists needs to be tested. Third, the opposite effects of MGIE on government R&D subsidies and environmental regulations are ignored (Li et al., [
30]). If we study the impact of R&D subsidies and environmental regulations on MGIE from only one perspective, endogenous problems may arise, which may have a certain impact on the accuracy of the research and the effectiveness of the policy promulgation and implementation.
Therefore, selecting the Yangtze River Economic Belt of China as the research area, this paper constructs a theoretical analysis framework of the impact of government R&D subsidies and environmental regulations on MGIE. With panel data from 2008 to 2017, taking into consideration of endogenous problems, this paper applies the slacks-based measure (SBM)-data envelopment analysis (DEA) model to measure the level of MGIE in the Yangtze River economic belt, and through the use of panel Tobit model, an empirical test is done to measure the effects of government R&D subsidies and environmental regulations on MGIE in the Yangtze River economic belt. The main contributions of this paper are as follows. First, not only government R&D subsidies, environmental regulations, and the second term of environmental regulations are included in the model, but the interaction term between government R&D subsidies and environmental regulations is considered to evaluate the way government intervention affects MGIE under the combination of the two policies. Second, considering the two-way interaction effect, the instrumental variable method is used to further correct the endogenous problem.
The paper is organized as follows.
Section 3 describes the theoretical basis and proposes three research hypotheses.
Section 4 outlines the research model. Empirical results and analysis are presented in
Section 5. The last section provides a conclusion and several policy implications.
4. Empirical Results and Analysis
4.1. Analysis of Estimation Results
According to the results of MGIE in China’s Yangtze River Economic Belt, it can be found that the truncation characteristics are obvious. In order to effectively correct estimated deviation, this paper adopts the panel Tobit model with left truncation set to 0. The estimated results are shown in
Table 3. At a significant level of 1%, all test results of model’s χ
2(chisq) pass the significance test, which shows that the models are reasonable. At the same time, the results of the Hausman test show that the fixed-effect Tobit model is more valid than the random-effect Tobit model. Therefore, this paper mainly analyzes the results of the fixed-effect Tobit model.
First, at a significant level of 5%, we find that government R&D subsidies are conducive to improving MGIE in China’s Yangtze River Economic Belt. In 2017, the average input of government R&D subsidies in the Yangtze River Economic Belt reached 1757.18 million yuan, which was three times the number in 2009. Meanwhile, compared with 2009, the total R&D input, sales revenue of new product, and number of domestic invention patents of industrial enterprises above a designated size increased by 246.93%, 219.03%, and 609.80%, respectively, in 2017. It can be seen that the increase of government R&D subsidies also promotes the innovation input and output of manufacturing enterprises in the Yangtze River Economic Belt. In other words, compared with the crowding-out effect of government R&D subsidies, the promotion effect is more obvious, and ultimately reflects in the fact that government R&D subsidies can improve MGIE.
Secondly, at a significant level of 10%, there is a “U” shaped relationship between environmental regulations and MGIE in the Yangtze River Economic Belt. After calculation, the value of the inflection point in model 2 is 1.047. Additionally, from the descriptive statistics in
Table 2, we can see that the average level of environmental regulation is about 1.200, a value that passed the turning point and is located on the right side of the U-shaped curve. That is to say, environmental regulation has a positive role in improving MGIE in the Yangtze River Economic Belt. This outcome is consistent with the findings by Deng et al. [
50]. As a matter of fact, since 2015, a series of government documents aiming at strengthening ecological environment protection and green development of manufacturing industry in the Yangtze River Economic Belt have been issued. The themes in these documents include the following: accelerating the green transformation and upgrading of traditional manufacturing industry; strictly control environmental risks of a series of projects along the Yangtze River, such as petroleum processing, chemical raw materials and chemical products production, pharmaceutical production, chemical fiber production, non-ferrous metals, printing and dyeing, paper making, and so on; promote the orderly relocation, transformation, or closure of enterprises with heavy pollution, such as iron and steel, non-ferrous metals, paper making, printing and dyeing, electroplating, chemical active pharmaceutical ingredients (API) manufacturing, chemical industry, and so on; strictly supervise cross-regional transfer of polluting industries; and, lastly, continuously improve the efficiency of resource and energy use and level of cleaner production. Indeed, all of these measures have greatly improved the level of green manufacturing and MGIE in the Yangtze River Economic Belt.
Thirdly, the coefficient of the interactive term between government R&D subsidies and environmental regulation fails to pass the significance test. In other words, government R&D subsidies have no significant positive moderating effect on environmental regulation and MGIE in the Yangtze River Economic Belt. It should be noted that, from the information in the China Procuratorial Statistical Yearbook (2009–2017) and the inspection reports of various provinces in China, the number of cases of corruption, bribery, and malfeasance in the Yangtze River Economic Belt accounted for about 38–40% of the total in China from 2008 to 2016. Under the background of rampant rent-seeking, it is not hard to imagine that, in order to relax the government’s supervision and review, government R&D subsidies are extensively used for rent-seeking, so that the punishment due to environmental regulations is reduced. From this point of view, rent-seeking behavior leads to waste of innovation resources and greatly reduces the effective utilization rate of green innovation input. Therefore, the positive moderating role of government R&D subsidies fails to play to a certain extent.
Fourth, the effects of other control variables on MGIE are as follows:
(1) Enterprise scale. At a significant level of 5%, the enterprise scale has an inhibiting effect on the improvement of MGIE in the Yangtze River Economic Belt. There are a number of large-scale, state-owned steel, automobile, and chemical enterprises with monopoly characteristics in the Yangtze River Economic Belt. These monopoly enterprises have established market leader status and relatively mature R&D and production management system. The cost or risk of R&D or adoption of green technology will exceed the potential increase of reputation or market share. Therefore, the willingness of these enterprises to carry out green innovation is relatively low.
(2) Industrial structure. At a significant level of 10%, industrial structure has an inhibiting effect on the improvement of MGIE in the Yangtze River Economic Belt. Because the industrialization in the middle and upper reaches of the Yangtze River is still at the stage of accelerating development, heavy chemical industry dominated secondary industry plays a main part in these provinces or cities. The extensive development mode characterized by large consumption of resources has led to the centralized layout of a large number of heavy chemical enterprises in the above areas. The phenomenon of “heavy chemical industry surrounding the river” is obvious. Huge industrial sewage is directly discharged into the Yangtze River without being processed, and a large amount of industrial waste gas is discharged in the production process by some high pollution chemical enterprises, which directly leads to a surge in the unexpected output of green innovation in the Yangtze River Economic Belt and, therefore, a slump of MGIE level.
(3) Agglomeration. At a significant level of 1%, enterprise agglomeration has a positive effect on MGIE in the Yangtze River Economic Belt. Making use of advantages such as location, industry, labor, market, and so on, provinces and cities along the Yangtze River Economic Belt have established five cross regional world-class industrial clusters based on FDI, which are electronic information, high-end equipment, automobile, home appliances, and textile and clothing flusters. These clusters provide possibilities for enterprises within them to adopt environmental protection production technology. At the same time, the positive externalities brought about by them can also promote technological progress and expansion of environmental protection technology. As a result, the “Pollution Halo Hypothesis” is reduced and MGIE is improved.
(4) Openness. Openness does not have any statistical impact on MGIE in the Yangtze River Economic Belt. One possible reason is that the human cost of the Yangtze River Economic Belt is increasing year by year. By 2017, the demographic dividend effect of the Yangtze River Economic Belt has gradually disappeared. The total wages of China’s urban employment reached 5,550,817 million yuan, an increase of 309.94% since 2008. In comparison, Laos, Vietnam, Cambodia, and other developing countries adjacent to the upper reaches of the Yangtze River Economic Belt have a greater comparative advantage in human cost. Therefore, some foreign enterprises in the Yangtze River Economic Belt began to shift their investment destination to Southeast Asian countries, which finally leads to an unobvious effect of openness to the improvement of MGIE in Yangtze River Economic Belt.
4.2. Analysis of Endogenous Problems
The two-way causal relationship between government R&D subsidies, environmental regulation, and MGIE will cause endogenous problems. Such problems are solved by using the instrumental variable method, and constructing the panel Ivtobit model. Generally speaking, the ideal instrumental variable is selected from the historical or geographical aspect, so that a direct correlation with endogenous variables can be maintained, and exogenous requirements can be met. Following this principle, together with the consideration of the correlation between fiscal revenue and R&D subsidies, and the non-correlation relationship between fiscal revenue and MGIE, the negative correlation between environmental regulation and the air circulation coefficient, as well as natural phenomena attributing to satisfying the requirements of exogenesis, this paper selects fiscal revenue and the air circulation coefficient as instrumental variables of government R&D subsidies and environmental regulations, respectively (Shen [
51]; Shi and Xu [
52]). As shown in
Table 4, each instrumental variable passes the weak instrumental variable test and exogenous test, which indicates that the selection of instrumental variable is effective. At a significant level of 5%, government R&D subsidies have a positive effect on MGIE, and the positive effect gets stronger. More explicitly, ignoring endogenous problems will underestimate the positive effect of government R&D subsidies on MGIE.
4.3. Robustness Test
The paper firstly replaced the core indicators of government R&D subsidies with its alternatives, and a robustness test is done to the results from the perspective of variables. The proportion of government technology subsidies to the main business income of the enterprise is selected as an alternative indicator of government R&D subsidies.
Table 5 demonstrates the estimation results of the panel Tobit model after adjusting the core indicator with the above alternative. At a significant level of 5%, the government R&D subsidies can promote MGIE in the Yangtze River Economic Belt. At a significant level of 10%, there is a “U-shaped” relationship between environmental regulations and MGIE. Additionally, the positive moderating effect of government R&D subsidies between environmental regulations and MGIE fails to pass the significance test. As compared with the estimation results in
Table 3, it is clear that the estimation results are essentially the same. As a result, we are confident that the empirical outcomes in
Table 3 are robust and reliable.
Secondly, it may take a long time for the government R&D subsidies and environmental regulations on MGIE to perform. Therefore, the lag of government R&D subsidies and environmental regulations is taken into the model again to test whether the effects are consistent in the long term and the short term. The specific results are shown in
Table 6. We can find that, at a significance level of 10%, the government R&D subsidies can promote MGIE in the Yangtze River Economic Belt. The coefficient of the interactive term between government R&D subsidies and environmental regulations fails to pass the significance test. Besides, affected by the selected time limit, the “U-shaped” relationship between environmental regulations and MGIE also fails to pass the significance test. However, generally speaking, the overall results are basically consistent with
Table 3.
5. Conclusion and Policy Implications
By using the SBM-DEA model with consideration of unexpected outputs, this paper measures the level of MGIE in the Yangtze River Economic Belt. With the introduction of the interactive term between government subsidies and environmental regulations and the quadratic term of environmental regulations into the model, the panel Tobit model is further used to empirically test the effects of government R&D subsidies and environmental regulations on MGIE in the Yangtze River Economic Belt. As evidenced from the empirical results, first, government R&D subsidies are conducive to improving MGIE in the Yangtze River Economic Belt. Government R&D subsidies and the economic signals released can provide other external financing opportunities, which is conducive to alleviating the problem of insufficient funds as well as reducing the cost and risk of green technology R&D activities. Secondly, there is a positive “U-shaped” relationship between environmental regulations and MGIE in the Yangtze River Economic Belt, and the level of environmental regulations has passed the inflection point and is on the right side of the U-shaped curve. Because the “innovation compensation effect” exceeds the “follow-the-cost effect” at this point, environmental regulations have a positive role in improving MGIE in the Yangtze River economic belt. Thirdly, the coefficient of the interactive term between government R&D subsidies and environmental regulations fails to pass the significance test. More explicitly, government R&D subsidies fail to effectively stimulate the “innovation compensation effect” of environmental regulation, which indicates that the positive moderating role of government R&D subsidies fails to play its role. Lastly, the characteristics of spatial layout, where a large number of monopoly enterprises agglomerating along the Yangtze River Economic Belt, and the industry structure of heavy chemical enterprise are not conducive to the improvement of MGIE. On the contrary, agglomeration has a significant positive role in improving MGIE in the Yangtze River Economic Belt. In addition, the degree of openness fails to pass the significance test.
The policy implications of this paper are as follows. First, in view of the significant positive effect of government R&D subsidies on MGIE in the Yangtze River Economic Belt, government should guide manufacturing enterprises to increase green innovation input by increasing government R&D subsidies. However, attention should be paid to the study of new methods, so as to avoid the “crowding out effect” and attract more manufacturing enterprises to engage in green technology activities. Second, considering the severe pressure of resources and environment along the Yangtze River Economic Belt, it is still necessary to highlight the important role of environmental regulations in improving MGIE in the near future. Through the establishment of a variety of environmental policies tools that are of command type, market-driven, or social willingness, provinces and cities along the Yangtze River Economic Belt can be guided to develop green manufacturing, advanced manufacturing, and intelligent manufacturing, and further reduce the unexpected output of manufacturing industry. Third, in order to exert the positive moderating role of government R&D subsidies, an optional path is to strengthen the honest construction of government departments along the Yangtze River Economic Belt. This can improve the transparency of government R&D subsidies, and reduce the reverse seeking subsidies of manufacturing enterprises and corruption of government. To ensure the effectiveness of the use of government R&D subsidies and the implementation of environmental regulations, it is important to strengthen the supervision of environmental regulations and take environmental quality as an important indicator of government performance evaluation. Fourth, in terms of control variables, in order to reduce the negative effects of the enterprise scale and industrial structure on MGIE in the Yangtze River Economic Belt, it is necessary to cultivate small- and medium-sized scientific and technological enterprises and promote the marketization reform of large state-owned enterprises with a monopoly characteristic. In the meanwhile, for the purpose of establishing a rational and high-end industry structure of the Yangtze River Economic Belt, attention should be paid to the new technologies, new products, new formats, and novel business models, and efforts should be made to realize the service-oriented, high-end, intelligent, knowledgeable, and low-carbon industry.
6. Discussion
At present, China is committed to building the Yangtze River Economic Belt into a world-famous manufacturing economic belt, similar to the Mississippi River in the United States and the Rhine River in Germany. However, the manufacturing industry along the Yangtze River Economic Belt is facing severe resource and environmental constraints. In order to improve the development quality of manufacturing industry, measures should be taken to improve the expected output of invention patents and develop new products through green innovation, and to reduce the unexpected output of environmental pollution. As an important participant, government intervention will directly or indirectly affect MGIE. In particular, government R&D subsidies and environmental regulations are typical forms. A joint analysis of multiple policies is one of the hot topics of future policy research. The main contributions of this paper is that government R&D subsidies, environmental regulations, and MGIE along the Yangtze River economic belt are included in a unified analyzing framework. The nonlinear characteristics of environmental regulation and the moderating effect of government R&D subsidies are considered comprehensively. The relationship between government R&D subsidies, environmental regulations, and MGIE in the Yangtze River Economic Belt is analyzed.
Nevertheless, this paper has several limitations that can be addressed in future studies. On the one hand, this paper does not consider the fact that there is obvious spatial correlation and interdependence of green innovation, the flow of factors, and environmental pollution among regions. Therefore, it is necessary to include spatial factor as one of the influencing factors of MGIE. In fact, there exist more and more innovation contacts between provinces, and the innovation network is becoming increasingly intensified [
53]. On the other hand, it should be noted that the selection of indicators plays a key role in the conclusions. Even though the indicators have been replaced in the robustness test, there may still be some deficiencies. For example, the actual amount of industrial pollution control completed investment, frequencies of supervision and inspection, government environmental protection expenditure, emission fee/tax, and so on can all be used to indicate environmental regulations. One question that needs further discussion is whether the conclusions will change when other variables are selected for regression.