Research on the Effect of the New Environmental Protection Law on the Market Competitiveness of China’s Heavily Polluting Enterprises

Abstract

Based on a difference-in-differences model, this study examines the effect of environmental regulation on the market competitiveness of heavily polluting enterprises, their mechanisms, and the space for effective implementation. Which all listed heavily polluting enterprises between 2010 and 2019 are included as the experimental group, and all other firms in the same industries listed on the Chinese stock market as the control group. The results indicate that environmental regulations have significantly increased the market competitiveness of heavily polluting enterprises in China. Furthermore, China’s New Environmental Protection Law (NEPL) has improved the market competitiveness of heavily polluting enterprises through strategic, flexible mitigation effects. Finally, the NEPL in regions with eastern or non-state enterprises has a significant impact on market competitiveness. The government should further improve laws and regulations for environmental protection, increase environmental regulations, and apply policies based on the differences in heavily polluting enterprises.

1. Introduction

Ecological and environmental crises have become crucial issues limiting global economic development. Environmental issues arising from economic development are of increasing concern to both governments and society. As the green development philosophy was the basic strategy to process the relationship between man and nature in the report of the 20th National Congress of the Communist Party of China (CPC), the construction of an ecological civilization has become an important strategy for Chinese development. Environmental conservation is becoming increasingly prominent in China owing to the fast economic and social development. The Chinese government enacted the Environmental Protection Law of the People’s Republic of China (the Old Environmental Protection Law) in 1989. With the increase in the level of environmental regulation, the Chinese government revised the law and named it the New Environmental Protection Law (NEPL) of the People’s Republic of China. China officially enacted the law in 2015. The NEPL has three new important features compared to the Old Environmental Protection Law. First, the NEPL has significant penalties, which directly increase the marginal cost of regulated enterprises. Second, it stimulates the environmental protection behavior of enterprises. On the supply side, the government provides more financial, tax, and price concessions to enterprises that overachieve pollution control and emission reduction. On the demand side, the government incentivizes consumers to use environmentally friendly products, which considerably stimulates enterprises to conduct environmental protection investment, technology research, and development. Finally, the NEPL emphasizes information disclosure and encourages public participation. In summary, the implementation of the NEPL is of significant importance to the sustainable development of Chinese enterprises. It is the strictest environmental protection law in history, has increased the cost of emissions for enterprises, and places pressure on heavily polluting enterprises to protect their environment.

Enterprises are important market players in achieving “win-win” economic and environmental development, and they are the backbone of China’s “double carbon” goal. Some scholars believe the NEPL has increased the cost of pollution control for companies. The costs crowd out funds for process innovation, low-carbon production and operations. Therefore, under the concept of “green hills” and “golden mountains”, can environmental regulations “push back” the competitiveness of heavy polluters? The answer to this question is the key to measuring the economic effects of policies, and the literature provides inconclusive empirical evidence [1,2]. Theoretically, the NEPL can “push” firms to actively fulfill their environmental obligations through pressure effects, such as the incentive effect of the NEPL through strict environmental regulations, which effects firms to increase their technological investment and actively participate in environmental management [3]. However, some studies argue that excessive regulatory pressure can increase the marginal costs of firms, crowd out investments in innovation, and subsequently reduce their competitiveness [4,5]. Among many enterprises, heavy polluters are the “top priority”, and they are the focus of government environmental legislation owing to their high pollution emissions and relatively backward production capacity. Following the implementation of the NEPL, such enterprises have been urged to undertake remediation measures and other means to enforce strategic adjustments and technological innovation as part of their transformation and upgrading process. This includes the utilization of existing resources and capabilities, as well as the introduction of green methodologies and processes. In addition to innovating and implementing cleaner projects, these steps serve to enhance the competitiveness of these enterprises in the market.

In the current era of predominantly stock market, the leading effect of each industry is evident; therefore, many companies want to win market power and improve their market competitiveness through research and development (R&D) investment, strategic transformation, and organizational mergers and acquisitions. Whether heavy polluters have a greater say in the product market and gain higher market competitiveness is crucial for business development [6]. Existing literature on the relationship between the implementation of the NEPL and the market competitiveness of enterprises is fragmented, focusing on the qualitative study of how the NEPL has increased the market share of retained enterprises by raising the entry barrier for new enterprises, the qualitative study of how enterprises have expanded their competitiveness in the name of the NEPL, and the asymmetrical nature of the NEPL policy of the NEPL due to its selective features. Three aspects of the NEPL, such as the intensity of regulation, were discussed, and no consensus was reached on the findings. Therefore, whether the NEPL can “force” heavy polluters to improve their market competitiveness should be considered and verified.

This study treats the commencement of the NEPL as an event, selects a list of heavily polluting enterprises in the Chinese stock market from 2010 to 2019 as the sample, and empirically tests the effect of the NEPL on competitiveness of heavily polluting enterprises using a difference-in-differences (DID) framework. The mechanisms through which NEPL affects market competitiveness were also investigated. Additionally, we analyze the heterogeneity of the relationship between the NEPL and the market competitiveness of heavily polluting enterprises. The results demonstrate that NEPL significantly increased the market competitiveness of heavily polluting enterprises in China, a phenomenon that is more significant in eastern China among non-state enterprises. Further investigation found that the NEPL increases the market competitiveness of heavily polluting enterprises by increasing their strategic flexibility. This study provides suggestions for the government in terms of improving the level of environmental regulation and for enterprises to conduct technological innovation and strategic alignment on their own.

2. Literature Review

2.1. Effect of the NEPL on Heavy Polluting Enterprises

Theoretically, the NEPL “forces” firms to actively participate in environmental management through pressure effects [3,7] however, excessive regulatory pressure may lead to negative responses [8]. Existing studies have established that the NEPL achieves environmental dividends, but there is persistent disagreement as to whether it achieves both environmental and economic dividends. The first view is the “suppression view” of the NEPL, which argues that although the NEPL is effective in curbing pollution emissions of firms, it inevitably increase firms’ marginal costs [9,10] and reduces their competitiveness [11]. Jia and Ye focused on firms’ productivity and argued that the NEPL is not conducive to the development of firms. They posited that the implementation of the NEPL is unfavorable to the development of enterprises and will lead them to change their existing production and operation behaviors and “crowd out” their productive investments in pollution control and environmental improvement [12,13]. In addition, the NEPL forces firms to engage in rent-seeking behavior, which slows down productivity growth in the short term as the marginal cost of production increases [14,15]. The increased cost resulting from the NEPL will affect firms’ innovation and investment behavior [16], which will also weaken their competitiveness [17]. The second is the “facilitation view” of the NEPL, the most representative of which is the Porter hypothesis, where Porter concluded from various case studies that the NEPL has an incentive effect on innovation, stimulating firms to innovate processes and products [18]. Hojnik and Ruzzier confirmed that the NEPL is an important driver of innovation for firms compared to other factors [19] and that environmental regulation indirectly affects firm development through technological innovation. Starting from the policy itself, the government’s strengthening of regulations and efficiency, and the provision of sound market mechanisms and subsidies for enterprises are conducive to guiding them to conduct green technological innovation, which positively affects their own development [20].

Specifically, at the microeconomic level, it mainly involves the impact of the NEPL on enterprises’ investment behavior, technological innovation, environmental governance behavior, and enterprise efficiency and performance, with investment behavior involving R&D, human capital, and export investments. The NEPL gave firms domestic and foreign capital and encouraged them to invest in environmental protection [21,22,23], which improved firm productivity. Zhang found that the implementation of the NEPL stimulated heavily polluting firms to undertake technological innovation, resulting in significant improvement in their environmental performance [24]. Most studies have concluded that the NEPL has positively affected green innovation; however, the findings are not entirely consistent. This study demonstrates that the Porter hypothesis holds true for listed companies in China, and that the law has promoted the improvement of information disclosure by heavy polluters, which has energized corporate innovation. Similarly, Liu demonstrated that heavy polluters in China are more likely to apply for more environmental patents owing to environmental regulations. However, a further analysis shows that state-owned enterprises (SOEs) are significantly influenced by policies [25]. Jing and Zhang addressed the environmental management investment activities conducted by heavily polluting enterprises, and they concluded that heavy polluting enterprises can improve their product competitiveness through technological innovation by innovating in areas such as clean production technologies [26]. Yu demonstrated that the incentive effect of the NEPL on technological innovation is significant in the eastern region because of regional variability in its implementation [27]. Additionally, a strict environmental regime increases the cost of compliance for heavily polluting firms, which can crowd out resources for firms to undertake technological innovation. Zhang assessed the adverse effects of the NEPL on the technological innovation activities firms and showed that environmental regulation policies have a dampening role on the enterprise innovation activities, but granting government subsidies weakens this adverse effect [28]. Yu and Li included the level of technological innovation measured by R&D investment in their empirical model; they found that stricter environmental regulations constrained the level of technological innovation of firms [29]. In summary, existing studies already explored sufficient research on the effect of the NEPL on firms’ innovation, and most of the studies confirm that reasonable environmental regulation policies can reduce costs and increase efficiency, lowering the marginal costs of firms while increasing their innovation levels.

Regarding the impact of the NEPL on the environmental governance behavior of enterprises, Cui and Jiang demonstrated that after the implementation of the policy, heavily polluting enterprises face greater pressure for environmental governance [3]. These firms do not show positive environmental investment behaviors owing to financial constraints, but instead scale down production to achieve environmental compliance. Liao established that heavy polluters adopt various positive environmental management behaviors to scale down the production of highly polluting projects and innovate process technologies to eliminate backward production capacity at source in the face of strict regulatory policies [30]. Regarding the impact of the NEPL on firm productivity, Han found that binding pollution controls increased the overall productivity of polluting firms [31]. In contrast, Cai and Ye argued that the NEPL impedes the improvement of total factor productivity at the firm level and is ineffective in reducing environmental pollution and promoting firm survival and development [32].

2.2. Effect of the NEPL on the Competitiveness of Heavy Polluting Enterprises

Part of the study points out that NEPL negatively affect a firm’s competitiveness. Meng examined the effect of the NEPL on firm stock market performance from the perspective of environmental information disclosure; it was found that the policy increases the production costs of a firm and subsequently reduces firm competitiveness [33]. Gray and Shadbegian studied the production of heavy polluting firms; they found that firms with higher regulatory costs are significantly lower than those with lower regulation costs [17]. The same conclusion was reached by other scholars, who found that strict legislative policies forced enterprises to transform and upgrade, spend more money on pollution control, or introduce environmentally friendly equipment equipment, and that the “squeeze-out effect” reduced working capital, lowered productivity, and lost competitive advantage [34]. From a cost perspective, some scholars have concluded that the NEPL increases marginal costs, which adversely affects the competitiveness of firms [35,36]. Some studies have explored the mechanisms through which the NEPL influences firm competitiveness indirectly. One such mechanism is that policies drive technological innovation, which in turn indirectly bolsters a firm’s market advantage. Porter has made outstanding contributions to the literature. Based on these findings, the innovation incentive effect can offset the cost of regulations, and thus improve firm competitiveness [18]. Lanoie proposed that the NEPL facilitates both technological and cost-cutting innovations in the environment [37]. Similar conclusions were obtained by Chinese scholars using different research methods [38,39]. Huang and Liu found that the NEPL imposes direct costs on some firms but also stimulate innovation, which can partially or fully offset the costs of such expenses and subsequently enhance the market competitiveness of firms [40]. Li and Yang studied data on thermal power generation firms in China and found that NEPL promotes technological innovation in such firms and subsequently has a positive impact on their competitiveness [35].

Through a review of existing research, the literature has been well explored around the microeconomic effects of the NEPL, but conclusions on the effectiveness of the policy are widely divergent. This study has three shortcomings. First, the conclusions of exploring the relationship between the NEPL and the market competitiveness of enterprises are inconsistent. Second, regarding the influence mechanism of the NEPL on the market competitiveness of enterprises, most of the literature is developed from the perspective of technological innovation, and few studies explore the influence mechanism of the above relationship from other perspectives. Finally, corporate strategy is an essential approach to respond to environmental changes and to adjust and allocate resources to enhance competitiveness in a timely and effective manner. Few studies have examined the impact of firms’ proactive adjustment of strategic orientation and flexible allocation of resources in response to environmental regulatory pressures, and the impact of firms’ strategic responses on their competitiveness in the context of the NEPL policy scenario.

3. Theoretical Analysis and Research Hypothesis

Theoretically, stricter environmental regulations increase the pressure on enterprises to comply. Heavily polluting enterprises must pay higher pollution control costs to cope with the environmental regulation constraints that may affect their competitiveness. However, Porter argued that enterprises may also actively engage in R&D innovation in the face of environmental regulations, responding to government environmental regulations by improving production technologies and equipment [18]. From this perspective, the implementation of the NEPL improves the productivity and competitiveness of enterprises [41]. Based on the existing literature and theories, this study further analyzes the impact of the NEPL on the market competitiveness of heavy polluters from two perspectives: cost compliance and innovation incentives.

In terms of the “cost compliance effect”, environmental regulations increase the cost of compliance for firms, reduce the markup rate, and ultimately reduce their market competitiveness while keeping product prices constant. Conversely, with the implementation of the NEPL, the hard constraints’ of environmental regulation have shifted the negative externalities of environmental pollution onto enterprises, resulting in increased marginal costs. Government regulations are directly linked to emissions from enterprises and are inextricably linked to their production and operational activities. Heavily polluting enterprises exhibit high pollution and emission characteristics that significantly increase their environmental regulatory costs. However, in response to these rising costs, heavy polluters may adopt a more conservative strategy to minimize costs and maximize benefits. Heavily polluting enterprises eliminate high-polluting production capacities and scale back high-polluting production projects to meet the impact of environmental regulations on their competitiveness and achieve environmental compliance. Therefore, whether environmental regulations directly increased costs for firms or whether firms adopt compliance behaviors in response to strict regulations will considerably increase marginal costs for firms, and thus adversely affect their market competitiveness.

Owing to the “innovation incentive effect”, the NEPL has stimulated heavy polluters to innovate and research, and the benefits of technological innovation have compensated for the marginal costs of enterprises while creating good conditions for enterprises to improve their market competitiveness. The NEPL implementation is selective and incentive-based, imparting positive externalities to enterprises. Although strict environmental regulations increase firms’ marginal costs considerably, they are accompanied by tax incentives, government subsidies, and economic resources granted to firms. Companies with more access to resources are more likely to adopt aggressive strategies, actively participate in environmental management, upgrade environmental protection and energy-saving equipment, improve production technologies, and develop innovative products. To achieve China’s “double carbon” goal, heavily polluting enterprises are innovating to achieve cleaner production, gaining compensation for innovation, and taking advantage of the market [18,42], which is beneficial to their market competitiveness. Additionally, the NEPL strengthens the government’s environmental regulatory constraints and corporate environmental governance disclosure responsibilities, requiring companies to publicly disclose their environmental protection information. Enterprises reduce information asymmetry and financing constraints through proactive compliance, which creates conditions for their innovative activities. Enterprises use technological innovation to cover the costs of corporate environmental investments, gain economic and political resources to invest in environmental technologies, and improve their competitiveness. From this perspective, environmental regulation has a positive externality in that it “incentivizes” heavily polluting enterprises to engage in environmental regulation technology innovation by increasing penalties, promoting greater transparency of their environmental information, and reducing opportunistic behavior in concealing environmental information [43]. In addition to enterprises, the public awareness of environmental protection has gradually increased. Consumers have a higher preference for cleaning products, and more investors are concerned about the fulfillment of corporate environmental responsibility [44]. Studies also show that investors support this positive environmental governance behavior despite the increased cost of corporate environmental investments [45]. Investors and consumers prefer reputable companies and cleansing products that comply with the environmental norms. As public awareness of environmental protection increases, heavily polluting enterprises are exploring new technologies and developing new products [46]. In the face of environmental regulations, “hard constraints” enterprises have an incentive in the name of environmental protection, environmental responsibility, and efforts to enhance their market competitiveness to attract long-term investment. Heavily polluting enterprises tend to choose cleaner technologies to signal positive environmental behavior to the outside world. Therefore, it is possible to achieve a “win-win” situation in which stricter environmental regulations and increased market competitiveness of enterprises are achieved [47]. The NEPL implementation imposes regulatory costs on companies. But in fact, the economic benefits of “innovation compensation” through environmental investment can offset the marginal cost of environmental regulation, which ultimately increases the market competitiveness of enterprises. Based on the above analysis, we propose the following competing hypotheses:

Hypothesis 1a (H1a). 

The NEPL promotes the market competitiveness of heavily polluting enterprises.

Hypothesis 1b (H1b). 

The NEPL suppresses the market competitiveness of heavily polluting enterprises.

4. Materials and Methods

4.1. Sample Selection and Data Sources

The operating standards of heavily polluting enterprises have higher environmental protection requirements for the operation and production of enterprises in the industry, which are closer to the environmental protection policies considered in this study. By consulting the policies and regulations promulgated by the relevant departments in China over the last 10 years, this study selected the revised NEPL implemented on 1 January 2015, as the time point of policy impact. Considering the accuracy of the study, the sampling interval was set from 2010 to 2019 to verify whether the promulgation of the NEPL had a significant policy impact. To identify heavily polluting enterprises, this study utilized the MEP Notice issued by the Ministry of Environmental Protection in 2013. The 2013 MEP Notice limits the target enterprises to 15 industries: thermal power, steel, petrochemicals, cement, nonferrous metals, and chemicals. If a listed enterprise operates in one of the above fifteen industries, it is classified as heavily polluting. According to the Guidelines for the Industrial Classification of Listed Companies of the China Securities Regulatory Commission, heavily polluting enterprises belong to the same category as other industry-listed enterprises that are regarded as not heavily polluting. All heavily polluting enterprises were used as the experimental group and all non-heavily polluting enterprises were used as the control group based on the NEPL event. Further selection was conducted by excluding the following: (1) the financial sector, (2) companies that received special treatment from the Chinese exchange, (3) data from companies in their IPO or pre-IPO stage in the current year, (4) delisted companies, and (5) companies with missing financial data. Finally, 12,407 available observation data points were obtained. Financial data are collected from the WIND Database. To avoid the effects of extreme values, the study winsorizes the variables at the 1% level.

4.2. Model Setting and Definition of Variables

4.2.1. Model Setting

This study uses a DID model to analyze the effect of the NEPL on the market competitiveness of heavily polluting enterprises. Therefore, this study constructed the following regression model:

$$Marku{p}_{i,t}={\beta }_0+{\beta }_{1}D+{\beta }_{2}T+{\beta }_{3}P+{\beta }_{4}contro{l}_{i,t}+{\epsilon }_{it}$$

(1)

where the explanatory variable $Marku{p}_{i,t}$ is the market competitiveness of heavily polluting enterprises; it denotes the magnitude of the additive rate of enterprise $i$ in year $t$. $D$ is the core explanatory variable, and it is the cross-product term of the grouping dummy variable ($T$) and time dummy variable ($P$). $contro{l}_{i,t}$ denotes the other control variables, and ${\epsilon }_{it}$ denotes the error term. The main coefficients of interest in this study are cross-coefficients, which reflect the effects of environmental regulation policies. If the coefficient is negative, that is, after a policy shock, environmental regulations reduce the market competitiveness of heavily polluting enterprises. Conversely, if the coefficient is significantly positive, the NEPL exert a positive externality.

4.2.2. Definition and Measurement of Variables

(1) Measurement of enterprise market competitiveness. In economics, the markup rate is a measure of how much price deviates from cost [48] and reflects a corporation’s market competitiveness [49], as well as its ability to compete profitably in the marketplace [50]. Therefore, this study refers to existing studies and uses the markup rate to measure the magnitude of market competitiveness, and calculates an enterprise’s markup rate using the DW structural model approach [51]. In this study, intermediate goods input was used as a proxy variable for productivity, ${\omega }_{it}$, and the transcendental log production function was used to avoid possible endogeneity and covariance problems and ensure the validity of the parameter estimation. The specific calculations are as follows: (1) use the LP method [52] to estimate firm-level total factor productivity as a proxy variable and (2) construct a transcendental logarithmic production function with three interaction terms

$$\begin{array}{c}{y}_{it}={\beta }_l{l}_{it}+{\beta }_k{k}_{it}+{\beta }_m{m}_{it}+{\beta }_{ll}{l}_{it}^2+{\beta }_{kk}{k}_{it}^2+{\beta }_{mm}{m}_{it}^2+{\beta }_{lk}{l}_{it}{k}_{it}\\ +{\beta }_{lm}{l}_{it}{m}_{it}+{\beta }_{km}{k}_{it}{m}_{it}+{\beta }_{lmk}{l}_{it}{m}_{it}{k}_{it}+{\omega }_{it}+{\epsilon }_{it}\end{array}$$

(2)

where $y_{it}$, $l_{it}$, $k_{it}$, and $m_{it}$ denote total enterprise output, number of employees, capital input, and intermediate goods input, respectively, after taking the natural logarithm. ${\beta }_l$ to ${\beta }_{lmk}$ are the parameters to be estimated. ${\omega }_{it}$ denotes enterprise productivity, ${\epsilon }_{it}$ denotes the error term. Proxy variables for productivity were introduced into the model and regressed to obtain estimates of expected output and residuals. (3) Symbol $\beta$ characterizes the parameter vector to be estimated and let ${\omega }_{it}\left(\beta \right)$ obtain the productivity perturbation term ${\zeta }_{it}\left(\beta \right)$ for a given $\beta$ after a nonparametric regression of its lagged term ${\omega }_{it-1}\left(\beta \right)$. Generalized moment (GMM) estimation is performed by constructing moment conditions to obtain the estimated parameters as the output elasticities of intermediate goods inputs; (4) Drawing on De Loecker and Warzynski [51], the formula for the additive rate is obtained

$${\mu }_{it}={\theta }_{it}^M{\left({\alpha }_{it}^M\right)}^{-1}$$

(3)

The estimated value of the markup rate of enterprise $i$i in period it can be obtained by introducing the input share of intermediate goods and the output elasticity of intermediate goods into the above equation. The markup rate measures an enterprise’s market competitiveness and is expressed in terms of $Markup$.

(2) Environmental regulation policy effects. This study considers the official implementation of the NEPL as a policy shock point, constructs a time-determination variable and a policy dummy variable, and uses the product of the two variables as the core explanatory variable. $timeP$ denotes the time-determination variable. This variable is zero before the NEPL shock was implemented in 2015 and one after the policy shock; $T$ is a dummy variable assigned a value of one for the experimental group and zero for the control group in model (1). $D$ is the interaction term between $T$ and $P$; for the experimental group, $D=0$ before the implementation of the NEPL and $D=1$ after the implementation; for the control group, $D=0$, regardless of whether the policy was implemented.

(3) Control variables. Concerning the established theoretical and empirical research literature, this study set the control variables as follows: the scale of the company (Size), calculated by taking the natural logarithm of the total assets of the sample companies at the end of the year; return on assets (ROA), calculated by dividing net profit by the average balance of total assets; growth opportunity (Growth), expressed by the growth rate of sales revenue; company solvency (Cashflow), expressed by the cashflow ratio; company governance level (Govern), expressed by the fluctuation of stock returns; risk-taking capacity (Risk), expressed by the fluctuation of stock returns; independence (Top1), calculated by taking into account the supervision, decision-making, and incentives; and year of company establishment (FirmAge), expressed as the company’s year of listing, year dummy variable, and annual dummy variable (year).

5. Empirical Results and Analysis

5.1. Descriptive Statistics

Table 1. Descriptive statistics of the entire sample.

Variable	N	Mean	p50	Sd	Max	Min
Markup	12,407	1.34	1.28	0.26	2.62	0.86
D	12,407	0.20	0.00	0.40	1.00	0.00
Size	12,407	22.26	22.09	1.20	26.14	19.76
ROA	12,407	0.04	0.03	0.05	0.16	−0.14
Growth	12,407	0.16	0.10	0.36	2.87	−0.57
Cashflow	12,407	0.05	0.05	0.060	0.24	−0.18
Govern	12,407	−0.15	−0.32	0.95	2.44	−2.39
Risk	12,407	−3.61	−3.63	0.30	−2.76	−4.61
Top1	12,407	0.34	0.32	0.14	0.76	0.08
FirmAge	12,407	2.86	2.89	0.30	3.53	1.61

summarizes the descriptions of the variables. Table 1 shows that the mean value of the market competitiveness of the enterprises in the sample is 1.34, the minimum value is 0.86, and the maximum value is 2.62, with a standard deviation of 0.26, indicating the prevalence of market competition among Chinese A-share listed enterprises and the large gap between them. The mean value of the NEPL policy effect ‘D’ is 0.20, which indicates that 20% of the enterprises are heavily polluting industries, illustrating the wider scope of NEPL implementation. Therefore, policy is an important tool for governments to regulate the environmental protection of heavily polluting enterprises, thus providing a good opportunity for this study. In addition, the other control variables of the sample are not significantly different from the average of Chinese listed enterprises. Which outcome indicates that the sample is representative as a whole, and the statistical characteristics of the data are consistent with previous literature.

5.2. Empirical Results from the Environmental Regulation on the Market Competitiveness of Heavily Polluting Enterprises

5.2.1. Parallel Trend Assumption Analysis

To satisfy the validity of the double-difference method estimation, the DID method needs to verify the parallel trend assumption; which is necessary to verify that if the experimental group is not affected by policy shocks, then the changing trend should be the same as that of the control group. Panels A and B of Figure 1 compare the changes in market competitiveness of the experimental and control groups before and after the NEPL. The data show that before the implementation of the NEPL, the mean market competitiveness of the experimental and control groups maintained roughly the same growth trend. However, after the implementation of the NEPL, the market competitiveness of the experimental group showed a significant increase, whereas the change in the market competitiveness of the control group remained stable. Therefore, based on the results of the parallel trend assumption test, it is appropriate to use the DID model to explore the effects of the environmental regulation on enterprises’ market competitiveness. Focusing on the trend of market competitiveness after the NEPL, the market competitiveness of the experimental group increased relative to that of the control group, which tentatively suggests that the NEPL policy may have boosted the competitiveness of heavily polluting enterprises.

5.2.2. Benchmark Regression Results

To examine the effect of the NEPL on the market competitiveness of heavily polluting enterprises, we conducted a regression analysis of the full sample data. In accordance with the previous section, this study analyzes empirically with the help of the DID method. The results of the benchmark regressions are presented in

Table 2. Benchmark Regression Results.

Variable	DID		PSM-DID
	(1)	(2)	(3)
	Markup	Markup	Markup
D	0.040 ***	0.037 ***	0.034 ***
	(0.005)	(0.005)	(0.006)
Size		−0.026 ***	0.001
		(0.003)	(0.004)
ROA		−0.102 ***	−0.177 ***
		(0.023)	(0.029)
Growth		−0.067 ***	−0.064 ***
		(0.003)	(0.004)
Cashflow		−0.162 ***	−0.131 ***
		(0.021)	(0.027)
Govern		0.007 **	0.012 ***
		(0.003)	(0.004)
Risk		0.019 ***	0.020 **
		(0.006)	(0.008)
Top1		0.109 ***	0.120 ***
		(0.020)	(0.025)
FirmAge		−0.092 ***	−0.081 ***
		(0.025)	(0.031)
_cons	1.297 ***	2.151 ***	1.515 ***
	(0.004)	(0.090)	(0.113)
N	12,407	12,407	6966
r2	0.144	0.207	0.264
year	Yes	Yes	Yes

t-statistics in parentheses, *** p < 0.01, ** p < 0.05.

. According to the regression results, the coefficient of the interaction term ‘D’ was significantly positive at the 1% level, indicating that the NEPL policy had a positive effect on the market competitiveness of heavily polluting enterprises. Furthermore, the interaction term remains significant for all control variables, and H1b is supported. For the control variables, the coefficient of company size is negative, indicating that the larger the company size, the smaller the market competitiveness, implying that the larger the size of the enterprise may not be more competitive in the market, while the better the corporate governance and the higher the risk-taking ability, the better its performance in the market. The higher the shareholding ratio of the enterprise’s first largest shareholder, the higher the market advantage of the enterprise. The older the enterprise, the lower the cost-plus rate, implying that the longer a firm has been based on the market, the greater the market competitiveness.

In addition, after testing whether the double-difference model satisfied the parallel trend assumption, PSM was used to overcome systematic differences in sample selection and eliminate sample selection bias. The primary reason for performing the PSM step was to ensure that the characteristics of the control and experimental groups were the same. The estimation based on the PSM-DID method solves the sample selection bias problem and largely avoids endogenous problems arising from omitted variables and yields the policy treatment effect. Therefore, this study used the PSM-DID method for estimation. After selecting all the control variables as firm characteristic variables to match the experimental and control groups, unmatched samples were removed and regressed according to Model (1). The regression results are presented in Column (3) of the above table. The results indicate that after utilizing the PSM-DID method, environmental regulation still significantly enhances the market competitiveness of heavily polluting enterprises. Before conducting the matching estimation, we tested the validity of the PSM-DID model to determine whether the variables were balanced in the experimental and control groups after matching.

Table 3. PSM-DID method adaptation test (common support hypothesis).

Variable	Control Group Mean	Experimental Group Mean	Differential	t-Value	p-Value
Markup	1.345	1.285	−0.06	7.52	0.0000 ***
Size	22.349	22.407	0.059	1.57	0.1176
ROA	0.032	0.033	0.001	0.83	0.4089
Growth	0.156	0.158	0.002	0.16	0.8708
Cashflow	0.055	0.055	0.000	0.21	0.8341
Govern	−0.441	−0.458	−0.017	0.68	0.2609
Risk	−3.702	−3.709	−0.007	1.12	0.5783
Top1	0.375	0.377	0.003	0.56	0.7014
FirmAge	2.728	2.741	0.014	1.52	0.1294

*** p < 0.01.

reports the common support hypotheses. The results indicate that the means of the covariates in the experimental and control groups did not differ significantly after matching, supporting the use of the PSM-DID approach. The results of the selected tests for each covariate show no significant difference in all variables after matching. However, there is a significant difference in the market competitiveness variable”, which justifies the use of the PSM-DID method in this study.

The kernel matching method was used for PSM estimation. Figure 2 plots the density function of the propensity score values for the matching effect of the experimental and control groups before the PSM estimation. The graphical results demonstrate that the probability densities of the propensity scores of the experimental and control groups were significantly similar after matching, indicating a better matching effect. In summary, it was further demonstrated that the selection of the PSM-DID method in this study was feasible and reasonable based on the common supporting hypothesis.

5.2.3. Analysis of the Mechanisms by Which the NEPL Affects the Market Competitiveness of Enterprises

The empirical results indicate that the NEPL can significantly increase the market competitiveness of heavily polluting enterprises. However, the competitiveness of all heavily polluting enterprises increased. What is the mechanism by which the “hard constraint” of environmental regulation enhances the market competitiveness of heavily polluting enterprises? Strategic flexibility is a firm’s dynamic ability to mitigate adverse shocks due to environmental changes and facilitate flexible resource allocation. It has been well established that strategic flexibility brings competitive advantages to firms under turbulent regulations [53,54], enabling them to quickly reallocate resources and exploit strategic effects [55,56,57], and that firms with greater strategic flexibility are more flexible in the face of the NEPL [58]. This study also argues that after the implementation of the NEPL, firms with greater strategic flexibility will actively take effective strategic measures to rationally allocate internal and external resources to respond to regulation requirements, which improves their market competitiveness. Therefore, from the strategic flexibility perspective, this study analyzes the mechanism by which NEPL enhances the market competitiveness of heavily polluting firms.

First, strategic flexibility, as a dynamic capability for firms to gain competitive advantage in response to changes in the external environment, helps firms quickly adjust their strategic orientation and reduce product design and manufacturing costs, which helps meet market demand under the implementation of the NEPL [54,56]. Based on the compliance motive, heavily polluting firms autonomously decide the direction and efficiency of resource allocation. Enterprises tend to identify opportunities that match their own resources and capabilities related to production, operation, and financial decision-making. The stronger the strategic flexibility, the more opportunities are available to enterprises to achieve strategic transformation and upgrading to rapidly capture the market and subsequently improve market competitiveness [59]. Second, strategic flexibility helps companies overcome strategic inertia [58], allocate resources flexibly, and strengthen the positive impact of new environmental protection laws on corporate management innovation. Conversely, as consumers’ demand for clean products increases, heavy polluters adjust their resource allocation to conduct environmental protection investments and integrate green production into the entire process of enterprise management to meet consumers’ environmental protection needs and develop markets. Strategic flexibility can overcome past heavy environmental pollution, resource mismatch, and other business practices that do not meet environmental requirements; broaden existing resource channels to reshape organizational structures; help companies develop new, clean substitutes to meet customer demand. Strategic flexibility can help companies improve their responsiveness to stringent regulations and ensure effective deployment of resources in green manufacturing, green operations, and green marketing to mitigate the adverse impact of tightening environmental regulations. Finally, strategic flexibility wins market recognition for the firm and enhances its position in the market, serving as a buffer against the pressures of environmental regulation, thus facilitating the firm’s competitiveness under NEPL [34]. NEPL innovatively introduces information disclosure and public participation. The recognition of stakeholders, including the public, peers, suppliers, and market customers, is crucial for business operations. When stakeholders’ recognition of heavy polluters to conduct active environmental management and marketing products is more acceptable, it is favorable for companies to obtain social resource support, which creates conditions for companies to fully use strategic flexibility to improve market competitiveness [60]. Simultaneously, the NEPL clearly states that the government will support heavily polluting firms that exceed pollution reduction targets using diverse resources, including prices, policy information, and capital [3]. Reduce the cost and uncertainty of strategic flexibility application in the process of creating market advantages for heavily polluting enterprises and overcome the negative impact of market competitiveness of enterprises due to strategic confusion and resource mismatch in the production and marketing of their products. In summary, the stronger the strategic flexibility, the better it is for enterprises to alleviate the pressure of environmental regulations and thus enhance their market competitiveness.

(1) DID model test for the full sample

To analyze the mechanism by which NEPL affect enterprises’ market competitiveness, this study draws on the three-step approach of Shi et al. to verify whether the NEPL enhances market competitiveness by increasing enterprises’ strategic flexibility [61]. The mechanism test model was divided into three steps.

The first is’ impact of the NEPL on the radicalness of corporate strategic flexibility.

$$Strateg{y}_{i,t}={\alpha }_0+{\alpha }_{1}D+{\alpha }_{2}contro{l}_{i,t}+{\epsilon }_{it}$$

(4)

Second, the impact of the NEPL on market competitiveness was validated.

$$Marku{p}_{i,t}={\beta }_0+{\beta }_{1}D+{\beta }_{2}contro{l}_{i,t}+{\epsilon }_{it}$$

(5)

Finally, the multiplicative difference term is added to the regression equation together with the degree of aggressiveness of corporate strategic flexibility.

$$Marku{p}_{i,t}={\gamma }_0+{\gamma }_{1}D+{\gamma }_{2}Strateg{y}_{i,t}+{\gamma }_{3}contro{l}_{i,t}+{\epsilon }_{it}$$

(6)

where $Strateg{y}_{i,t}$ denotes strategic flexibility. Concerning existing research [62,63], this study constructs a measure of corporate strategic flexibility in six dimensions: corporate R&D aggressiveness, historical sales growth rate, efficiency of corporate production and operation, product marketing and service, expense ratio, volatility of the number of employees, and capital intensity. If the coefficient ${\alpha }_1$ in the model (4) is positive, the NEPL has increased the strategic flexibility of heavily polluting enterprises. If the coefficient ${\beta }_1$ in the model (5) remains positive and the coefficients of both ${\gamma }_1$ and ${\gamma }_2$ in the model (6) are positive, corporate strategy flexibility is the mechanism by which the NEPL are used for market competitiveness. The NEPL increases market competitiveness by enhancing their enterprises’ strategic flexibility.

Table 4. Results of the mechanism test based on corporate strategy.

Variable	A	B	C
	Strategy	Markup	Markup
D	0.131 **	0.037 ***	0.036 ***
	(0.062)	(0.005)	(0.004)
Strategy			0.012 ***
			(0.001)
Size	0.324 ***	−0.026 ***	−0.025 ***
	(0.044)	(0.003)	(0.003)
ROA	−5.561 ***	−0.102 ***	0.010
	(0.316)	(0.023)	(0.023)
Growth	−0.855 ***	−0.067 ***	−0.069 ***
	(0.044)	(0.003)	(0.003)
Cashflow	−1.327 ***	−0.162 ***	−0.155 ***
	(0.291)	(0.021)	(0.021)
Govern	0.054	0.007 **	0.005 *
	(0.039)	(0.003)	(0.003)
Risk	0.161 *	0.019 ***	0.014 **
	(0.085)	(0.006)	(0.006)
Top1	0.769 ***	0.109 ***	0.106 ***
	(0.275)	(0.020)	(0.020)
FirmAge	−1.690 ***	−0.092 ***	−0.115 ***
	(0.337)	(0.025)	(0.024)
_cons	−1.492	2.151 ***	2.027 ***
	(1.231)	(0.090)	(0.089)
N	12,407	12,407	12,407
r2	0.093	0.207	0.233
year	Yes	Yes	Yes

t-statistics in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1.

reports the results of the mechanism test based on corporate strategic flexibility. The results of the first regression step show that the coefficient of the policy effect on enterprises’ strategic flexibility is significantly positive, and this result is consistent with the elaboration of the previous theoretical analysis that the NEPL enhances enterprises’ strategic flexibility. The results of the second regression step indicate that the NEPL enhances enterprises’ market competitiveness. The results of the third test show that after including both strategic flexibility and the policy effect in the empirical model, strategic flexibility significantly increases the market competitiveness of enterprises. The policy effect remains significantly positive, confirming that the NEPL improves the market competitiveness of heavily polluting enterprises by increasing their strategic flexibility.

(2) Test for innovation compensation effect

Based on the strategic response perspective of enterprises, this study further analyzes the “puzzle” of why the NEPL has increased the market competitiveness of heavily polluting enterprises. As previously mentioned, heavy polluters respond proactively to the adverse impacts of environmental regulations by increasing their strategic flexibility. Theoretically, enterprises with high strategic flexibility actively pursue technological development and innovative new products. This is because there is complementarity between the ability to innovate and sell new products, which indirectly enhances an enterprise’s competitive advantage. After the implementation of the NEPL, the government will adopt several preferential measures such as subsidies and tax breaks to motivate enterprises to actively participate in environmental protection, which will help them gain economic and political resources and seize market advantage. Additionally, the NEPL is “incentive-based”. It has an “innovation compensation effect”, motivating enterprises to conduct innovative R&D to improve the productivity of their products while achieving cleaner production and increasing market competitiveness. Therefore, this study further tests whether, under strong environmental regulations, heavily polluting enterprises with a high level of strategic flexibility will invest more in R&D, compensate through innovation, and eventually increase their market competitiveness. Based on the previous paper, a sample of heavily polluting enterprises is selected and divided into an experimental group (strategic value $\mathrm{Strategy}>12$ with $\mathrm{chi}=1$ for a high level of strategic flexibility) and a control group (strategic value $\mathrm{Strategy}\le 12$ with $\mathrm{chi}=0$ for a low level of strategic flexibility) based on corporate strategic heterogeneity to construct a mediating effect model.

$$Marku{p}_{i,t}={\alpha }_0+{\alpha }_{1}time\times chi+{\alpha }_{2}contro{l}_{i,t}+{\epsilon }_{it}$$

(7)

$$R{d}_{i,t}={\beta }_0+{\beta }_{1}time\times chi+{\beta }_{2}contro{l}_{i,t}+{\epsilon }_{it}$$

(8)

$$Marku{p}_{i,t}={\gamma }_0+{\gamma }_{1}time\times chi+{\gamma }_{2}Rd+{\gamma }_{3}contro{l}_{i,t}+{\epsilon }_{it}$$

(9)

where $time\times chi$ denotes the policy effect of the NEPL on heavily polluting enterprises with a high level of strategic flexibility and the other variables are defined in line with the previous section.

Table 5. Results of the test for the innovation compensation effect.

Variable	Model (7)	Model (8)	Model (8)
	Markup	Rd	Markup
time $\times$ chi	0.030 ***	0.002 ***	0.029 ***
	(0.006)	(0.001)	(0.006)
Rd			0.762 ***
			(0.175)
Size	0.025 ***	0.001 ***	0.024 ***
	(0.005)	(0.001)	(0.005)
ROA	−0.191 ***	−0.005	−0.187 ***
	(0.043)	(0.004)	(0.043)
Growth	−0.068 ***	−0.003 ***	−0.066 ***
	(0.006)	(0.001)	(0.006)
Cashflow	−0.100 ***	−0.007 **	−0.095 ***
	(0.033)	(0.003)	(0.033)
Govern	0.011 **	−0.001 *	0.012 **
	(0.005)	(0.000)	(0.005)
Risk	0.026 ***	0.000	0.025 ***
	(0.010)	(0.001)	(0.010)
Top1	0.084 ***	−0.000	0.084 ***
	(0.031)	(0.003)	(0.031)
FirmAge	−0.119 ***	−0.010 **	−0.111 ***
	(0.040)	(0.004)	(0.040)
_cons	1.086 ***	0.008	1.080 ***
	(0.146)	(0.014)	(0.146)
N	4165	4165	4165
r2	0.286	0.121	0.290
year	Yes	Yes	Yes

t-statistics in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1.

reports the results of the test for the innovation compensation effect. Model (7) tests the effect of the NEPL on the market competitiveness of heavily polluting enterprises with a high level of strategic flexibility, and the regression coefficient of policy effect $time\times chi$ is significantly positive. It indicates that the market competitiveness of enterprises with a high level of strategic flexibility significantly increases. Next, the results of model (8) show that the coefficient of $time\times chi$ is significantly positive, indicating that firms with a high level of strategic flexibility in the sample of heavy polluters have increased their technology R&D investment under strong environmental regulation; the results of model (9) show that the regression coefficient of the policy effect time $\times$ chi is still significantly positive, and the coefficient of Rd is also significantly positive.

5.2.4. Robust Check

(1) Excluding the Disruptive Impact of the NEPL Amendments in 2014

The NEPL was revised and passed on 4 April 2014, and announced to be officially implemented on 1 January 2015. The results of the parallel trend test in the previous section show a significant increase in the market competitiveness of the heavily polluting enterprises in 2014. Therefore, the adoption of the 2014 NEPL revision may have affected market competitiveness. This led to an overestimation of the policy effects of the environmental regulations in this study. To identify this effect, we draw upon Shi et al. [61] and include a 2014 event dummy variable in the benchmark model. If the policy effect of the NEPL after adding the 2014 event dummy variable is not significant, the conclusion of this study that NEPL enhance the market competitiveness of heavily polluting enterprises is not robust. If the policy effect of the NEPL after adding the event dummy variable of 2014 is significant but the coefficient decreases, then the previous estimation result is overestimated; however, this overestimation phenomenon does not affect the conclusions of this study. The conclusion of the main test indirectly indicates the relative robustness of the estimation results of the previous main test.

Table 6. A test to exclude interference with the effect of the 2014 event.

Variable	Baseline Return	Mechanism Testing
	Markup	Strategy	Markup	Markup
D	0.036 ***	0.131 **	0.036 ***	0.034 ***
	(0.005)	(0.062)	(0.005)	(0.004)
2014 Event Effect Impact	0.159 ***	0.030	0.159 ***	0.171 ***
	(0.014)	(0.193)	(0.014)	(0.014)
Strategy				0.012 ***
				(0.001)
Control variables	Control	Control	Control	Control
N	12,407	12,407	12,407	12,407
r2	0.202	0.093	0.202	0.230
year	Yes	Yes	Yes	Yes

t-statistics in parentheses, *** p < 0.01, ** p < 0.05.

reports the test results excluding disturbances from the 2014 event shock. The coefficient of the 2014 event effect in the benchmark model is significant, indicating that adopting the NEPL revision effectively increases market competitiveness. Meanwhile, the policy coefficient of the NEPL remained significantly positive; however, the coefficient was reduced compared with the benchmark regression model. This finding suggests that the effect of NEPL on enterprises’ market competitiveness has been overestimated. However, the NEPL effect still exists and is significantly positive, indicating that the findings are robust. This is also true for the mechanism test models.

(2) Placebo Testing

Although this excludes the impact of the adoption of the 2014 event on the estimation in this study, other policies or regulations may interfere with the results in the context of accelerating the development of a green and low-carbon circular economy in China. To exclude this possibility, this study used a placebo test method based on the research designs of Butler & Cornaggia [64]. First, as a placebo test, we set a dummy year point before the actual year in which the NEPL was promulgated. If there is a causal effect between the NEPL and the market competitiveness of heavily polluting enterprises, then, if the event does not occur, the processing effect of the virtual NEPL cannot theoretically be observed. Thus, the coefficients should no longer be negative or significant. If the positive significance persisted in the placebo test, the previous estimates were meaningless. Figure 3 shows the distribution of the regression coefficients and corresponding p-values for the “pseudo-policy dummy variables” with 500 repeated placebo tests. The results indicate that the regression coefficients are concentrated around zero and the p-values of most of the estimated coefficients are not significant at the 10% level. This finding indicates that the results of the study are valid, as evidenced by the successful placebo test. Thus, it is reasonable to choose 2015 as the policy time node for the NEPL to construct a quasi-natural experiment, and the findings of this study are robust.

(3) Endogeneity Tests

In benchmark regressions, changes in enterprises’ market competitiveness may affect cash flows from the business process, the enterprise’s growth capacity, or its risk-taking abilities. To exclude possible bidirectional effects between the control variables and market competitiveness, the continuous control variables are lagged by one period for both the baseline regression and mechanism test models.

Table 7. Regression results excluding bivariate effects interference.

Variable	Baseline Return	Mechanism Testing
	Markup	Strategy	Markup	Markup
D	0.034 ***	0.131 **	0.034 ***	0.033 ***
	(0.005)	(0.062)	(0.005)	(0.005)
Strategy	0.011 ***			0.011 ***
	0.083 **			(0.001)
Control variables	Control	Control	Control	Control
N	10,304	10,304	10,304	10,304
r2	0.210	0.093	0.210	0.236
year	Yes	Yes	Yes	Yes

t-statistics in parentheses, *** p < 0.01, ** p < 0.05.

reports the results of the lagged control variable regressions. The results indicate that The lagged one-period regression results are consistent with the above findings and exclude the endogeneity problem due to reverse causality.

6. Heterogeneity Analysis

A previous study found that the NEPL can significantly enhance the market competitiveness of heavily polluting enterprises, and the effect of NEPL constraints also differs for enterprises with different market structures, regions, and nature-property rights. To answer this question, this study analyzes the heterogeneity of policies affecting the market competitiveness of heavily polluting enterprises based on differences in market structure, regional differences, and differences in property rights and summarizes the implementation space for the NEPL to play effectively.

6.1. Market Structure Differences Analysis

As a country in the middle of high-quality economic development, China has an imperfect market economy, which causes different market structures to exhibit different competitive dynamics. In a monopoly market, product concentration is high and competition among enterprises is low. In a competitive market, competition among enterprises is more intense because of low product concentration. The intensity of market competition is directly related to the magnitude of external competitive pressure on enterprises, which affects their innovation input decisions, product market pricing, and other behaviors [65]. In the face of environmental regulations, heavily polluting enterprises in free competitive markets could increase their technology investment and develop cleaner products to maintain market competitiveness [66]. Therefore, the impact of NEPL on enterprises’ market competitiveness differs under different competitive market structures [67]. In this study, the Herfindahl index is used to measure the degree of market competition. The median Herfindahl index is chosen as the critical value to classify the market structure in which the enterprise is in a competitive market and a monopolistic market. Model (1) is then regressed. When the Herfindahl index is below the critical value, the industry in which the enterprise is located is a competitive and free competitive market, and vice versa; it is a monopolistic market. Table 7 presents the regression results of heterogeneity analyses. The regression results of market structure heterogeneity show that the coefficients are not significantly different between competitive and monopolistic markets. This is probably because this study measures the market competitiveness of enterprises in terms of their markup rate and the degree of price deviation from cost. When enterprises are in a monopoly market, and the degree of competition among enterprises is low, enterprises are prone to collide with each other for collusion to increase the markup rate by raising the price of the product, which can increase market competitiveness.

6.2. Regional Differences Analysis

Uneven levels of regional economic and political development are a basic national condition in China. Differences in resource endowment, human capital accumulation, and environmental protection awareness in different regions may lead to different reactions from the sample enterprises to the implementation of the NEPL. In this study, we categorize the samples into eastern and midwestern regions based on the registered location of the enterprises, and conduct a subsample analysis. The results indicate that although the coefficients were significant in both the eastern and midwestern regions, they were significantly larger in the eastern region than in the midwestern region, indicating that the effect of NEPL on the market competitiveness of heavily polluting enterprises is more pronounced in the eastern region, which is consistent with existing studies [68].

6.3. Nature-Property Rights Differences Analysis

Different enterprise attributes can lead to differences in the effectiveness of regulations at the micro-enterprise level. In reality, the NEPL may appear to be “uniform”; however, it can create asymmetric environmental regulation costs among different enterprises [69]. The government controls SOEs, and heavily polluting Chinese-owned and Chinese-controlled enterprises bear greater social responsibility and pay closer attention to environmental issues. The introduction of the NEPL had a smaller impact on them. Compared with SOEs, non-SOEs may have neglected their environmental protection responsibilities before the official implementation of the NEPL because they were more concerned about their own economic benefits. Under the strict regulatory constraints of NEPL, non-state enterprises are forced to reduce pollution and emissions, improve quality and efficiency, and respond quickly to policies to enhance market competitiveness. This study divides the sample into state-owned and non-state-owned enterprises (non-SOEs), according to whether or not they are state-controlled.

Table 8. Results of the heterogeneity analysis.

Variable	Market Structure Heterogeneity		Regional Heterogeneity		Property Heterogeneity
	Competitive Market	Monopoly Market	Eastern Region	Midwest Region	State-Owned	Non-State
	Markup	Markup	Markup	Markup	Markup	Markup
D	0.032 ***	0.033 ***	0.061 ***	0.017 ***	0.019	0.043 ***
	(0.007)	(0.007)	(0.008)	(0.005)	(0.006)	(0.006)
Control variables	Control	Control	Control	Control	Control	Control
N	6457	5950	7849	4558	4655	7752
r2	0.213	0.204	0.230	0.195	0.262	0.189
Year	Yes	Yes	Yes	Yes	Yes	Yes

t-statistics in parentheses, *** p < 0.01.

shows that the coefficient of the interaction term is significantly positive in the sample of non-SOEs but is not significant in the sample of SOEs. This finding indicates that the NEPL has a more significant impact on the market competitiveness of non-SOEs than on that of SOEs.

7. Conclusions

As an environmental regulation policy, the NEPL significantly influenced the behavior of heavily polluting enterprises. This study incorporates NEPL, strategy flexibility, and enterprises’ market competitiveness into the same analytical framework and uses Chinese Shanghai and Shenzhen A-share listed enterprises from 2010 to 2019 as the research objects to analyze the impact of the NEPL on the market competitiveness of heavily polluting enterprises, the mechanism of action, and the space of effective play. Further tests the “innovation compensation effect”. The results indicate that the NEPL significantly enhances the market competitiveness of heavily polluting enterprises, and this conclusion holds after various robustness tests. The mechanism of action test shows that in the context of NEPL, enterprises increase their market competitiveness by increasing their strategic flexibility in the face of environmental regulation. Under environmental regulations, enterprises with a high level of strategic flexibility increase their market competitiveness by increasing their R&D and innovation investments to take advantage of the innovation compensation effect. The heterogeneity analysis shows that the policy of the NEPL is “selective”, and the effect of the NEPL on the market competitiveness of heavily polluting enterprises is greater in non-state enterprises and enterprises in the eastern region, whereas the effect of market structure differences on this relationship is not significant.

This study confirms that a “win-win” situation between environmental regulation and increased market competitiveness of heavily polluting enterprises is achievable. Enterprises are embedded in various environments in which the government, market, and public influence strategic choices. As a part of the market, heavily polluting enterprises are also considered as the “source of environmental pollution”, and in the context of the NEPL, they should strive to improve the level of strategic flexibility, strengthen the sense of strategic adjustment, and actively respond to changes in environmental dynamics by actively conducting innovative R&D and continuously improving innovation capacities. They can also control pollution, reduce waste emissions, achieve sustainable resource utilization, and ultimately enhance the market competitiveness of enterprises. Based on the conclusions of this study, it is recommended that government departments continuously improve the laws and regulations of environmental protection, increase the government’s environmental supervision and punishment for environmental pollution, and refine the management methods of various pollutants to motivate heavily polluting enterprises to conduct active innovation activities to enhance their competitiveness and profitability. Additionally, the NEPL is an inelastic environmental regulation tool implemented by the government, and both inelastic and elastic environmental regulations have been widely used in environmental governance. How flexible environmental regulation affects the behavior of enterprises and its influence mechanism are not yet clear and need to be further explored, which is our next main research direction.