Analysis of the Influence of Heterogeneous Environmental Regulation on Green Technology Innovation

Abstract

Since its reform and opening up, China’s economy has undergone rapid development and has experienced problems such as the overexploitation of resources and the destruction of the ecological environment. To achieve a balance between economic growth and environmental protection and to follow the sustainable development path, China must implement corresponding environmental regulation policies and vigorously encourage enterprises to pursue green technology innovation. In this paper, environmental regulation is divided into command-and-control, market incentive and voluntary participation. Command-and-control environmental regulation is measured using the entropy method and the logarithm of the pollution discharge fee income in each region is used as the measurement index of market-incentive environmental regulations. At the same time, the logarithm of the number of environmental protection proposals planned by the National People’s Congress and the number of environmental protection proposals planned by the CPPCC is used as the measurement index of voluntary participation in environmental regulations. Based on a regression equation of the effects of environmental regulations on green technology innovation, this paper uses the two-step system GMM method to analyze the panel data of industrial enterprises larger than a designated size in 30 provinces, autonomous regions and municipalities in China from 2006 to 2017. Moreover, the paper compares the effects of command-and-control, market-incentive and voluntary participatory environmental regulations on green technology innovation. The empirical results show that command-and-control environmental regulations initially have an inverted U-shaped effect on green technology innovation and market incentive and voluntary participatory environmental regulations have a U-shaped effect on green technology innovation. A comparison of the three environmental regulation policies shows that the effect of command-and-control environmental regulation is more significant.

1. Introduction

Since the reform and opening up, China’s economy has undergone rapid development and has made remarkable achievements. At the same time, the traditional intensive economic growth mode of high input, high consumption and high pollution has also led to many problems, such as the overexploitation of resources, ecological destruction and serious environmental pollution. Therefore, finding a way to protect the ecological environment while maintaining economic growth has become critical.

In recent years, the Chinese government has attached great importance to ecological environmental protection and has made remarkable achievements in building an ecological civilization. However, environmental protection still has a long way to go. The report of the 19th National Congress of the Communist Party of China in 2017 clearly established the need to accelerate the establishment of a legal system and policy orientation for green production and consumption to build a government-led environmental governance system with enterprises as the main body and the joint participation of social organizations and the public to improve pollution discharge standards, strengthen the responsibility of polluters, and improve environmental credit evaluations, mandatory information disclosures and the effective punishment of offenders and other systems. Moreover, the report emphasized the need to define the red line of ecological protection and to reform the system for supervising the ecological environment [1]. The 2018 government work report also emphasized the pursuit of ecological environmental quality, replacing the previous goal of pursuing economic development [2]. In addition to these policies, many more initiatives have shown that China has put environmental issues on its agenda. Because of the public nature of the environment and the negative externalities caused by environmental pollution, it is necessary for the Chinese government to formulate and implement a series of strict environmental regulations governing environmental pollution to push the country along the path of sustainable development, such as implementing sewage charges, performance standards and emissions trading systems.

The government’s 2019 work report of the State Council [3] stated that green development should be vigorously promoted; green technology innovation is the only way to achieve green development. Green technology innovation is the driving force for building an ecological civilization and only breakthrough green technology innovation can provide technical support for sustainable development. Therefore, green technology innovation aimed at pollution reduction has become a bridge between economic growth and the ecological environment. The “Porter hypothesis” states that strengthening environmental regulations is beneficial for enterprises attempting to carry out technological innovation activities; that is, environmental regulations may make enterprises reduce their pollution emissions and dedicate more available resources to technological innovation. Although enterprises need considerable funds and technical support to engage in technological innovation, the benefits it can bring not only offset the increased costs due to the environmental regulations implemented by the government but also help enhance the competitive position of enterprises in the market. If enterprises gain a favorable and competitive market position through green technology innovation, corresponding performance growth inevitably follows; that is, environmental regulations may play a positive role in promoting the green technology innovation of enterprises [4]. Today, governments and the public are paying increasing attention to environmental protection. Balancing ecological and developmental concerns, realizing the optimal allocation of factors and promoting economic development through green technology innovation to achieve a “win–win” situation for both environmental protection and economic growth have become important and urgent research topics.

The research significance of this paper mainly includes theoretical and practical significance.

(1)

Theoretical significance

Green technological innovation is affected by many factors. Under environmental pressure, the response of technological innovation to environmental regulations is the focus of environmental economists. However, most existing studies do not distinguish environmental regulations. Even if they do, they only discuss the impact of a certain type of environmental regulation on green technology innovation. To improve the operationality of the system of environmental regulations, it needs to be analyzed from the perspective of environmental regulation tools. This paper divides environmental regulation tools into three types: command-and-control, market-incentive and voluntary participation. Based on existing research, this paper analyzes the differences between different environmental regulation tools in terms of their effect on green technology innovation incentives with a view to supplementing and expanding the relevant theories of environmental regulations affecting green technology innovation to a certain extent.

(2)

Practical significance

The report of the 19th National Congress of the Communist Party of China took “adhering to the harmonious coexistence of man and nature” as one of the basic strategies for adhering to and developing socialism with Chinese characteristics in the new era; moreover, this report implemented the strictest ecological environment protection system and formed a green development mode and lifestyle. At present, China’s economic development has entered the green development stage. To achieve green development, we must rely on green technology innovation. However, enterprises implementing green technology innovation should not only bear the economic losses caused by knowledge spillover but also the economic costs caused by negative environmental externalities, making it difficult for them to spontaneously carry out green technology innovation. The government must formulate relevant environmental policies to solve the environmental externalities of green technology innovation, to provide economic compensations for knowledge spillovers and to encourage enterprises to carry out green technology innovation, thereby achieving a win–win situation for economic development and environmental protection.

At present, China is in a transition period from a traditional industrial civilized society to a new ecological civilized society. Finding a development model that meets the needs of ecological protection and economic growth is the focus of the research at this stage. It is of great practical significance to explore how the government should formulate and implement environmental regulation tools to encourage production enterprises to carry out green technology innovation and to explore different environmental regulation tools that stimulate various green technology innovations.

2. Literature Review

At present, there is no consensus in academic circles on the relationship between environmental regulation intensity and green technology innovation. There are two main theories, namely the neoclassical theory and the Porter hypothesis [5]. The neoclassical theory holds that when the technical level and resource allocation of enterprises are fixed, the implementation of environmental regulation policies increases the production cost of enterprises, thus inhibiting their green technology innovation [6,7,8]; that is, the “following the cost theory”. In contrast, the Porter hypothesis holds that an appropriate level of environmental regulation intensity can partially or even completely offset the increased production costs of enterprises due to their compliance with these more stringent policies, thus promoting their green technology innovation; that is, the “innovation compensation theory” [9]. Based on a review of the domestic and international literature, this paper holds that there are four main viewpoints on the relationship between environmental regulations and green technology innovation: environmental regulations inhibit the green technology innovation of enterprises [10,11], environmental regulations promote the green technology innovation of enterprises [9], there is a nonlinear effect of environmental regulations on green technology innovation [12,13] and there is an unclear impact of environmental regulations on green technology innovation [14,15,16].

On the other hand, when analyzing the relationship between environmental regulations and green technology innovation, many scholars assert that the impact of environmental regulations on green technology innovation is reflected in not only the intensity of environmental regulation but also the environmental regulation tools. For example, Rousseau and Proost consider that both the intensity and tools of environmental regulations have an impact on green technology innovation [17].

Xu, Qingrui et al. (1995) conducted a case study of 62 environmental regulation technological innovations in more than 50 enterprises in Jiangsu and Zhejiang and show that command-and-control environmental regulation based on government policies and decrees is the most important source of motivation for enterprises to carry out green technological innovation and, at this time, such environmental regulation tools are more likely to drive enterprises to innovate end-of-pipe treatment technologies. Public opinion pressure—an environmental regulatory tool—can play only a limited role in facilitating enterprises’ implementation of green technology innovations. However, environmental regulations through economic incentives such as sewage charges have a smaller effect on green technology innovation because the cost of sewage collection fines in China is far lower than the cost of carrying out green technology innovation, so many enterprises prefer to pay fines than engage in green technology innovation. Therefore, Xu Qingrui and others propose establishing and improving the incentive system for environmental technology innovation to enhance enterprises’ motivation to engage in green technology innovation. Therefore, we need to address the issue through three main actions. First, the core action is strengthening the command-and-control environmental regulation tool based on the compulsory management of the government as this plays a direct role in the green technology innovation of enterprises. The second area of action is implementing market-incentive environmental regulations based on economic stimulus. Finally, the third action is creating indirect but far-reaching environmental regulation tools for enterprise green technology innovation, including environmental education, industrial policy, technology policy and more [18].

Lv, Yonglong and Liang, Dan (2003) argue that environmental policies have positive and negative effects on technological innovation. They classify environmental policy instruments into twelve types and analyze in detail the possible technological effects of each policy while pointing out that economic instruments, such as emissions charges and emissions trading, can have long-term and continuous incentive effects on green technological innovation. In contrast, command-and-control policies and regulations have a one-time coercive incentive effect on green technological innovation. Therefore, it is ultimately argued that from the perspective of green technological innovation effects, non-command-and-control environmental regulation tools should be used more often, with market-based approaches such as environmental economic policies and information disclosure instruments as the dominant environmental policy tools and command-and-control environmental regulation tools as a necessary complement [19].

From the above literature analysis, it can be seen that the impact of environmental regulations on green technology innovation has been the focus of debate among scholars, but no consistent conclusion has been reached on their relationship. As the understanding of environmental regulation policy deepens, there are still many topics that require further exploration and research.

First, previous studies more often observe environmental regulations as a whole to study their impacts on green technology innovation. The effects of different types of environmental regulation tools are different, making it necessary to differentiate the proposed countermeasures. This paper further subdivides environmental regulation tools into command-and-control, market-incentive and voluntary participation types and analyzes the effects of different types of environmental regulations on green technology innovation.

Among them, command-and-control environmental regulation refers to the mandatory laws, rules, regulations and ordinances made by the government and relevant functional departments to control environmental pollution and protect the environment. Market-incentive-type environmental regulation refers to regulations based on market mechanisms and economic instruments, the mechanism of which is to encourage emissions reductions by raising the pollution cost of polluting enterprises or providing incentives. Market-incentivized environmental regulations mainly include environmental protection tax and fee systems, financial subsidies, emissions trading, ecological compensation pilots, etc. Voluntary participation-based environmental regulations refer to agreements or plans and commitments to protect the environment that are signed voluntarily by enterprises, industry associations or the public under the guidance of the government or because of enterprises’ own environmental awareness. They are in the form of environmental information disclosure systems, unilateral commitments, environmental certification (labels), voluntary public participation, etc.

Second, there is no uniform measurement standard in academic circles for green technology innovation and many scholars use the number of enterprise patent applications for measurement. Generally, enterprises are the main body of innovation activities and the number of patent applications is a direct reflection of their innovation achievements. Patent applications must follow a fixed process and take a long time, so using the current year’s patent application data instead of patent grant data can be a more time-efficient way to examine the impact of environmental regulation policies on enterprise technology innovation.

However, the number of patent applications in general can only reflect the innovation ability of enterprises and cannot reflect the concept of “green innovation”. At present, the State Intellectual Property Office and various statistical yearbooks do not specifically classify green technology patents and data on green technology patents are not directly available. In this paper, to measure green technology innovation more accurately, we retrieve the data on green patent applications as the index of green technology innovation by searching the State Intellectual Property Office according to the international classification of the green patent list (IPC Green Inventory).

The structure of this paper is as follows: the first part is the introduction; the second part is the literature review; the third part is the theoretical analysis; the fourth part is a description of the research design; the fifth part is an explanation of the empirical test and recommendations; the sixth part provides an explanation of the research limitations and proposes avenues for future research.

3. Analysis of the Effect of Heterogeneous Environmental Regulations on Green Technology Innovation of Enterprises

3.1. Analysis of the Effect of Environmental Regulations on the Green Technology Innovation of Enterprises

For the ecological environment, scientific and technological progress is a double-edged sword. On the one hand, technological innovation in the field of environmental protection can help enhance environmental awareness and promote the development of pollution control levels. However, at the same time, using advanced technology to control pollution and to improve the environment may also trigger new environmental crises. Therefore, whether technological innovation can achieve a win–win situation of economic development and environmental protection depends on an understanding of the green direction of technological innovation. Any action to encourage enterprises to carry out green technology innovation must be closely linked to environmental regulation policies and measures to maximize the role of such innovation in promoting environmental protection.

Environmental regulations affect the costs and benefits as well as the supply and demand of green technology innovation. Reconfiguring the resources that enterprises use to invest in green technology innovation activities ultimately affects the timing, scale and degree of the green technology innovation. The effects of environmental regulations on the green technology innovation of enterprises include the “innovation compensation effect” and the “compliance cost effect”, as shown in Figure 1.

Under different environmental regulation intensities, the “innovation compensation effect” and “compliance cost effect” show different influences. During the initial regulation stage, the intensity of environmental regulations is generally weak. Because the cost of environmental regulations accounts for a small proportion of the total cost of enterprises, enterprises cannot attach importance to it. Therefore, enterprises cannot be motivated to carry out equipment transformation or research and development and cannot introduce new equipment and technology, having a “crowding out” effect on enterprises’ green technology innovation [20]. At this time, environmental regulation mainly plays a negative role in “compliance costs”. As the government strengthens its environmental regulations for enterprises, the proportion of pollution control costs that enterprises need to pay out of total costs is becoming increasingly larger, thus forcing enterprises to carry out green technology innovation. When enterprises carry out green technology innovation, the benefits begin to show slowly and the positive “innovation compensation” effect of environmental regulation begins to dominate.

3.1.1. Innovation Compensation Effect

The green technology innovation of enterprises brings the first-mover advantage to enterprises and enterprises voluntarily carry out green technology innovation driven by government subsidies and demand.

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First-mover advantage

The so-called first-mover advantage means that the enterprise that takes the lead in R&D activities and uses new technologies has the first-mover advantage in enterprise competitive activities to occupy a dominant position in market competition. Therefore, for these first-mover enterprises that take the lead in green technology innovation, on the one hand, they provide enterprises with proprietary technology, thus establishing their position as enterprise technology leader and forming a certain competitive advantage. On the other hand, they can take the lead in product and technology research and development, develop the market first, improve market share, reduce product costs, improve enterprises’ economic efficiency and further encourage enterprises to carry out new green technology innovation, develop new markets and form a sustainable virtuous circle.

(2)

Government subsidies

While implementing environmental regulations, the government also implements green technology innovation subsidies for enterprises. Government subsidies may have multiple impacts on the green technology innovation of enterprises. However, theoretically, an enterprise’s receipt of direct financial support from the government and the rational use of it can compensate for the lack of its own funds, thus increasing capital investments in green technology innovation.

(3)

Demand pull

On the one hand, enterprises are constrained by environmental regulation policies and have to carry out green technology innovation. On the other hand, market demand also drives enterprises to carry out green technology innovation. Given the enhancements in the public’s environmental awareness, green, environmentally friendly and pollution-free products have become more popular in the market. To meet the market demand for green products, enterprises actively increase their investments in technology research and development and other aspects of capital and personnel and implement green technology innovation.

3.1.2. Follow-Up Cost Effect

The following cost effect of environmental regulations on the green technology innovation of enterprises is mainly reflected in the crowding-out effect, technology introduction, simple imitation and unknown potential risks.

(1)

Insufficient funds for innovation

Environmental regulations squeeze the innovation funds of enterprises, resulting in insufficient innovation funds. On the one hand, under environmental regulations, environmental resources have the characteristics of economic goods [21]. In response to environmental regulations, enterprises need to pay corresponding fees for using environmental resources. On the other hand, if enterprises do not adopt measures to address environmental regulations, they need to bear corresponding penalties, which eventually lead to an increase in their total costs and a decrease in their total profits, thus affecting green innovation funds.

(2)

Reduced investments in innovation

On the one hand, to meet the requirements of environmental regulations, enterprises must spend more to pay for pollution control facilities or to purchase more advanced pollution control equipment and increase their expenditures on pollution control costs, causing them to invest limited funds in environmental pollution control, which results in a “crowding-out effect” of funds and personnel investments in green technology innovation and research and development.

At the same time, due to the different intensities of environmental regulations in different regions or countries, enterprises transfer production and investments from regions or countries with strong environmental regulations to regions or countries with relatively weak environmental regulations, namely, the so-called “pollution shelter hypothesis”. This method of transferring polluting industries also reduces local enterprises’ share of investments in green technology innovation resources in general.

(3)

Increased innovation risk

Due to substantial investments of funds and personnel and the uncertainty of innovation performance, technological innovation activities face great risks. The implementation of environmental regulations allows green technological innovation to meet not only the needs of their own economic interests but also the objectives of environmental protection, causing increased uncertainty and risks related to green technological innovation.

From the above analysis, it can be seen that the impact of environmental regulations on green technology innovation includes the “innovation compensation effect” and the “compliance cost effect”, with different environmental regulation measures having their own advantages and disadvantages and thus different effects on green technology innovation.

3.2. Analysis of the Effect of Heterogeneous Environmental Regulations on Green Technology Innovation of Enterprises

3.2.1. Command-and-Control Environmental Regulations

Command-and-control environmental regulations refer to the laws, regulations and rules formulated by the government and other relevant functional departments to control environmental pollution and protect the environment, such as product standards, market access and the “three simultaneities” system for construction projects.

We use product standards as an example. As shown in Figure 2, these standards can stimulate and inhibit the green technology innovation of enterprises. First, product standards are specific provisions made for the environmental protection requirements of consumer products. If the technical level of products is lower than that called for in the product standards, enterprises are compelled to carry out technological innovation activities to meet these standards. In this case, product standards can promote the green technological innovation activities of enterprises to a certain extent. However, product standards also somewhat inhibit green technology innovation. If the technical level of an enterprise already allows it to meet product standards and if these standards are not further raised, the enterprise has no motivation to implement further green technology innovation.

3.2.2. Market-Incentive Environmental Regulations

Market-incentive environmental regulations mainly include sewage charges and environmental taxes. It is generally believed that the sewage charge system can effectively promote the green technology innovation of enterprises. Sewage charges give enterprises the opportunity to choose whether to carry out green technology innovation or to pay sewage charges according to their situations. When sewage charges are sufficiently high and enterprises’ products developed through green technology innovation are valued by consumers and bring sustainable benefits, enterprises have greater motivation to actively engage in green technology innovation.

Of course, the sewage charge system also has limitations. First, the sewage charges levied against enterprises must be high enough to stimulate green technology innovation. Second, enterprises have different reactions to the sewage charge system. The effectiveness of this system often requires that enterprises be very sensitive to price, which may not be the case in reality. Finally, if the fees are too high, the regulations lead to an increase in environmental costs for enterprises, which in turn puts pressure on policy makers to reduce fees. Therefore, the sewage charge system may also inhibit green technology innovation.

On 1 January 2018, China officially began to levy an environmental protection tax and announced that the pollution charge system, which has been implemented for nearly 40 years, was officially withdrawn from the historical stage. The environmental tax includes taxes not only specifically collected to protect the environment but also that have other purposes but can nevertheless play a role in protecting the environment. Generally, an environmental tax is a very effective market-incentive regulation tool for protecting the environment and realizing sustainable economic development and such a tax can promote the green technology innovation of enterprises. By increasing or reducing the environmental tax rate, the state can urge enterprises to quit the practice of transferring environmental costs to society and guide them to engage in green technology innovation. However, due to the short period during which environmental taxes have been implemented in China, their effect has not yet been assessed.

3.2.3. Voluntary Participatory Environmental Regulation

Given the great improvements in material living standards, the public has begun to pay increasing attention to environmental protection. Voluntary participatory environmental regulation refers to voluntary agreements or plans and commitments to protect the environment that are initiated by enterprises, trade associations or the public under the guidance of the government or that arise from the environmental awareness of enterprises themselves. Unlike the first two means of environmental regulation, this type of environmental regulation is more voluntary and relies on the spontaneous participation of enterprises and the public rather than passive compliance. Examples include information disclosure and environmental labeling. Theoretically, the public disclosure of information can exert pressure on enterprises to a certain extent, which stimulates enterprises to carry out green technology innovation. However, because information disclosure has not been implemented for a long time in China and because the information publicly disclosed is extensive and systematic and does not involve only a specific environmental element, it may promote overall green technology innovation rather than end governance green technology innovation for a specific environment.

4. An Empirical Analysis of the Influence of Environmental Regulations on Green Technology Innovation in Enterprises

The above analysis of the impact mechanism of environmental regulations on green technology innovation shows that different environmental regulation tools have different effects on such innovation. To further analyze the impact of environmental regulations on green technology innovation, this paper uses provincial panel data on 30 provinces, municipalities, autonomous regions and municipalities directly under the central government in China from 2006 to 2017 (the Tibet Autonomous Region, Hong Kong, Macao and Taiwan are excluded because of a lack of data) as samples for the empirical analysis. Because of the large amount of information included in the panel data, the possibility of collinearity between variables is reduced and the degree of freedom can be increased to improve the effectiveness of the estimation (As one of the market incentive environmental regulation tools, the sewage charge stopped being enforced in 2018. This paper uses data from 2006 to 2017 based on their continuity and availability.)

4.1. Indicator Selection and Data Sources

4.1.1. Explained Variables

Enterprise green technology innovation (patents) is an explained variable measured using the number of green technology patent applications. According to the international patent green list published by the State Intellectual Property Organization and the corresponding patent classification code in the list, the number of green utility model patent applications and green invention patent applications in different provinces and years are obtained according to the application region, IPC patent code and application time, and the total number of green patent applications is obtained as the sum of the two. At the same time, to eliminate the right-deviated distribution of green patent application data, referring to the practices of Xu Jia, Cui Jingbo [22], Wang Xin and Wang Ying [23], we add 1 to the number of green patent applications and take the logarithm to obtain green technology innovation data (patents).

4.1.2. Core Explanatory Variables

The core explanatory variables in this paper are environmental regulation, including command-and-control environmental regulation (ER₁), market-incentive environmental regulation (ER₂) and voluntary participatory environmental regulation (ER₃).

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Measurement of the command-and-control environmental regulation index

Command-controlled environmental regulation is mainly manifested in the end pollution treatment or equipment renewal and transformation carried out by enterprises in accordance with laws and regulations to meet the requirements of pollutant discharge or technical standards. Therefore, to calculate command-and-control environmental regulation, many scholars use a single index method, such as the proportion of industrial pollution control investments to the total industrial output value [24], the ratio of industrial waste gas emissions to the total industrial output value of provinces and cities [25] or the implementation qualification rate of the “three simultaneities” system [26]. Considering that the most direct and important embodiment of command-and-control environmental regulations is the reduction in pollutant emissions from industrial enterprises in various regions and, based on data availability, referring to the practices of Dong Jingrong [27], Tian Hongbin [28], and ye Qin [29], this paper comprehensively calculates the command-and-control environmental regulation based on the total discharge of chemical oxygen demand (COD), SO2 and industrial solid waste in industrial wastewater in various regions. (Industrial enterprise pollutants are measured using emissions data on SO₂ and COD in wastewater and waste gas because these are the two main sources of pollutants and their index data are relatively complete, allowing for the continuity of the data.)

The entropy method is a means of objective assignment that determines the index weight according to the information provided by the observed values of each index, which is more objective and fairer than the index weight given by the subjective assignment method.

First, the extreme value method is used to standardize the above three indicators because they are negative indicators; that is, the smaller the emissions are, the greater is the intensity of environmental regulation. The calculation formula is

R^s_i,j = [max (R_j) − R_i,j]/[max (R_j) − min (R_j)]

(1)

where R_i,j is the initial value of a single index of class J pollutants in province i; min (R_j) and max (R_j) are the minimum and maximum values of a single index of class j pollutants, respectively; R^s_i,j are the standardized values of class j single pollutants in province i after dimensionless standardization treatment.

Second, the adjustment coefficient of each single pollutant index is calculated as follows:

$${\mathrm{W}}_{\mathrm{j}}={\mathrm{R}}_{\mathrm{i},\mathrm{j}}/{\overline{\mathrm{R}}}_{\mathrm{i}}$$

(2)

where ${\overline{\mathrm{R}}}_{\mathrm{i},\mathrm{j}}$ is the provincial average level of the unit output value of class j pollutants in province i in the sample.

Finally, the comprehensive index ER_i of environmental regulation in each region is calculated:

$${\mathrm{ER}}_{1\mathrm{i}}=\frac{1}{3}{\sum }_{\mathrm{j}=1}^3{\mathrm{W}}_{\mathrm{j}}{{\mathrm{R}}^{\mathrm{s}}}_{\mathrm{i},\mathrm{j}}$$

(3)

The greater the value of ER₁ is, the stricter and stronger the command-and-control environmental regulation. (Stata 15.0 software was used for the entropy calculation and ER₁ was forward processed during the analysis.)

(2)

Measurement of market-incentive environmental regulation index

Market-incentive environmental regulations mainly affect the profit of or cost to enterprises to promote energy savings and emissions reductions, protect the environment and thus improve the overall environmental quality of society. Market-incentive environmental regulations mainly include environmental tax and fee systems, emissions trading and subsidies. Because China’s current market economy system needs to be perfected and the emissions tax has only been implemented for a short time, its effectiveness is not yet evident and data on subsidies and emissions trading are difficult to obtain. In contrast, although sewage charges are a single index, the policy was implemented earlier and has been continuously in place; furthermore, the policy is relatively stable, its coverage is wide and it can effectively measure enterprises’ cost of pollution control. Sewage charges are the main method of market-incentive environmental regulations in China at present and the relevant data are easy to obtain. Therefore, referring to the practices of Cai Wugan and Fan Dan [30,31], this paper takes the logarithm of pollutant discharge fee income in each region as the measurement variable of market-incentive environmental regulations.

(3)

Measurement of the voluntary participation environmental regulation index

Due to the wide coverage of voluntary participatory environmental regulations involving the government, enterprises, nongovernmental organizations, the public and other levels, it is impossible to fully cover all participants with a single index. At the same time, it is difficult to find alternative indicators to reflect the effect of this means of environmental regulation. Some scholars measure voluntary participatory environmental regulations using the number of environmental news reports by provincial party committee organizations in various regions [32,33], while others use the amount of correspondence and number of official visits to various provinces [34], the size of mass petitions [35] or environmental telephone complaint data from the Ministry of Environmental Protection [36]. Referring to the practice of Liang Jinrui [37] and based on data availability and the continuity of data periods, this paper uses the logarithm of the number of NPC proposals on environmental protection and CPPCC proposals on environmental protection and uses it as the measurement index of voluntary participation in environmental regulations.

4.1.3. Control Variables

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Degree of openness to the outside world (FDI)

Currently, most countries worldwide have an open policy toward foreign trade. While bringing advanced technology, production methods and management experience to the host country, the open trade policy also prompts the transfer of some highly polluting industries to countries or regions with relatively weak environmental regulations, thus causing environmental deterioration of the host country, that is, the “pollution refuge effect”. Therefore, the degree of a country’s openness to the outside world has an impact on its environmental regulation policy and green technology innovation. This paper uses the degree of openness as one of the control variables. Referring to the practices of Shen Guobing and Zhang Xin [38], this paper measures the degree of opening to the outside world using the ratio of foreign direct investments utilized in each region to GDP. Because the utilization of foreign direct investments (FDI) in each region is indicated in US dollars, this paper first converts the actual utilization of FDI in each region into RMB according to the average exchange rate between US dollars and RMB for each year, deflates the GDP data using 2000 as the base period and finally obtains the index of openness to the outside world.

(2)

Enterprise scale (SIZE)

Different enterprise sizes result in their innovation resources and thus their innovation motivation to differ. Size is expressed as the ratio of the main business income of industrial enterprises larger than a designated size in each region to the number of enterprises.

(3)

Regional education level (JY)

The higher the average education level of residents in a region is, the higher the overall quality of the residents, with corresponding increases in their environmental awareness and attention. In these areas, voluntary environmental regulations can also result in better development [39] and have an impact on green technology innovation. Based on this correlation, the regional education level is measured as the number of college students per 100,000 residents and is treated logarithmically.

(4)

Industrial structure (indshare)

The industrial structure of a region affects the local environmental quality, thus affecting the environmental regulation policy. The secondary industry is generally considered the industry that mainly produces pollutants. This paper measures the industrial structure of each region as the proportion of the output value of the secondary industry to the GDP of each region.

(5)

Market mechanism: ownership structure (ownership)

The ownership structure, that is, the market mechanism, is measured as the proportion of the number of state-owned and state-controlled industrial enterprises larger than a designated size to the total number of industrial enterprises larger than the designated size.

The selection, description and data sources of specific variables are shown in

Table 1. Description of variables.

Variable Name	Type	Variable Symbol	Variable Interpretation	Data Source
Green Technology Innovation	Explained variable	Patent	Number of green technology patent applications	According to the green list of international patent classifications, this variable is obtained after searching and sorting in the State Intellectual Property Office
Command-and-control environmental regulation	Explanatory variable	ER1	Comprehensive values of total chemical oxygen demand (COD), SO2 and industrial solid waste in industrial wastewater in each region	China Environmental Statistics Yearbook
Market-incentive environmental regulation	Explanatory variable	ER2	Logarithm of sewage charge income in each region	China Environmental Yearbook
Voluntary participatory environmental regulation	Explanatory variable	ER3	Logarithm of the sum of the number of NPC proposals on environmental protection and the number of CPPCC proposals on environmental protection	China Environmental Yearbook
Degree of openness to the outside world	Control variable	FDI	Ratio of actual utilization of foreign direct investment to GDP in different regions	China Statistical Yearbook
Enterprise scale	Control variable	SIZE	Ratio of main business income of industrial enterprises above a designated size to the number of enterprises in each region	China Statistical Yearbook
Regional education level	Control variable	JY	Logarithm of the number of college students per 100,000 people	China Statistical Yearbook
Industrial structure	Control variable	Indshare	Industrial structure of each region is measured as the proportion of the output value of the secondary industry to the GDP of each region	China Statistical Yearbook
Market mechanism	Control variable	Ownership	Proportion of the number of state-owned and state-controlled industrial enterprises larger than a designated size to the total number of industrial enterprises larger than the designated size	China Statistical Yearbook

Source: authors’ collation.

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4.2. Setting of the Econometric Model

Considering that green technology innovation is a gradual and cumulative process, it is easily affected by the previous technical level; thus, the first-order lag term of green technology innovation is introduced into the model. Moreover, since it is unclear whether the impact of environmental regulations on green technology innovation is linear, the quadratic term of environmental regulations is introduced into the model. To measure the impact of environmental regulations on green technology innovation, we construct the following dynamic panel model.

Patent_it = a + b₁Patenti_t−1 + b₂ER_1it + b₃(ER_1it)² + cX_it + ε_it

(4)

Patent_it = a + b₁Patent_t−1 + b₂ER_2it + b₃(ER_2it)² + cX_it + ε_it

(5)

Patent_it = a + b₁Patenti_t−1 + b₂ER_3it + b₃(ER_3it)² + cX_it + ε_it

(6)

where i represents each province; t represents time (2006–2017); a is the intercept term; b and c are coefficients to be estimated; ε is the random disturbance term; Patent is green technology innovation; lnPatent_it−1 is the first-order lag term of green technology innovation; X represents each control variable; ER₁, ER₂ and ER₃ are command-and-control environmental regulations, market-incentive environmental regulations and voluntary participation environmental regulations, respectively.

5. Empirical Test and Results Analysis

5.1. Descriptive Statistics of Key Variables

In this paper, Stata 15.0 is used for data analysis, and the descriptive statistical results of the variables are shown in

Table 2. Descriptive statistics of the variables.

Variable Name	Observation Value	Average	Standard Deviation	Minimum Value	Maximum Value
Patent	360	6.70478	2.023262	0	10.68606
ER1	360	0.7636792	0.1517444	0.3198205	0.9957773
ER2	360	10.6847	0.9521876	7.495153	12.53128
ER3	360	5.105651	1.020232	2.079442	7.980195
FDI	360	0.0236703	0.0183709	0.000386	0.0819825
JY	360	7.71733	0.3589294	6.806829	8.838842
indshare	360	0.4637606	0.0812898	0.19014	0.5904543
SIZE	360	2.547616	1.196853	0.6255286	6.413507
Ownership	360	0.1110625	0.0768908	0.0113417	0.4016807

. Table 2 shows that the minimum value of green technology innovation is 0 and the maximum value is 10.68606. This is because the green technology innovation in this paper uses the green patent application amount in each region as the measurement index. When looking up the data, it is found that the green patent application amount in Inner Mongolia is 0; therefore, before using the logarithm of green technology innovation, we first increase the number of green patent applications in each region by 1. After taking the logarithm, the number of green technology innovations in Inner Mongolia is 0. Thus, substantial differences are seen among the provinces in the indicators of green technology innovation, which may be due to the provinces’ different levels of regional development. In addition, there are also great differences in the intensity of the three types of environmental regulations among provinces or the intensity is related to the strength of local governments’ implementations of environmental regulation policies and the degree of public participation.

5.2. Stability Test

In this paper, the ADF–Fisher test is used to test the unit root of each variable to ensure the validity of the estimation results and to avoid the “pseudoregression” problem caused by nonstationary data. The test results are shown in

Table 3. Data stationarity test.

Variable.	ADF–Fisher Test P	Conclusion
Patent	73.9083 *	Stable
ER1	259.8908 ***	Stable
ER2	164.2208 ***	Stable
ER3	223.0930 ***	Stable
FDI	231.1975 ***	Stable
JY	160.9840 ***	Stable
SIZE	116.4967 ***	Stable
indshare	101.9616 ***	Stable
Ownership	234.9385 ***	Stable

Note: * and *** represent significance at 10%, 5% and 1%, respectively.

. The results indicate that all variables reject the original hypothesis of the unit root; the panel data are thus stationary.

5.3. Analysis and Discussion of Results

The Impact of Environmental Regulations on Enterprise Green Technology Innovation across Countries

This section presents a regression estimation of the panel data of 30 provinces (cities, autonomous regions and municipalities directly under the central government) in China on the impact of command-and-control environmental regulations, market-incentive environmental regulations and voluntary participation in environmental regulations on green technology innovation. The test results are shown in

Table 4. Regression results of the three types of environmental regulations on green technology innovation.

Variable	Model 4	Model 5	Model 6
Patentit−1	0.8781029 *** (23.54)	0.8938802 *** (25.56)	0.8926136 *** (26.77)
ER	2.746057 *** (3.27)	−1.822148 *** (−2.83)	−1.1009159 ** (−2.80)
ER2	−1.757539 *** (−3.04)	0.0894047 *** (2.73)	0.082978 ** (2.59)
FDI	−6.325532 * (−1.79)	−10.29888 *** (−3.02)	−6.312114 ** (−2.29)
JY	1.07784 *** (3.05)	1.145187 ** (2.38)	0.5400351 * (1.94)
indshare	−2.080832 *** (−3.63)	−3.108446 *** (−5.17)	−2.056861 *** (−4.10)
SIZE	0.0570897 * (1.91)	0.0569903 * (1.92)	0.0582159 * (1.83)
Ownership	−6.010745 *** (−3.92)	−3.871742 ** (−2.05)	−5.681422 *** (−5.51)
C	−0.7352297 (−0.23)	3.604933 (0.87)	−1.131343 (−0.50)
Curve type	“Inverted U”	“U−shaped”	“U−shaped”
Inflection point	0.78	10.189	6.633
AR (1)	0.0002	0.0002	0.0002
AR (2)	0.1562	0.3770	0.3173
Sargan	0.7869	0.8712	0.6827
Wald	6220.96	37,078.81	19,123.46
p-value	0.0000	0.0000	0.0000
Sample size	360	360	360

Note: * p < 0.1; ** p < 0.05; *** p < 0.01. Z values were obtained using the robust standard deviation; AR (1), AR (2) the Sargan test gives the p-value corresponding to the statistic.

.

Due to the lagging and cumulative effects of technological innovation, a dynamic panel model is constructed by introducing the first-order lagged term of green technological innovation as an explanatory variable in the model, thereby potentially endogenizing the lagged term by correlating it with the disturbance term. In addition, the factors affecting green technology innovation are intricate and complex and the problem of omitted variables in the model’s construction may lead to endogeneity problems. Once the endogeneity problem arises, estimation using the OLS method leads to biases in the results, so a systematic GMM approach is used for the estimation. Systematic GMM is a combination of differential GMM and horizontal GMM, combining differential and horizontal equations as a system of equations for GMM estimation [40]. To overcome the endogeneity of the explanatory variables and the heteroskedasticity of the residuals, a two-step approach is used for the estimation. (Systematic GMM includes two-step systematic GMM estimation and one-step systematic GMM estimation. In the case of a limited sample size, the one-step systematic GMM estimation is susceptible to heteroskedasticity.)

The last five rows of Table 4 report the results of the sequence correlation test and the overidentification test. The results show that AR (1) rejects the original hypothesis and AR (2) accepts the original hypothesis that the disturbance term has no autocorrelation, indicating that the error term of the original model has no sequence correlation and the model setting is reasonable. The corresponding p-values of the Sargan test are all close to 1, which shows that the selected instrumental variables are valid and can be further estimated using the GMM system. The Wald test results show that the p-values are all 0, indicating that the overall model is significant.

From the results in Table 4, it can be seen that the lag items in the previous period of green technology innovation are significantly positively correlated with the current indicators, which further verifies that green technology innovation is a continuous accumulation and dynamic adjustment process and shows the importance of maintaining policy consistency and coherence.

From the regression results of Model 4, we can see that the primary coefficient of command-and-control environmental regulations on green technology innovation is positive, the quadratic coefficient is negative and both coefficients surpass the 0.1% significance level, which shows that the impact effect of command-and-control environmental regulations on green technology innovation has an inverted “U-shape” with an inflection point of 0.78. On the left side of the inflection point, command-and-control environmental regulations play a major role in the “innovation compensation” effect of green technology innovation. With the increasing strictness of command-and-control environmental regulations, these regulations begin to have a “compliance cost” effect, which inhibits green technology innovation.

The regression results of Model 5 show that the primary coefficient of market-incentive environmental regulations on green technology innovation is negative, the secondary coefficient is positive and both coefficients surpass the 0.1% significance level, which shows that as market-incentive environmental regulations are enhanced, green technology innovation presents a “U-shaped” change trend that first declines and then rises. The table also shows that the inflection point value is 10.189. On the left side of the inflection point, the “compliance cost” effect of market-incentive environmental regulations plays a major role. Once the inflection point is exceeded, market-incentive environmental regulations begin to play a positive role in promoting green technology innovation, and the “innovation compensation” effect plays a major role at this time.

The regression results of Model 6 show that the primary coefficient of voluntary environmental regulations on green technology innovation is negative, the secondary coefficient is positive and both coefficients surpass the 0.1% significance level, which shows that voluntary environmental regulations on green technology innovation also present a “U-shaped” change trend that first declines and then rises. The inflection point value is 6.633. Before the inflection point value is reached, voluntary participatory environmental regulations have a restraining effect on green technology innovation and the “compliance cost” effect occurs. As voluntary participatory environmental regulations continue to increase, the “innovation compensation” effect begins to work after the inflection point value is crossed and, at this time, voluntary participatory environmental regulations play a positive role in promoting green technology innovation.

Overall, the comparison of the three environmental regulation methods reveals that, based on the influence coefficient in the table, the influence of command-and-control environmental regulations on enterprise green technology innovation is much higher than those of both market-incentive environmental regulations and voluntary participation in environmental regulations.

From the perspective of control variables, for the three types of environmental regulations, the coefficient symbols of the control variables are relatively consistent and basically conform to the expected results of the theoretical analysis. ① Foreign direct investment (FDI) has a significant negative effect on green technology innovation. Generally, foreign investments can bring an advanced technological level to a country. Absorbing and introducing foreign advanced technology and experience is conducive to promoting domestic innovation activities. However, due to the “pollution paradise” effect in a market economy, some foreign high-pollution industries enter China and FDI is concentrated in the medium- and low-end industries with less advanced technology and an export orientation; alternatively, due to the strict confidentiality of high-end industrial technology and the export control of high-tech products, FDI has a negative inhibitory effect on enterprise green technology innovations. ② Education (JY) plays a positive role in promoting green technology innovation. The role of education in innovation is self-evident. The more educational resources a country invests in, the more conducive the action to cultivating talent that can promote green technology innovation, thus ensuring a source and motivation toward innovation and increasing the possibility of successful green technology innovation for enterprises. ③ Industrial structure (indshare) has a significant negative inhibitory effect on green technology innovation, indicating that the larger the proportion of industry in the industrial structure is, the more likely its production mode is to remain entrenched in path dependence on resources and the environment, thus hindering green technology innovation. ④ Corporate scale (SIZE) plays a significant positive role in promoting green technology innovation. Generally, the larger the enterprise is, the more conducive it is to implementing green technology innovation, because green technology innovation requires considerable capital and personnel investments and has a long cycle and high risk. Strong enterprises have more capital strength and risk mitigation aptitudes, so they are more likely to implement green technology innovation. ⑤ The market mechanism (ownership) plays a very significant negative role in inhibiting green technology innovation. This finding shows that the proportion of state-owned enterprises in industrial enterprises is too high, which is not conducive to green technology innovation activities. This situation may exist because China is currently in the crucial stage of state-owned enterprise reform and many state-owned enterprises have not yet formed a management system and operating mechanism that can fully meet the requirements of the market economy, thus hindering their green technology innovation activities.

6. Research Conclusions and Policy Recommendations

6.1. Research Conclusions

Based on the regression equation of the impact of environmental regulations on green technology innovation, this paper uses the two-step system GMM method to analyze the panel data of industrial enterprises above a designated size in 30 provinces, autonomous regions and municipalities in China from 2006 to 2017 and compares the impact of command-and-control environmental regulations, market-incentive environmental regulations and voluntary participatory environmental regulations on green technology innovation. The empirical results show that: (1) An inverted “U-shaped” effect of command-and-control environmental regulations on green technology innovation occurs; that is, in the initial stage, enterprises increase their investments in green innovation to meet the requirements of environmental regulations and as the intensity of environmental regulations increases, the compliance cost effect on green technology innovation appears. This effect then increases the costs for enterprises and diminishes the investment funds available for green innovation, thus inhibiting green technology innovation. However, the “U-shaped” effect of market incentives and voluntary participation in environmental regulations on green technology innovation first inhibits and then promotes innovation.

Market incentives and voluntary participation in environmental regulations play a “U” role in green technology innovation, that is, inhibition before promotion. When market-incentive environmental regulations and voluntary participation in environmental regulations cross the critical value, they promote green technology innovation. (2) When comparing the three environmental regulation types, the effect of command-and-control environmental regulations is more remarkable, perhaps because it has been in place for the longest period and has the most extensive application in China. (3) The effect of environmental regulations on green technology innovation is also influenced by the degree of openness to the outside world (FDI), enterprise scale (SIZE), regional education level (JY), industrial structure (indshare), market mechanism (ownership) and other control variables.

6.2. Policy Recommendations

6.2.1. Coordinate and Optimize Various Environmental Regulation Policies

From the above analysis, it can be seen that different environmental regulation tools have significant differences in their impact on enterprise green technology innovation due to their different theoretical bases and participants. Therefore, when using environmental regulation tools to promote green technology innovation, policy makers should adopt targeted policy tools according to different regulation objects and objectives and reasonably allocate and optimize the combination of various regulation tools, cooperate with other systems, combine the technology and economic development level of different regions and finally promote the construction of an ecological civilization through the development of enterprise green technology innovation. Generally, command-and-control environmental regulations are the most important environmental regulation tool implemented in China at present. These environmental regulation tools have played an active role in pollution control and environmental protection but their specific implementation methods still need to be adjusted and reformed. For market-incentive environmental regulations, having drawn lessons from the advanced experience of Western developed countries and having combined this information with the current practice in China, this paper advocates for forging a unique development path for China, such as vigorously promoting the environmental tax system and further perfecting the emissions trading market. Since the 1990s, China has introduced voluntary participatory environmental regulations. As a supplement to traditional environmental regulations, voluntary participatory environmental regulations have strong flexibility and autonomy. In contrast to the regulations of the past, China’s voluntary participatory environmental regulations have made great progress in their concepts and forms of implementation at this stage. From the above analysis, it can be seen that voluntary participatory environmental regulations have a U-shaped impact on green technology innovation and the greater the intensity of voluntary participatory environmental regulation, the greater its positive impact on green technology innovation. Therefore, this paper argues that the focus of China’s environmental regulation policy in the future should be to vigorously develop voluntary participatory environmental regulations and enhance the intensity of this type of regulation by, for example, continuously promoting environmental information disclosure, strengthening public participation and perfecting the mechanism of public participation.

6.2.2. Improve Relevant Supporting Policies

The green technology innovation effect of environmental regulations needs to cooperate with other elements, such as foreign direct investment (FDI), education (JY), industrial structure (indshare), enterprise scale (SIZE) and market mechanism (ownership). Developed countries have accumulated experience in balancing the protection of the ecological environment and economic development as well as in promoting the green technology innovation of enterprises through environmental regulations. Introducing foreign capital and technology can better promote the green technology innovation ability of Chinese enterprises. However, from the above analysis, it can be seen that during the sample period, FDI had a significant negative inhibitory effect on green technology innovation. Therefore, when foreign technology and management experience are introduced, the government should consider the current state of Chinese enterprises, selectively and cautiously formulate appropriate investment policies through policy support and tax incentives and optimize the structure of foreign investments. Furthermore, the government should increase investments in educational resources, improve the quantity and quality of human resources and provide solid human guarantees for the green technology innovation of enterprises, in addition to actively adjusting the industrial structure and promoting the green technology innovation of enterprises by developing green and clean industries.

The above analysis shows that China’s current ownership structure has a negative inhibitory effect on green technology innovation. At present, the proportion of industrial enterprises in China is too high. Although state-owned enterprises have a natural advantage in green technology innovation, many have not formed a management system and operation mechanism that can fully meet the requirements of the market economy and their incentive mechanism is not fully developed, resulting in a lack of innovative spirit that inhibits their green technology innovation activities. In addition, enterprise scale plays a positive role in promoting enterprise green technology innovation. Generally, the larger the enterprise scale, the more funds and R&D personnel can be invested, and the higher the risk mitigation aptitude, the more conducive it is for enterprises to implement green technology innovation. On the other hand, the promotion of green technology innovation still requires the participation of small and medium-sized enterprises with flexible mechanisms and high innovation. Therefore, government agencies should create a good business environment for small and medium-sized enterprises through laws and regulations and ensure that these enterprises can compete with large enterprises, especially large state-owned enterprises, on a level playing field. At the same time, through fiscal, tax, financial and other means, it is important to further guide small and medium-sized enterprises to innovate in technology and products and encourage them to establish industrial clusters and develop alongside large enterprises.

6.3. Limitations and Prospects

The relationship between environmental regulations and green technology innovation is a relatively complex and meaningful topic that has very broad research prospects. This paper, to a certain extent, attempts to explore this topic; however, due to the authors’ research ability and the research space, this paper has various limitations and deficiencies that need to be explored and remedied in future studies.

The first is the choice of alternative indicators for environmental regulations. There has always been controversy in academic circles about the index used in the calculation of environmental rules. In this paper, environmental regulations are divided into three environmental regulation tools: command-and-control, market incentives and voluntary participation. The entropy method is used to calculate a comprehensive index as the command-and-control environmental regulation index. Based on data availability, when measuring the market-incentive environmental regulation index, we use sewage charges as an alternative index. For voluntary participation in environmental regulations, the number of proposals on the environmental protection by the National People’s Congress and the number of proposals on the environmental protection by the CPPCC are used as alternative indicators. Although it is reasonable to select these as alternative indicators, identifying more scientific and reasonable alternative indicators to measure the three regulatory tools is a very important direction for exploring the impact of environmental regulations on green technology innovation in the future.

Second, the time span of the research samples presents some limitations. On 1 January 2018, the sewage charge system was officially replaced with an environmental protection tax. Because the environmental protection tax has been implemented for such a short time and its efficacy is not yet clear, this paper still uses the indicator of sewage charges when measuring market-incentive environmental regulations. Based on the continuity and availability of the data, the selection sample interval of this paper is 2006–2017, which is a relatively short research period. In the future, we can consider extending the research time interval to study the impact of environmental regulations on green technology innovation over a longer period.

Third, the research space needs to be further refined. In this paper, environmental regulation is divided into command-and-control environmental regulation, market-incentive environmental regulation and voluntary participation environmental regulation. When measuring green technology innovation, we use the comprehensive index of green technology patents, which is widely used in academia. However, after consulting the literature on green technology innovation, we find that the concept of green technology innovation can be further refined by, for example, dividing it into green product innovation and green process innovation. Therefore, this finding raises a future research question: how will different types of environmental regulation tools affect green product innovation and green technology innovation? More detailed studies on these topics should be conducted in the future.