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Article

Party Branch Embeddedness and Urban–Rural Environmental Inequality: Self-Regulation or Pollution Shelter?

by
Hongzhen Zhang
1,
Jingyang Yu
2 and
Yakun Chen
3,*
1
School of Management, Hebei University, Baoding 071000, China
2
Beijing Pinggu District Culture and Tourism Bureau, Beijing 101299, China
3
China Rural Revitalization and Development Research Center, Beijing Normal University, Beijing 100875, China
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(16), 6713; https://doi.org/10.3390/su16166713
Submission received: 9 July 2024 / Revised: 29 July 2024 / Accepted: 2 August 2024 / Published: 6 August 2024
Browse Figures
Figure 1
<p>β contour plot.</p> "> Figure 2
<p>Contour plot of the T statistics.</p> ">
Review Reports Versions Notes

Abstract

:
With the deepening of environmental governance, the overall environmental quality of the region has been improved. However, internal environmental inequality, especially urban–rural environmental inequality, has continued to come to the fore. Nevertheless, there are still few studies on how to mitigate the increasing urban–rural environmental inequality. On the basis of examining the urban–rural environmental inequality in China’s environmental emission reduction investment dimension, this research verified the impact and mechanism of informal regulatory forces (grassroots party organizations) in alleviating urban–rural environmental inequality. In particular, based on an empirical analysis of data from the Chinese Private Enterprise Survey (CPES) 2006–2014, this study found that (1) investment in environmental management of polluting enterprises in rural areas is significantly lower than in urban areas, and the trend of urban–rural environmental inequality is intensifying; (2) urban–rural environmental inequality is more pronounced at the enterprise level in areas with larger enterprises and greater environmental enforcement and that urban-centered environmental regulatory policies continue to exacerbate urban–rural environmental inequality; and (3) the embeddedness of regional party organizations can narrow the gap between urban and rural environmental protection investment by private enterprises and alleviate urban–rural environmental inequality. The specific pathway is to improve rural enterprises’ social responsibility awareness and policy implementation. Based on the above findings, this paper argues that a gradual break with “urban-centered environmentalism” is the fundamental solution to urban–rural environmental inequality. However, in the current context of limited resources for formal environmental regulation, the power of informal environmental regulation can still mitigate these effects.

1. Introduction

Environmental inequality, especially between regions within countries, has become an important global environmental issue [1]. Although China’s overall ecological environment has improved, the structural, root, and trend pressures on ecological environmental protection have not been fundamentally alleviated. The construction of an ecological civilization is still in a critical period of overlapping pressures and heavy loads. As the limited environmental regulatory resources are mainly concentrated in urban areas, urban–rural environment inequality (hereinafter referred to as UUEI) has become a typical problem in the structural dimension of ecological environmental protection in China [2]. This inequality not only forms a mutually reinforcing vicious cycle with environmental depletion [1] but also damages the physical health of residents in low-income areas and aggravates preexisting income inequality and can lead rural areas to fall into the “environmental poverty trap” [3,4], which affects the sustainable economic and social development of rural areas in China [5]. Therefore, verifying the factual characteristics of UUEI and exploring potential ways to alleviate UUEI are of great significance for the government to grasp the full picture of environmental inequality, alleviate the structural problems of ecological and environmental protection, and therefore realize sustainable development.
Although UUEI is an important component of environmental inequality, the existing literature on UUEI and its alleviation strategies is still in its infancy. Existing studies on environmental inequality mainly focused on the measurement [6] of intergroup [7,8,9] and inter-regional environmental inequality [6,10], causes of problems [11,12,13], and mitigation strategies [1,6,14,15]. Many researchers have contributed solutions to curb interregional pollution transfer and environmental inequality [6,16,17,18]. However, owing to data limitations, few studies have revealed the effects of intraurban pollution transfer, especially the differences in pollution between urban centers and neighboring rural areas.
Fortunately, some scholars have gradually begun to pay attention to UUEI, but they still mainly focused on the causes of UUEI, with most studies based on theoretical and qualitative analysis. For example, based on theoretical analysis, Cao [19] found that the special urban–rural structural dichotomy and the “urban-centered” environmental protection model are important causes of UUEI in China. To the best of the authors’ knowledge, the study by Long et al. [2] is currently the only study that focused on UUEI using empirical analysis. Based on data on the difference in pollution emission intensity between urban and rural firms in China, Long et al. [2] used empirical evidence to reveal UUEI for the first time and emphasized the role of public environmental concern in alleviating UUEI. However, it is worth noting that the mechanism of informal regulation represented by public environmental concern is still to draw the government’s attention to environmental problems, increase the government’s investment in environmental management, and improve the government’s regulation [2], which remains limited by insufficient resources for formal environmental regulation to correct UUEI. However, it is worth noting that the mechanism of informal regulation, represented by public environmental concern, has yet to draw the government’s attention to environmental issues, increase government investment in environmental management, and improve government regulation [2]. The alleviation of UUEI is still limited by insufficient resources for formal environmental regulation. Considering China’s severe pollution situation and its large rural population, it is particularly urgent to explore potential pathways to alleviating China’s UUEI in the context of limited regulatory resources and a lack of formal environmental regulation in rural areas.
It is worth mentioning that Chinese enterprises have unique organizational governance characteristics. The Communist Party of China (CPC) monitors and advises private enterprises on business decisions, compliance with the law, and workers’ rights and interests through the establishment of Party branches in the private sector. Existing literature suggests that corporate party organizations play an important role in safeguarding workers’ welfare [20], providing employment protection [21,22], facilitating the participation of private firms in social governance [23], and boosting research and development (R&D) investment [24]. Therefore, regional grassroots party organizations may be able to improve the environmental governance behaviors of rural enterprises, thus alleviating UUEI. But whether and how regional grassroots party organizations affect rural–urban environmental inequality remains unclear. There is a lack of empirical research on grassroots party organizations and UUEI. If grassroots Party organization in enterprises can effectively alleviate UUEI, and its role is not constrained by the limited resources of formal environmental regulation, grassroots Party organizations could become an effective path to improve environmental inequality, providing limited resources for formal environmental regulation. This is especially the case in the context of the continuous promotion of the creation of grass-roots Party organizations in Chinese enterprises (By the end of 2016, 1.9 million private enterprises (68 percent) had established party branches, an increase of 16 percent from 2015 (Organization Department of the Central Committee of the Communist Party of China, 2017)).
On the basis of the above theoretical and practical background, this paper uses data from the Chinese Private Enterprise Survey (CPES) 2006–2014 to reveal the trends in urban–rural environmental inequality in China by manually collecting data on the geographic location of private enterprises and examining how party organization embeddedness affects UUEI. The main findings of this paper are as follows: (1) Investment in environmental management of polluting enterprises in rural areas is significantly lower than in urban areas, and UUEI is intensifying. (2) Heterogeneity analysis revealed that UUEI is more pronounced at the enterprise level in areas with larger enterprises and greater environmental enforcement and that urban-centered environmental regulatory policies continue to exacerbate UUEI. (3) Regional party organization embeddedness can narrow the gap between urban and rural environmental investment by private enterprises and alleviate UUEI. This positive effect stems from the fact that the embeddedness of party organizations can enhance the degree of policy implementation by rural enterprises and stimulate the environmental investment behavior of rural enterprises.
This paper makes the following marginal contributions to the literature: (1) In the context of literature on regional environmental inequality, in contrast to studies on the total amount of pollution emissions and the number of polluting enterprises at the regional level [25,26,27], this paper reveals environmental inequality for the first time from the micro perspective of corporate environmental protection investment. This perspective not only reveals the causes of environmental inequality in terms of the total amount and intensity of pollution but also reflects the developmental trend of environmental inequality, thereby expanding the understanding and research boundaries of environmental inequality. (2) In the context of the distinct national conditions of China’s dualistic structure and distinguishing itself from existing research on interregional environmental inequality, this paper manually collected private enterprises’ urban and rural locations, and determined the difference in environmental investment between urban and rural firms, focusing on revealing the unique urban–rural environmental inequality within Chinese regions; to a certain extent, compensating for the shortcomings of the literature on China’s environmental inequality, which fails to accurately penetrate the Chinese context. (3) The literature has seldom explored the evidence and solutions regarding the environmental inequality between urban and rural areas in China from an empirical perspective [2]. In contrast, this paper reveals the trends in UUEI in China based on data on corporate environmental investment and party organization embeddedness and found that party organization embeddedness can effectively improve deteriorating UUEI, which provides a solution to alleviate the increasing UUEI under limited regulatory resources in rural areas and with the absence of formal environmental regulation. (4) This paper provides a new research perspective on informal environmental regulation, expanding the perspective from external public participation and public opinion supervision to the grassroots party organizations within the enterprise, highlighting the role of grassroots party organizations embedded in environmental governance, especially in alleviating UUEI under limited environmental regulatory resources, revealing its unique internal supervision advantages. Thus, this paper enriches research in the field of informal environmental regulation.
The remainder of the paper is structured as follows: Part II conducts theoretical analysis and presents the research hypotheses; Part III introduces the empirical research design; Part IV presents the empirical results and analyses; Part V provides further analyses; and Part VI presents the conclusions and policy implications.

2. Theoretical Analysis and Research Hypotheses

Since the 1980s, as China’s urbanization process has accelerated, rising land and labor prices and the intensity of environmental regulations have forced industrial enterprises to gradually move to rural areas. According to certain statistics, by 1995, the proportion of overall industrial pollution accounted for by township and village enterprises had increased from 11% in the 1980s to 45%; in 2008, 66.37 percent of all industrial emissions came from polluting enterprises in rural areas. However, despite the continuous invasion of pollution into rural areas, China is characterized by urban-centrism in terms of the environment, legislation, and law enforcement [28]: the state, provinces, and municipalities focus on environmental remediation in urban areas, with cities allocating most of the resources, including financial support, on the formulation of policies and regulations. Consequently, the costs and risks of pollution emissions from enterprises in rural areas are lower than those in urban areas [29]. Profit-maximizing rural firms choose to generate as much pollution as possible until their marginal gains from emitting additional pollution decline to zero [30], rather than choosing green innovations with high inputs, high risks, and lagging returns. Even if technological reform and end-of-pipe treatment equipment are mature, rural enterprises prefer low-risk and “zero-cost” emissions theft and leakage in the absence of environmental monitoring networks. Therefore, industrial enterprises in rural areas not only have a higher pollution intensity per unit of output value than those in urban areas [2] but also have a lower environmental protection investment and environmental governance willingness than those in urban areas. It is worth pointing out that the characteristics of UUEI may also be heterogeneous across regions, given the significant differences in enterprise size, regional economic characteristics, and environmental regulations in China. In particular, the strength of enforcement of environmental regulations and the spatial allocation of environmental regulatory resources between urban and rural areas can significantly affect the urban–rural transfer and pollution characteristics of polluting enterprises within a region, and thus the characteristics of regional UUEI. Thus, this paper puts forward Hypothesis H1:
H1. 
There are significant differences in environmental investment between urban and rural enterprises, but there will be heterogeneity in the characteristics of environmental inequality between urban and rural areas, influenced by the enterprise size and regional characteristics.
In the absence of formal environmental regulations, how can the pollution emission behavior of rural industrial enterprises be effectively regulated to curb UUEI? In the current context, where formal environmental regulation resources remain scarce, public and media monitoring with lower regulatory costs has become important to compensate for the lack of formal environmental regulation. Long et al. [2] found that public environmental participation mitigates urban–rural differences in pollution intensity and compensates for the lack of formal environmental regulatory power in rural areas by influencing the government’s regulatory behavior. However, although public environmental participation can reduce the cost of pollution monitoring and improve the efficiency of government environmental enforcement, the role of public environmental participation in curbing UUEI is still limited, because of the government’s capacity and resource constraints for environmental enforcement in rural areas. On the other hand, both public environmental participation and media monitoring are “passive” regulatory approaches that focus on listed or heavily polluting enterprises. Moreover, the role of public environmental regulation is relatively limited for most private enterprises in rural areas because of the relatively low awareness of environmental protection in the countryside, among other factors. Therefore, the key to alleviating the inequality between urban and rural environments is a less costly and more proactive approach to environmental regulation.
Chinese enterprises have unique organizational governance characteristics. The CPC monitors and advises private enterprises on business decisions, compliance with the law, and workers’ rights and interests through the establishment of Party branches in the private sector. The existing literature has suggested that corporate party organizations make a great contribution to safeguarding workers’ welfare [20], providing employment protection [21,22], facilitating the participation of private firms in social governance [23], and boosting research and development (R&D) investment [24]. Enterprise party organizations play an important role in the implementation of central government policies by enterprises, and are an important hub for the synergy between the government and enterprises [31,32]. Moreover, the above studies provide some empirical evidence for the speculations in this paper. Regional enterprise grassroots party organizations may be able to improve corporate environmental governance behavior, thereby alleviating UUEI. Moreover, private entrepreneurs themselves are equally willing to establish party organizations in their firms [33,34]. This is because, as a natural political connection, party organizations can help private firms maintain good political relations with local governments [35]. This helps private firms to obtain bank loans; reduce cumbersome aspects of the communication process with the government [36,37]; and in this way, obtain higher corporate profits than non-Party private firms [38]. With the joint efforts of the CPC and private firms, 1.9 million private firms (68%) had established Party branches by the end of 2016 (Organization Department of the Central Committee of the Communist Party of China, 2017). If grassroots Party organization in enterprises can effectively alleviate UUEI, and if its role was not constrained by the limited resources of formal environmental regulation, grassroots Party organizations could become an effective path to improving the environment inequality, by providing limited resources of formal environmental regulation. This is especially the case in the context of the continuous promotion of the construction of grass-roots Party organizations in Chinese enterprises. This paper therefore proposes Hypothesis H2:
H2. 
The construction of regional grassroots party organizations can reduce the gap between the urban and rural environmental investments of industrial enterprises under resource constraints on formal environmental regulation, and alleviate UUEI.
Compared with “forced” governance under public participation and media monitoring, grassroots party organizations are more inclined to enhance the “initiative” of corporate environmental governance in areas where formal regulation is lacking. On the one hand, private enterprise party organizations are an important link between the Party, the government, and enterprises for collaborative environmental governance. The construction of regional grassroots party organizations can enhance the self-regulation and social responsibility of industrial enterprises through party supervision, thus checking and balancing corporate agency conflicts and enhancing the enterprises’ awareness regarding their social responsibility for environmental protection [39,40]. On the other hand, improved construction of regional grassroots party organizations can motivate enterprises to proactively cooperate with the government’s policies, including environmental governance and technological upgrading, and thus improve enterprises’ willingness to protect the environment. Thus, Hypothesis H3 is proposed.
H3. 
Regional grassroots party organization construction can reduce the difference in environmental investment between urban and rural enterprises and alleviate UUEI by increasing the degree of corporate social responsibility and policy implementation.

3. Research Design

3.1. Sample Selection and Data Sources

As of May 2023, the number of Chinese private enterprises exceeded 50 million, and the share of private enterprises among enterprises had increased to 92.4%, making them the major component of Chinese enterprises. Thus, the important role of private enterprises in UUEI in China is self-evident. To empirically test whether there is urban–rural environmental inequality in China in terms of investment in environmental emissions reduction and to explore the mechanism of the role of party organization embeddedness in mitigating urban–rural environmental inequality, this paper used data from the Chinese Private Enterprise Survey (CPES). The data were collected by the joint research team, which is composed of the United Front Work Department of the CPC Central Committee, the State Administration for Industry and Commerce, the China Federation of Industry and Commerce, and the China Association for the Study of Private Economy. The data survey has been conducted every two years since 1993. Currently, the data has been updated to 2016. However, due to the lack of enterprise location zip code and enterprise emission reduction investment data in the 2016 survey, this paper chose the 2006–2014 data as the research sample.
The 2006–2014 data survey used multi-stage sampling to identify a nationwide sample of private enterprises at a certain percentage (around 0.05%, with slight variations in the percentage each time), encompassing enterprises of different industries, sizes, and types in all 31 provinces, autonomous regions, and municipalities directly under the central government in mainland China. Samples with missing core information were eliminated. The locations of enterprises were parsed via postal codes to determine their urban and rural attributes. On that basis, this article classified the industries of the sampled enterprises according to China’s National Economic Industry Classification standards, taking more polluting industries as the research object, including mining, manufacturing, and the production and supply of electricity, gas, and water. In addition, to control for the influence of outliers on the regression results, after the continuous variables were reduced by the 1% and 99% quantiles, the final data containing 5892 enterprises in 24 provinces and cities across the country from 2006 to 2014 were obtained.
In addition, considering the impact of regional characteristics on urban–rural environmental inequality, this paper controlled for characteristics such as the level of regional economic development and the intensity of environmental regulation. The macrolevel data were mainly drawn from the China Statistical Yearbook, with missing data manually supplemented by data from government statistical bulletins. Then, this research matched the city-level data with the above firm-level data via firm location information.

3.2. Empirical Strategy

To test the above hypotheses and analyze urban–rural environmental inequality in terms of China’s environmental emission reduction investment, the empirical strategy of this paper was divided into three steps.
First, this paper established a baseline regression model to identify the factors affecting enterprises’ environmental abatement investment behavior. The model was used to test whether there are significant differences in environmental abatement investment between urban and rural enterprises to reveal urban–rural environmental inequality in terms of China’s environmental abatement investment. The model design is shown in Equation (1):
E P I i j t = β 0 + β 1 C i t y R u r a l i j t + β 2 E n t r e p r e n e u r i j t + β 3 E n t e r i j t + γ j + τ t + ε i j t
where E P I i j t   represents the environmental emission reduction investment of enterprise i in city j in year t, which is measured by the logarithm of the actual emission reduction investment of the enterprise. A higher EPI indicates that the enterprise pays more attention to environmental protection and its own environmental emission reduction behaviors in production and operation, whereas an enterprise with a lower EPI is regarded as unsustainable and will emit a large amount of pollution during the survival period, which will exacerbate the environmental pollution in the region. C i t y R u r a l i j t is a dummy variable that takes a value of 0 when enterprise i is located in urban areas and 1 otherwise. E n t r e p r e n e u r i j t is an entrepreneur-level control variable, and E n t e r i j t   is an enterprise-level control variable. In addition, region fixed effects ( γ j ) and year fixed effects ( τ t ) were added to the model design to reduce the estimation bias caused by region and year characteristics. ε i j t   is the error term. β 1   is the first core coefficient of interest in this paper; if it is significantly negative, then the investment in emissions reduction of rural enterprises is significantly lower than that in urban areas. This outcome implies that not only is there inequality between urban and rural environments in terms of investment in environmental mitigation but also that this inequality gap is exacerbated.
Second, the degree of embeddedness of regional party organizations in private enterprises was introduced into the estimation model as a moderating variable to assess its impact on UUEI and to reveal the moderating effect of party regulation as informal environmental regulation in UUEI. The model design is shown in Equation (2):
E P I i j t = β 0 + β 1 C i t y R u r a l i j t + β 2 P a r t y j t + β 3 C i t y R u r a l i j t × P a r t y j t + β 4 E n t r e p r e n e u r i j t + β 5 E n t e r p r i s e i j t + γ j + τ t + ε i j t
where P a r t y j t   is the degree of embeddedness of party organizations in private enterprises in city j, which is measured by the proportion of private enterprise party branches established in the region. Then, the interaction term C i t y R u r a l i j t × P a r t y j t     was added to the model. β 3   is the coefficient of interest in this paper, which reveals how the urban–rural environmental emission reduction investment differences are moderated by party regulation. If   β 1   is significantly negative and β 3   is positive, party organizations’ embeddedness in private enterprises can effectively narrow the differences in environmental emission reduction investment between urban and rural areas, and thus inhibit the degree of environmental inequality between urban and rural areas.
Finally, this paper proposed a mechanism of action framework to understand how regional party organizational embeddedness narrows environmental abatement investments by rural and urban firms. As proposed in Hypothesis 3, building regional grassroots party organizations can narrow the difference in environmental abatement investment between urban and rural firms by increasing the social responsibility and policy implementation of rural firms. This paper employed a stepwise regression model to test the above mechanism framework, as shown in Models (3) and (4):
R e s i j t ( I m p i j t ) = β 0 + β 1 C i t y R u r a l i j t + β 2 P a r t y j t + β 3 C i t y R u r a l i j t × P a r t y j t + β 4 C o n t r o l i j t + γ j + τ t + ε i j t
E P I i j t = β 0 + β 1 C i t y R u r a l i j t + β 2 R e s i j t ( I m p i j t ) + β 3 C i t y R u r a l i j t × R e s i j t ( I m p i j t ) + β 4 C o n t r o l i j t + γ j + τ t + ε i j t
where R e s i j t ( I m p i j t ) denotes the degree of firms’ perceptions of social responsibility and policy implementation, which are measured by a dummy variable for firms’ perceptions of social responsibility and the effect of innovation policy implementation (patent ownership), respectively. The other model designs are the same as those in Equation (1). Equation (3) examines the impact of regional grassroots party organization building on rural enterprises’ perception of social responsibility and the degree of policy implementation, and, on the basis of Equation (4), further tests the impact of the above mechanisms in reducing the difference between urban and rural enterprises’ investment in emission reduction, to reveal the moderating mechanism of building regional grassroots party organization in curbing the inequality between urban and rural environments.

3.3. Variable Definitions and Statistical Descriptions

3.3.1. Dependent Variable: Corporate Environmental Protection Investment (EPI)

The literature on UUEI has mainly focused on pollution emissions [2]. In this way, it reveals the current status of environmental inequality. However, less consideration has been given to how to correct environmental inequality [6]. Therefore, this paper explored urban–rural environmental inequality in the dimension of environmental investment from the perspective of corporate environmental investment, which not only enriches the understanding of urban–rural environmental inequality but is also crucial for alleviating urban–rural environmental inequality in pollution emissions. Accordingly, this paper adopted “firms’ pollution control investment in the current year” to measure the environmental protection investment behavior (EPI) of firms and reveals the environmental protection differences in China’s UUEI by examining the differences in environmental protection investment between urban and rural firms. In addition, considering that enterprise pollution control investment is significantly related to enterprise size [24], this paper further measured “enterprise pollution control investment in the current year/enterprise sales revenue” (EPI_out) to eliminate the estimation bias caused by the enterprise size effect [41].
By comparing the EPI data of urban and rural enterprises (Table 1), this paper found that the environmental governance investment of urban enterprises is significantly higher than that of rural enterprises. Moreover, the t test results were significant after controlling for the effect of enterprise size, which, to a certain extent, explains the existence of environmental governance differences between urban and rural areas, which will continue to exacerbate the existing UUEI.

3.3.2. Moderating Variable: Regional Grassroots Party Organization Construction

Grassroots party organizations are not only important driving forces that encourage enterprises to assume environmental responsibility but also important nodes for collaborative environmental governance between the government and enterprises [24]. To test whether the degree of embeddedness of regional party organizations can inhibit urban–rural environmental inequality, this paper adopted “the number of enterprises with regional party organizations/the number of regional private enterprises” ( P a r t y j t ) to measure the degree of embeddedness of regional party organizations.

3.3.3. Mediating Effect Variables

The above theoretical analysis indicates that the establishment of enterprise party organizations can increase enterprises’ awareness of social responsibility, policy implementation, and government resource support, which in turn can regulate their environmental investment behavior. In this paper, we asked the following question in the questionnaire: “What is your attitude toward nonpublic enterprises’ participation in social management?”. The answer to the question “How do you feel about the participation of nonpublic enterprises in social management?” was used to measure corporate social responsibility ( R e s i j t ). When an enterprise replied “should participate in social management, this is the social responsibility of the enterprise”, the dummy variable took a value of 1; otherwise, it took a value of 0. The variable “enterprise R&D expenses/sales revenue” was used to indicate the degree of importance that enterprises attached to innovation and the support of government resources. Considering that innovation is an important policy guideline of the country, this variable was used to measure the degree of policy implementation by enterprises ( I m p i j t ).

3.3.4. Control Variables

On the basis of existing studies [24,42,43,44], this paper introduced entrepreneur-level and firm-level variables, including entrepreneur age (Age), gender (Female), education (Edu), firm age (F_age), number of employees (Labor), innovative technology (Innovation), sales revenue (Output), net profit (Profit), fixed assets (Fixed), and Association of Industry and Commerce Social Networks (AIC). The measures and statistical descriptions of each of these variables are shown in Table 2.

4. Empirical Results and Analyses of UUEI

4.1. Baseline Results and Analyses

The willingness of urban and rural industrial enterprises to reduce emissions is more important for reducing UUEI than the difference in pollution intensity. This paper examined the current status and developmental trends of UUEI by testing whether there is a significant difference between the emission reduction behaviors of urban and rural industrial enterprises. This paper used the least squares (OLS) method to estimate Equation (1), with robust standard errors to eliminate heteroskedasticity and autocorrelation. The results of estimating the OLS model with time and area fixed effects are reported in Table 3. In Column (1), the firm location variable is introduced, and Columns (2) and (3) control for the effects of entrepreneur and firm-level control variables, respectively. To test the robustness of the regression results, this paper further measured the “pollution treatment input/sales revenue” of corporate environmental protection investment (EPI_2) to eliminate the effect of firm size on pollution reduction investment. The estimation results are in Columns (4)–(6).
The enterprise location variable in Column (1) of Table 3 is significantly negative at the 1% level, with a coefficient of −1.617. With further control for entrepreneurial and firm characteristics, the coefficients of the enterprise location variable were still significantly negative at the 1% level, at −1.727 and −1.243, respectively, which suggests that there was still a significant difference between urban and rural enterprises’ willingness to reduce emissions after controlling for other control variables and that rural areas are not only significantly more polluting than urban areas are [2] but also significantly less willing to take care of the environment without an external intervention. Industrial enterprises in rural areas not only have a significantly higher pollution intensity [2] but also have lower environmental investment than urban enterprises. Although rural industrial enterprises can stimulate rural economic growth [45], the polluting emissions they produce not only have a significant impact on impairing the ecological carrying capacity of rural areas [5], contaminating valuable land and water resources [46], but also cause cancer, respiratory system diseases, and other disease problems [47], impairing the physical health of rural residents [30]. It is worth mentioning that there are currently more than ten million environmentally unregulated rural enterprises in China, and without intervention, the trend in UUEI will intensify and become the primary problem affecting the sustainable development of rural economy and residents’ health.
In addition, higher-order theory suggests that managers’ values and perceptions are closely related to behavioral traits and can influence managers’ preferences and strategic decisions at work. The cognitive base and values of top managers affect the socially responsible behaviors of companies [48]. Strengthening environmental protection investment and reducing pollution emissions are social responsibilities that should be fulfilled by enterprises. CSR (corporate social responsibility) is a moral concept that requires enterprises to consider the interests of multiple stakeholders, such as the public and the government, in addition to the interests of shareholders in the course of business. Therefore, CSR is inevitably influenced by the values of decision-makers. The above estimation results revealed that entrepreneurs’ personal characteristics significantly affect their emission reduction investment behavior. Additionally, the coefficients of both gender and education were significantly negative, indicating that female and less educated rural entrepreneurs are more supportive of environmental investment behavior than male and more educated rural entrepreneurs. The findings of this paper suggest that female managers prefer environmental governance behaviors, which is consistent with the findings of Bhalotra and Clots-Figueras [49], Mavisakalyan [50], and others that an increase in the proportion of female managers leads to policy outputs that are more in line with the interests of human society. The estimation of educational attainment, however, was contrary to existing studies [51]. Specifically, increased educational attainment reduced the environmental governance behavior of rural firms. A possible reason for this finding is that more educated entrepreneurs are more aware of the shortcomings of the current environmental regulation in rural China and take advantage of them by reducing their investment in environmental abatement to maximize profits.
Among polluting firms, characteristics such as firm size, technological innovation, and social networks can also have a significant effect on firms’ emission reduction investment behavior [52]. The empirical results showed that when the number of workers, output value, and fixed assets of enterprises increased, enterprises paid more attention to their own environmental protection behaviors when the scale of business expanded, possibly because, even in rural areas, this expansion draws the attention of society and the government’s environmental protection efforts, and enterprises’ own sense of social responsibility becomes correspondingly stronger [2], which shifts the reason for enterprises’ environmental protection behaviors from passive to active, namely, to increase environmental governance investment. In addition, firms’ innovative technological behaviors and social networks increase their environmental investments. The empirical results provided some practical ideas for enhancing firms’ emission reduction behavior. Owing to the higher marginal abatement cost of pollution in rural areas, technological innovation has become an important way for enterprises to reduce emissions and secure profits; thus, the government should focus on encouraging and subsidizing enterprise innovation in rural areas to increase their willingness to innovate and realize the double dividend of reduced enterprise emissions and increased profits. Accordingly, it should also fully exploit the social networks of enterprises; encourage enterprises to participate in the Federation of Industry and Commerce, industry associations, and other organizations; and increase the positive influence of social organizations on the emission reduction behavior of enterprises.

4.2. Robustness Tests

4.2.1. Controlling for Area-Level Characteristic Variables and Other Policy Effects

Firms’ emission reduction investments are still affected by district-level characteristics, in addition to firm-level characteristics. To weaken the endogeneity triggered by missing important variables, this paper further controlled for regional-level characteristic variables on the basis of controlling for regional fixed effects in the previous section. These variables included the regional economic development level (P_GDP), regional environmental regulation intensity (Envir), regional urban–rural environmental regulation differences (Gap_envir), and a dummy variable for the two control areas (Control). In addition, the study used regional GDP per capita, the environmental regulation composite index [53] the ratio of urban and rural environmental protection agency personnel, and whether it is a two-control area dummy variable for measurement. The estimation results are shown in Columns (3) and (6) of Table 4, Panel A. The coefficients are −1.263 and −1.262, respectively, which are both significantly negative at the 1% level. After controlling for the regional level variables and the impact of the two control area policies, there was still a significant difference between urban and rural enterprises’ investment in environmental emission reductions, and the environmental inequality between urban and rural areas in China is manifested not only in the status quo difference in pollution intensity but also in the willingness to reduce emissions.

4.2.2. Estimated Model Robustness Test

Considering that some firms in the sample did not make environmental investments (N = 2328), there was a truncation phenomenon, and when OLS performed linear regression on the entire sample, its nonlinear disturbance term was included in the disturbance term, which may have introduced bias into the estimation results [54]. Therefore, in this paper, the Tobit model was used to estimate the robustness of Equation (1) via MLE to overcome the estimation bias that could be caused by restricted dependent variables and model design. The estimation results are shown in Table 4 Panel B. The results are shown in Table 4 Panel B, where Columns (1) and (4) are the MLE estimation results, Columns (2) and (5) are the marginal effects of y|y > 0, and Columns (3) and (6) are the marginal effects of overall y. The significance and sign of the estimation results did not change significantly from the benchmark results: the marginal effects of y|y > 0 and y were −0.291 and −0.179, respectively, indicating that the benchmark results were still robust to the significant difference in environmental protection investment between urban and rural firms after considering the characteristics of the data for the dependent variable and the bias in the model setup. Without a policy intervention, this trend of UUEI will intensify.

4.2.3. Considering the Effect of Sample Selection Bias

The results of the different model estimations described above indicated that the estimates were significantly robust. However, to further rule out the possible problems of model setting bias, multicollinearity, and the infeasibility of comparing the experimental and control groups [55], this paper adopted the PSM method in the causal inference analysis framework to conduct a robustness analysis of the UUEI problem. Compared with the traditional OLS estimation method, PSM can solve the sample self-selection bias problem very effectively, and there is no qualification of model form setting, parameters, and exogenous explanatory variables when dealing with endogeneity problems. First, the probability of a firm being located in a rural area was measured through probit regression using owner-, firm-, and region-level control variables. Second, different nearest neighbor matching methods were used to examine the impact of firm location on firms’ mitigation investments on the basis of propensity scores. Finally, sensitivity analyses were conducted to assess the robustness of the PSM estimation results. To ensure the quality of matching and the reliability of the estimation results, we conducted a common support and balanced trend test, which showed that the overlap of the range of propensity score intervals became larger after matching, and the balance assumption was satisfied after matching. The PSM estimation results are shown in Table 4, Panel C. After overcoming the effect of sample selection bias, the estimation results remained robust, and the emission reduction investment of firms in rural areas was significantly lower than that of firms in urban areas. Thus, the trend of worsening UUEI still existed.

4.2.4. Endogeneity Testing: Sensitivity Analysis

The presence of endogeneity problems may lead to biased results of benchmark estimation. The independent and dependent variables did not have an obvious causal relationship in terms of economic logic, so this paper focused on analyzing the endogeneity problems caused by omitting important variables. Therefore, this paper conducted a sensitivity test to verify the impact of omitted variables on the robustness of the estimation results.
The results of the sensitivity test are shown in Figure 1 and Figure 2. In particular, the contour line in Figure 1 shows the value of the regression coefficient β, and the red line represents β = 0. The four value points refer to the cases of no omitted variables, omitted variables with the same intensity of sex, omitted variables with two times the intensity of sex, and omitted variables with three times the intensity of sex. The values of the regression coefficients β for their corresponding econometric models are reported in parentheses for the four value points. All of them are less than 0, i.e., all four value points are located on the left side of the red line. Thus, even the inclusion of the sex three-fold strength omitted variable did not change the original estimated coefficient from negative to positive. In addition, the contour line in the lower panel is the t statistic, with the red line at 1.96 (95% confidence interval threshold). The four value points are the same as those in the upper panel and refer to the inclusion of the omitted variables for sex with 0 to 3 times the intensity. The t statistics of their corresponding measurement models are reported in parentheses for the four value points. The t statistic for the three value points that join sex with 0 to 3 times the intensity is less than 1.96 to the left of the red line. Therefore, even the inclusion of the omitted variable for sex three-fold intensity did not change the original estimated coefficient from significant to insignificant. The sensitivity test showed that even the presence of omitted variables did not significantly affect the robustness of the benchmark results; i.e., there is a significant difference in environmental protection investment between urban and rural enterprises, and there is a clear trend of UUEI.

4.2.5. Endogeneity Tests: Instrumental Variables Approach

In addition to sample self-selection bias and omission of important variables, the endogeneity of the party organization embeddedness level and firm location variables could still have introduced bias into the estimation results. Therefore, this paper chose the instrumental variable method to address the endogeneity problem due to mutual causation, omitted variables, and measurement error. Following He and Liu [56] and Xu and Yan [57], this paper chose “the historical imprint of communism in each region (the time interval between the time of liberation of each province and the date of the founding of New China)” as the instrumental variable to measure the embeddedness of regional grassroots party organizations. The stronger the historical imprint of communism in each locality, the stronger the local red cultural atmosphere, and the more likely the grassroots community is to actively engage in party building. Each province’s time of liberation is a historical event, which is exogenous to current firms’ environmental investment decisions and is equally exogenous.
In addition, the geographical location of firms may be endogenous, especially for polluting firms. The polluter’s paradise hypothesis suggests that polluting firms actively move to areas of low environmental regulatory intensity to avoid regulations in areas of high environmental regulatory intensity. Comparatively speaking, the intensity of environmental regulation is higher in cities than in rural areas, so private firms in cities invest more in the environment than those in rural areas. To lessen the impact of urban–rural transfer on the estimation results, due to the difference in environmental regulations between urban and rural areas, this paper excluded enterprises registered later than 2005. The reason for this exclusion was that China’s environmental protection efforts have made continuous progress since their inception in the 1970s, undergoing a process of starting from scratch, growing from a small size to a large size, and expanding continuously and developing gradually. Their history can be approximately divided into three stages and the three phases are as follows: Phase I (1973–1993): point source management, system construction; Phase II (1994–2004): watershed improvement, strengthened law enforcement; Phase III (2005–present): total prevention and control, optimized growth (https://www.gov.cn/guoqing/2012-04/10/content_2584066.htm, accessed on 1 August 2024). In December 2005, the State Council issued the “Decision on Strengthening Environmental Protection through the Implementation of the Scientific Outlook on Development”, which established the purpose of environmental protection as a people-oriented, environmental protection for the people and has become a programmatic document guiding the coordinated development of China’s economy and society and the environment. “The Outline of the Eleventh Five-Year Plan”, in response to the ever-increasing pressure on China’s resources and environment, put forward strategic tasks and specific measures to build a resource-saving and environmentally friendly society, and pollution prevention and control efforts were gradually shifting from the industrial sector to urban areas. Consequently, the differences in environmental regulations between urban and rural areas before 2005 were relatively small, and the impact of differences in environmental regulations and environmental protection investment between urban and rural areas on enterprises’ location decisions was relatively small, thus reducing the estimation bias caused by the endogeneity of enterprises’ geographic locations.
The results of the 2SLS regressions are shown in Table 5. Column (1) reports the results of the first-stage estimation, with significantly positive instrumental variable coefficients and an F statistic of 83.26, which is greater than the empirical critical value of 10, and the instrumental variables satisfy the correlation. In addition, the LM and Hansen J statistics are 58.37 and 1.279, respectively, rejecting the under-identified and weak instrumental variable hypotheses and satisfying the exogeneity requirement. (2) The second-stage estimation results include the coefficients of enterprise location, party organization embeddedness, and the interaction term, all of which are still significant. The estimation results showed that after controlling for the effects of variable endogeneity, the difference between urban and rural enterprises’ environmental investment was significant, and party organization embeddedness is still able to reduce the difference between urban and rural enterprises’ environmental investment, thus suppressing UUEI.

4.3. Heterogeneity Analysis

4.3.1. Heterogeneity of Enterprise Size

Owing to the significant differences in the development mode, R&D capability, competitive advantage, and social concerns of enterprises of different sizes [58], there may also have been heterogeneous differences in urban and rural emission reduction investment between large and small enterprises. To test the degree of heterogeneity in the differences in environmental protection investment between urban and rural enterprises, this paper divided the sample into two groups according to the median total assets of the enterprises: those with values higher than the median were defined as large-scale enterprises, and those with values lower than the median were defined as small-scale enterprises. The estimation results are presented in Columns (1) and (2) of Table 6. Both large and small firms had significantly negative urban and rural environmental investments at the 1 percent level, which suggests that the difference in environmental investments between urban and rural firms was generalized. However, there was also a significant difference in the urban–rural gap between large and small firms between groups, and the SUR between-group coefficient difference test was significant at the 5 percent level. This result suggests that the difference in abatement investment between large firms was more pronounced than that between small firms’ rural and urban areas. The current trend of pollution in rural areas was consistently highlighted, which aggravates industrial pollution in the countryside but also leads to a decline in the emission reduction investment of some large enterprises, further exacerbating pollution in rural areas and aggravating the inequality between urban and rural environments.

4.3.2. Regional Heterogeneity

Differences in regional locations and levels of economic development also have important impacts on the environmental investment behavior of enterprises. The eastern coastal region has a higher level of environmental regulation, scientific and technological innovation, and economic development, which can provide more incentives, technical support, and financial subsidies for enterprises to invest in emission reduction and thus may weaken the difference in emission reduction investment between urban and rural enterprises. To test the regional heterogeneity of environmental investment differences between urban and rural enterprises, this paper divided the sample into two groups according to the regional location of enterprises: economically developed areas (coastal areas) and economically backward areas (inland areas). The estimation results are listed in Columns (3)–(6) of Table 6. The results showed that the coefficients of the variables in different regions were significantly negative and that the coefficient test between groups was not significant. This finding suggests that there was no regional heterogeneity in the differences in environmental investment between urban and rural enterprises but rather a national generalization.

4.3.3. Heterogeneity of Environmental Regulations

The intensity of regional environmental regulation is closely related to the environmental abatement behavior of firms, and stricter environmental regulation forces regional firms to increase their environmental investments. In addition to the intensity of regional environmental regulation, urban–rural differences in regional environmental regulation have a greater impact on the environmental behavior of urban and rural enterprises. To test the impact of overall regional environmental regulation intensity and urban–rural environmental regulation differences on UUEI, this paper grouped the samples on the basis of regional environmental regulation intensity and urban–rural environmental regulation intensity differences. For high environmental regulation areas and low environmental regulation areas, differences in urban–rural environmental regulation in the urban–rural environment were high and low, respectively. The results of the group regression estimation are shown in Table 7. Columns (1) and (2) show the group estimation results of environmental regulation intensity. The urban–rural location variables were all significantly negative, indicating that the UUEI was universal. However, the SUR test results indicated a significant difference in the coefficients between the groups, i.e., the difference between urban and rural business investment in abatement was higher in high environmental regulation areas (−2.249), whereas it was lower in low environmental regulation areas (−0.668). Since the current environmental policy in China is still urban-centered, the higher the level of environmental regulation in regions with higher levels of environmental regulation, the greater the difference in the level of environmental regulation, leading to a more significant difference in environmental investment between urban and rural enterprises. Conversely, the lower the level of regional environmental regulation, the lower the difference between urban and rural environmental regulation. The level of environmental regulation faced by both urban and rural enterprises is low, and the difference in environmental investment between enterprises is even smaller.
This paper further explored the heterogeneity of the cross-grouping of environmental regulation levels and the urban–rural differences in environmental regulation. Columns (3) and (4) show the results of grouping different urban–rural differences in regulation at high levels of environmental regulation, with between-group coefficient tests showing no significant differences. Columns (5) and (6) show the grouping estimates at low levels of environmental regulation. Notably, at this point, there was no significant difference in corporate investment in emission reduction in regions with lower urban–rural environmental regulation differences (−0.569), whereas urban–rural corporate environmental investment in regions with higher urban–rural environmental regulation differences showed a significant difference (−0.682). Even in regions with relatively low levels of environmental regulation, higher urban–rural differences in environmental regulation can exacerbate differences between urban and rural enterprises’ investments in emission reduction. The results of the subgroup study suggested that urban-centered environmental regulatory policies, even if they are increasing, have a limited effect on reducing urban–rural environmental inequality. They can even exacerbate UUEI, forcing polluting firms to move to rural areas, thereby reducing firms’ environmental investments. Therefore, while continuing to increase the level of regional environmental regulation, the optimization of environmental regulation policy should focus on adjusting the internal structure, increasing the level of environmental regulation in rural areas, and narrowing the difference between urban and rural environmental regulation, to compel rural enterprises to increase their investment in pollution abatement and reduce UUEI.

5. Can Grassroots Party Alleviate Inequalities between Urban and Rural Environments?

5.1. Moderating Effect of Building Grassroots Party Organization

To test whether building grassroots party organization can reduce the difference between urban and rural firms’ abatement investment, this paper added building regional grassroots party organization ( P a r t y _ r ) and an interaction term with firms’ location (Loc) to the baseline model P a r t y _ r × L o c . The estimation results are shown in Table 8. The coefficient for urban and rural location (Loc) was still significantly negative, and the interaction term ( P a r t y _ r × L o c ) was significantly positive. The estimation results showed that building grassroots party organization can significantly inhibit the difference in abatement investment between urban and rural firms and thus reduce UUEI in the abatement dimension. Overall, building regional grassroots party organization can increase enterprises’ investment in emission reduction, especially for polluters in rural areas. The party organization embedded as informal self-regulation can regulate enterprises’ own regulatory behaviors and compensate for the lack of informal regulation in rural areas, to reduce enterprises’ pollution emissions, increase their emission reduction behaviors, and alleviate regional UUEI. The results of the baseline results and the results of the moderating effect supported Hypotheses 1 and 2; that is, there is environmental inequality between urban and rural areas, and building grassroots party organization can reduce this environmental inequality.

5.2. A Test of the Mechanism of the Moderating Effect Embedded in Building Regional Grassroots Party Organization

The previous section demonstrated the impact of grassroots party organizations on the pollution abatement investment of urban and rural enterprises, but the mechanism behind this effect was not clear. Theoretical analyses suggest that building grassroots party organization positively affects the social responsibility and policy implementation of regional firms and further reduces the difference in emission reduction investment between urban and rural firms. To test the potential moderating effect mechanism of building grassroots party organization, this paper first tested the impact of grassroots party organization on the degree of corporate social responsibility and policy implementation. On this basis, we verified whether CSR and policy implementation can reduce the differences in environmental investment between urban and rural enterprises and thus lessen the degree of environmental inequality between urban and rural areas in China. The results of the mechanism test are listed in Columns (2)–(5) of Table 7.
Columns (2) and (3) show the results of the CSR adjustment mechanism, and Columns (4) and (5) show the results of the policy implementation adjustment mechanism. The estimation results show that there was a significant difference in policy implementation between urban and rural enterprises (−0.360). Additionally, building grassroots party organization could effectively reduce the policy implementation gap between urban and rural enterprises (0.489) and indirectly reduce the difference in environmental investment between urban and rural areas (0.332). Notably, the CSR mechanism in the theoretical analysis was not empirically tested. Social responsibility did not differ significantly between urban and rural enterprises (−0.027), and the construction of regional grassroots party organizations did not significantly affect the difference in social responsibility between urban and rural areas (−0.526). These empirical estimation results indicated that regional grassroots party organization construction can effectively reduce the difference in environmental emission reduction investment between urban and rural enterprises and dampen the trend of UUEI. The main mechanism is reducing the degree of policy implementation between urban and rural enterprises and fully exploiting the role of “self-regulation” within enterprises.

6. Policy Implications: How to Alleviate Urban–Rural Environmental Inequalities?

The current structural, root, and trend pressures on ecological environmental protection in China have not been fundamentally alleviated. As a typical structural problem, urban–rural environmental inequality urgently needs to be considered and resolved by the government and society. Against the backdrop of weak rural formal regulation, the above findings have important policy implications for alleviating the growing UUEI, as well as for promoting sustainable development in rural areas.
First, the situation of rural non-face source pollution remains critical [59], especially the lack of adequate resources for environmental regulation. Policy-makers need to pay more attention to the worsening issue of UUEI in the context of the weak formal regulatory power in the countryside. The findings of this paper show that firms in rural areas not only pollute more intensively than those in urban areas [2] but also invest significantly less in environmental management than those in urban areas, and that UUEI is worsening. Therefore, the government must pay more attention to the supervision of polluting enterprises in rural areas, and environmental resources should be aimed toward rural areas to optimize the urban–rural structure of environmental regulation [60]. Specifically, the government should increase its efforts in rural environmental protection and realize a shift from “urban-centrism” to equal emphasis on both urban and rural areas in environmental protection and governance. National and local governments should increase investment in rural environmental protection, increase financial transfers, accelerate the construction of rural environmental protection infrastructure, and strengthen grass-roots environmental protection organizations and teams, to enhance rural pollution control and ecological environmental protection [61].
Second, informal regulatory forces should be seen as an important complement to formal regulation. Owing to the lack of resources for environmental regulation, policies should make full use of informal regulatory forces to regulate the environmental behaviors of rural enterprises. The empirical results showed that the embeddedness of party organizations as an informal regulatory force can effectively enhance policy implementation by rural firms, thereby alleviating UUEI. Specifically, the government should encourage rural enterprises to set up party organizations, accept party leadership, strictly abide by party discipline, and use party regulation to supplement current formal environmental regulation in rural areas. Specifically, for China, the CPC should broadly utilize self-regulation as a complement to informal environmental regulation, guiding enterprises in upgrading and adopting cleaner production, thereby reducing pollution emissions in areas where environmental regulation resources are scarce. It is worth noting that China’s unique approach to informal environmental regulation is less applicable to other countries, but still worthy of consideration. Existing studies have shown that informal environmental regulatory instruments such as labor unions [62,63,64], religions [65,66], and public environmental concern [2] can all have an impact on pollution emissions, with a dampening effect. Therefore, other countries can also focus on the role of informal environmental regulation such as labor unions, religions, or residents in regions with relatively few resources for formal environmental regulation, so as to achieve overall regional sustainable development.
Finally, firms’ innovative technological behavior and social networks increase their environmental investment. The empirical results provided some practical ideas for enhancing rural firms’ emission reduction behavior. Owing to the higher marginal abatement cost of pollution in rural areas, technological innovation has become an important way for enterprises to reduce emissions and secure profits, so the government should focus on encouraging and subsidizing enterprise innovation in rural areas, to increase their willingness to innovate and thus realize the double dividends of enterprise emission reduction and profits. At the same time, it should fully exploit the role of social networks of enterprises; encourage enterprises to participate in the Federation of Industry and Commerce, industry associations, and other organizations; and increase the positive influence of social organizations on the emission reduction behavior of enterprises [67].

7. Conclusions and Future Research

7.1. Conclusions

As the effectiveness of global environmental governance has been emphasized, the issue of environmental inequality in the process of environmental governance has continuously attracted the attention of scholars and governments [1]. However, existing studies mainly focused on intergroup and interregional environmental inequalities [5]. Research on the trends and mitigation strategies of environmental inequality between rural and urban areas within regions is still in its infancy. Especially in developing countries such as China, the accelerated industrialization of the countryside is accompanied by a lack of sufficient resources for environmental regulation [68]. This has led to increasingly serious environmental pollution in the countryside [69]. In this context, it is of great significance to reveal the characteristics of UUEI and explore solutions to alleviate urban–rural inequality under the constraints of formal environmental regulatory resources in the countryside, for the sustainable development of rural areas.
Based on an empirical analysis of the Chinese Private Enterprise Survey (CPES) 2006–2014, this research comprehensively examined the enterprise- and region-level factors influencing enterprises’ environmental investment behaviors. Based on this, China’s UUEI in the dimension of environmental investment was revealed. This study also explored the moderating role of party organization embeddedness as an informal regulation in mitigating UUEI under the limited formal environmental regulation in rural areas, which expanded the meaning of UUEI and suggests potential policy options. The main findings of this paper are as follows: (1) Polluting enterprises are widely distributed in rural areas. Pollution intensity in rural areas is higher than in urban areas, while investment in environmental management is significantly lower than in urban areas, which intensifies UUEI. (2) Differences in environmental investment behavior between urban and rural firms are heterogeneous in the dimensions of firm size and environmental regulation intensity. Rural–urban environmental inequality is more severe in regions with higher levels of environmental regulation than in regions with lower levels of environmental regulation. This implies that China’s urban-centered environmental regulation policy has exacerbated UUEI. (3) Regional party organization embeddedness can narrow the gap between urban and rural environmental investment by private enterprises and alleviate UUEI. This positive effect stems from the fact that the embeddedness of party organizations can enhance the degree of policy implementation by rural enterprises and give full play to the role of “self-regulation” within the enterprise.

7.2. Limitations and Future Research

Although this study explored a solution to alleviate UUEI under the conditions of the lack of formal environmental regulatory power in the countryside, i.e., the building of grassroots party organizations at the enterprise level, the study had some limitations. Like most research studies, this study was based on a specific economy. China has the political characteristic of “party unity”, and its large amount of grassroots party branches provide a natural informal regulatory force for rural environmental governance. This is an advantage that many other countries do not have. Therefore, the findings of this paper are applicable to developing countries such as North Korea, Vietnam, and Cuba, which have similar political environments. However, the findings of this paper can still provide policy implications for the governance of rural–urban environmental inequality in other countries, by focusing on the role of informal environmental regulation, such as public environmental concerns, labor unions, and even including religious beliefs. Future research could collect data from sample urban–rural environments in other countries to explore other effective programs to mitigate UUEI. Additionally, it may be valuable to explore the impact of different environmental policies (e.g., government-type and market-type environmental regulation) on UUEI and to improve existing environmental policies from an urban–rural environmental equity perspective.

Author Contributions

Conceptualization, H.Z. and Y.C.; methodology, H.Z.; software, H.Z. and J.Y.; data curation, H.Z. and Y.C.; writing—original draft preparation, H.Z. and Y.C.; writing—review and editing, H.Z. and Y.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Science Research Project of Hebei Education Department (Grant No. BJS2024043); the 2023 Baoding Philosophy and Social Sciences Planning Project (Grant No. 2023029); Hebei University Social Science Cultivation Project (Grant No. 2023HPY024).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available upon request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Sustainability 16 06713 g001
Figure 1. β contour plot.
Figure 1. β contour plot.
Sustainability 16 06713 g001
Sustainability 16 06713 g002
Figure 2. Contour plot of the T statistics.
Figure 2. Contour plot of the T statistics.
Sustainability 16 06713 g002
Table 1. Preliminary test of UUEI.
Table 1. Preliminary test of UUEI.
VariableFirm LocationObsMeanStd.95% Confidence Interval
EPICity23924.9960.116[4.768, 5.222]
Rural28643.0820.05[2.896, 3.267]
Diff 1.9130.18[3.806, 4.099]
T 12.931 ***
EPI_outCity2126−1.8000.115[−2.026, −1.575]
Rural2399−3.5660.102[−3.767, −3.365]
Diff 1.7650.154[−2.889, −2.584]
T 11.498 ***
Note: t values are in parentheses; *** indicates significance levels of 10%.
Table 2. Variable measures and statistical descriptions.
Table 2. Variable measures and statistical descriptions.
CategoryVariable NameMeasureMeanStd.Sample Size
Dependent VariableInvestment in environmental protectionPollution control investment of the enterprise in a year3.9535.4265256
Pollution treatment input of the enterprise in a year/sales revenue of the enterprise−2.7365.2294525
Independent variableUrban–rural locationRural enterprises take the value of 1, otherwise the value is 00.5580.4975892
Moderating variableDegree of embeddedness of regional party organizationsNumber of regional enterprises affiliated with the party organizations/number of regional private enterprises0.4200.1355892
Intermediary VariablesSocial ResponsibilityWhat is your attitude toward the participation of nonpublic enterprises in social management?0.5820.4933351
Policy ImplementationEnterprise R&D expenditure/sales revenue1.5682.0515349
Government SupportWhether the enterprise receives government support for technological reform0.1220.328794
Control VariablesAge of EntrepreneursAge value45.6598.5665820
GenderFemale = 1, vice versa = 00.1210.3265874
Educational attainmentPrimary school and below = 1; middle and high school = 2; bachelor’s degree = 3; graduate school and above = 42.5540.8005831
Enterprise ageAge 9.7985.2595674
Employed laborAnnual number of employed laborers4.1901.5115659
InnovationPatent ownership1.5682.0515349
Sales RevenueAnnual sales revenue6.9482.2794907
Net ProfitCorporate net profit4.0202.0824381
Fixed AssetsFixed assets6.0911.9483829
Social NetworkChamber of Commerce and Industry Associations0.6680.4715412
Table 3. Results of the baseline estimation.
Table 3. Results of the baseline estimation.
VariablesEnvironmental InvestmentEnvironmental Investment/Sales Revenue
(1)(2)(3)(4)(5)(6)
Urban and rural locations−1.617 ***−1.727 ***−1.243 ***−1.662 ***−1.603 ***−1.243 ***
(−10.37)(−10.77)(−5.77)(−10.19)(−9.55)(−5.77)
Gender −0.915 ***−0.887 *** −0.224−0.887 ***
(−4.39)(−2.78) (−0.98)(−2.78)
Age 0.051 ***−0.008 0.002−0.008
(5.85)(−0.59) (0.16)(−0.59)
Education level 0.528 ***−0.458 *** −0.177 *−0.458 ***
(5.47)(−3.26) (−1.76)(−3.26)
Age of enterprise 0.016 0.016
(0.69) (0.69)
Number of workers 0.702 *** 0.702 ***
(5.96) (5.96)
Technological Innovation 0.396 *** 0.396 ***
(6.54) (6.54)
Production value 0.082 −0.918 ***
(0.92) (−10.33)
Profit 0.121 0.121
(1.52) (1.52)
Fixed Assets 0.187** 0.187 **
(2.39) (2.39)
Industrial and commercial associations 0.559** 0.559 **
(2.32) (2.32)
Constant3.668 ***0.145−1.193−2.608 ***−2.335 ***−1.193
(15.09)(0.28)(−1.48)(−9.97)(−4.12)(−1.48)
Year fixed effectsYESYESYESYESYESYES
Region fixed effectsYESYESYESYESYESYES
Observations525651472618452544402618
R-squared0.0610.0760.1800.0520.0540.104
Note: t values or z values are in parentheses; ***, ** and * indicate significance levels of 1%, 5%, and 10%, respectively.
Table 4. Robustness test.
Table 4. Robustness test.
VariablesEnvironmental InvestmentEnvironmental Investment/Sales Revenue
(1)(2)(3)(4)(5)(6)
Panel A: Controlling for district-level variables and the impact of other policies
Urban–rural location −1.263 *** −1.262 ***
(−5.84) (−5.84)
Area Control Variables YES YES
Sample size 2618 2618
R-squared 0.181 0.105
Panel B: Tobit Estimated Model Test
Urban–rural location−0.305 **−0.276 **−0.291 **−0.262 ***−0.160 *−0.179 **
(−2.13)(−2.13)(−2.13)(−1.98)(−1.76)(−1.98)
LR chi2 (38)1518.20 *** 1328.12 ***
Pseudo R20.239 0.3042
Sample size111211121112111011101110
Panel C: Sample selection bias test
Before matching ATT
Urban–rural location −1.262 ***
(−5.83)
After matching
Urban–rural location −0.725 ***
(−2.27)
Firm Control VariablesYESYESYESYESYESYES
Year fixed effectsYESYESYESYESYESYES
Region fixed effectsYESYESYESYESYESYES
Note: t values or z values are in parentheses; ***, ** and * indicate significance levels of 1%, 5%, and 10%, respectively.
Table 5. Endogeneity test.
Table 5. Endogeneity test.
Variables2SLS
Grassroots Party Organization EmbeddingEnvironmental Investments
(1)(2)
Urban–rural location −2.073 ***
(−6.52)
Communist Historical Imprints0.349 **0.409 ***
(2.07)(2.93)
Urban–rural location × Communist Historical Imprints 0.607 *
(1.79)
Pseudo R2/F83.2638.66
Sample size17841784
Firm control variablesYESYES
City-level control variablesYESYES
Year fixed effectsYESYES
Area fixed effectsYESYES
Note: t values are in parentheses; ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively.
Table 6. Heterogeneity test results (I).
Table 6. Heterogeneity test results (I).
VariablesEnterprise SizeLevel of Regional Economic DevelopmentLocation
(1)(2)(3)(4)(5)(6)
Small BusinessBig BusinessEconomically BackwardEconomically DevelopedCoastalInland
Urban–rural location−0.688 **−1.658 ***−1.271 ***−1.249 ***−1.196 ***−1.408 ***
(−2.52)(−4.93)(−4.20)(−3.79)(−4.79)(−3.28)
Control VariablesYESYESYESYESYESYES
Year fixed effectsYESYESYESYESYESYES
Area Fixed EffectsYESYESYESYESYESYES
Observations12311387128413341987631
R-squared0.1450.1060.1300.1080.0990.140
SUEST5.17 **0.9610.08
Note: t values or z values are in parentheses; *** and ** indicate significance levels of 1% and 5%, respectively.
Table 7. Heterogeneity test results (II).
Table 7. Heterogeneity test results (II).
VariablesEnvironmental RegulationHigh Environmental RegulationLow Environmental Regulation Variable
(1)(2)(3)(4)(5)(6)
LowHighLow VarianceHigh VarianceLow VarianceHigh Variance
Urban–rural Location−0.668 **−2.249 ***−1.791 ***−2.374 ***−0.569−0.682 *
(−2.46)(−5.82)(−2.81)(−4.59)(−1.48)(−1.73)
Control VariablesYESYESYESYESYESYES
Year Fixed EffectsYESYESYESYESYESYES
Area Fixed EffectsYESYESYESYESYESYES
Observations16041014630384813791
R-squared0.1170.1310.1410.1710.1280.134
SUEST11.57 ***0.638.42 ***
Note: t values or z values are in parentheses; ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively.
Table 8. Moderating effect test results.
Table 8. Moderating effect test results.
(1)(2)(3)(4)(5)
E P I _ o u t R e s E P I _ o u t I m p E P I _ o u t
R e s ( I m p ) 0.167 0.332 ***
(0.61) (7.36)
C i t y R u r a l −1.335 ***−0.027 −0.360 ***
(−4.96)(−0.35) (−3.04)
P a r t y 1.7351.328 ** 2.521 ***
(1.01)(2.26) (3.52)
C i t y R u r a l ∗ P a r t y 4.119 *−0.526 0.489 *
(1.90)(−0.94) (1.87)
Control VariablesYESYESYESYESYES
Year Fixed EffectsYESYESYESYESYES
Area Fixed EffectsYESYESYESYESYES
Observations15483287147237943600
R-squared0.0510.0550.0350.0890.175
Note: t values or z values are in parentheses; ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively.
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Zhang, H.; Yu, J.; Chen, Y. Party Branch Embeddedness and Urban–Rural Environmental Inequality: Self-Regulation or Pollution Shelter? Sustainability 2024, 16, 6713. https://doi.org/10.3390/su16166713

AMA Style

Zhang H, Yu J, Chen Y. Party Branch Embeddedness and Urban–Rural Environmental Inequality: Self-Regulation or Pollution Shelter? Sustainability. 2024; 16(16):6713. https://doi.org/10.3390/su16166713

Chicago/Turabian Style

Zhang, Hongzhen, Jingyang Yu, and Yakun Chen. 2024. "Party Branch Embeddedness and Urban–Rural Environmental Inequality: Self-Regulation or Pollution Shelter?" Sustainability 16, no. 16: 6713. https://doi.org/10.3390/su16166713

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