Coupling and coordinated development of environmental regulation and the upgrading of industrial structure: Evidence from China's 10 major urban agglomerations

Zheng, Xiaozhou; Liu, Renming; Wang, Huiping Article Coupling and coordinated development of environmental regulation and the upgrading of industrial structure: Evidence from China's 10 major urban agglomerations Economies Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Zheng, Xiaozhou; Liu, Renming; Wang, Huiping (2024) : Coupling and coordinated development of environmental regulation and the upgrading of industrial structure: Evidence from China's 10 major urban agglomerations, Economies, ISSN 2227-7099, MDPI, Basel, Vol. 12, Iss. 9, pp. 1-17, https://doi.org/10.3390/economies12090231 This Version is available at: https://hdl.handle.net/10419/329157 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Citation: Zheng, Xiaozhou, Renming Liu, and Huiping Wang. 2024. Coupling and Coordinated Development of Environmental Regulation and the Upgrading of Industrial Structure: Evidence from China’s 10 Major Urban Agglomerations. Economies 12: 231. https://doi.org/10.3390/ economies12090231 Academic Editors: Francesco Sica, Elena Di Pirro, Maria Rosaria Sessa, Francesco Tajani, Maria Rosaria Guarini, Alessio Russo and Debora Anelli Received: 23 July 2024 Revised: 25 August 2024 Accepted: 27 August 2024 Published: 29 August 2024 Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). economies Article Coupling and Coordinated Development of Environmental Regulation and the Upgrading of Industrial Structure: Evidence from China’s 10 Major Urban Agglomerations Xiaozhou Zheng 1,*, Renming Liu 2and Huiping Wang 1 1Research Center of Resource Environment and Regional Economy, Xi’an University of Finance and Economics, Xi’an 710100, China; [email protected] 2School of Economics, Xi’an University of Finance and Economics, Xi’an 710100, China; [email protected] *Correspondence: [email protected] Abstract: Exploring the coupling and coordinated development of formal and informal environmental regulation, as well as their impact on the upgrading of the industrial structure of urban agglomerations, represents a new breakthrough. The comprehensive index of formal environmental regulation, informal environmental regulation, and industrial structure upgrading is calculated using the entropy method based on sample data from 127 cities in China’s ten major urban agglomerations between 2003 and 2019. The characteristics of the coupling and coordinated development between formal and informal environmental regulation in these urban agglomerations are examined using a coupling coordination degree model. Furthermore, the effects of the coupling and coordinated development of formal and informal environmental regulation on the industrial structure upgrading in urban agglomerations are analyzed through fixed-effect and threshold regression models. The findings demonstrate that although the development of urban agglomerations remains unbalanced, the overall coupling coordination degree between formal and informal environmental regulation is increasing. Generally, the ten major urban agglomerations have transitioned from a state of reluctance coordination to primary coordination. The Pearl River Delta urban agglomerations have progressed from reluctance coordination to middle coordination, while the Yangtze River Delta, Shandong Peninsula, Central Plains, and Beijing–Tianjin–Hebei urban agglomerations have advanced from reluctance coordination to primary coordination. The remaining five urban agglomerations have shifted from near disorder to reluctance coordination. The coupling and coordinated development of formal and informal environmental regulation significantly promote the upgrading of the industrial structure in both overall and grouped samples of urban agglomerations, and the higher the degree of coupling coordination, the greater the promoting effect. Moreover, when informal environmental regulation is considered as a threshold variable, the coupling coordination degree exhibits a brokenline relationship with the industrial structure upgrading in urban agglomerations. Currently, the intensity of informal environmental regulations is relatively reasonable in China’s ten major urban agglomerations, and the coordinated development of formal and informal environmental regulations has an impact on the industrial structure of urban agglomerations. Finally, this paper proposes corresponding suggestions encompassing the construction of an environmental regulation policy system, differentiated industrial policy, and the coordinated promotion of various policies. Keywords: environmental regulation; coupling and coordinated development; upgrading of industrial structure; urban agglomerations; panel threshold regression models; panel data 1. Introduction Although China’s economy developed rapidly in recent decades, the booming economy has also given rise to severe environmental problems (Yu 2014). The United Nations’ Department of Economic and Social Affairs has established 17 sustainable development Economies 2024,12, 231. https://doi.org/10.3390/economies12090231 https://www.mdpi.com/journal/economies Economies 2024,12, 231 2 of 17 goals, including “Make cities and human settlements inclusive, safe, resilient and sustainable”, which prioritize the need to pay attention to environmental problems resulting from the process of urbanization (United Nations 2020). As the most populous nation and a global economic powerhouse, China accounts for approximately 30% of worldwide carbon emissions and drives 73% of global emission growth (Shan et al. 2018). Consequently, China’s advancements in environmental regulation play a pivotal role in shaping the global trajectory towards achieving carbon neutrality and peaking carbon emissions targets, underscoring its critical influence on international climate outcomes. However, compared to its geographical neighbor, Japan, China relies more on coal, which signifies that China may face a more difficult predicament in reducing carbon emissions (Ouyang and Lin 2017). Also, Yoon et al. (2020) pointed out that China is the net exporter of embodied carbon emissions to South Korea and Japan, which causes significant carbon leakage in China. Nevertheless, such a coal-dominated energy structure and international carbon leakage may also mean greater potential for further improvement. Thus, an effective environmental regulation system is desperately needed in China. Research has demonstrated that the development of an appropriate environmental regulation strategy can effectively constrain corporate conduct, facilitate the transformation of enterprise production methods, and drive the advancement of industrial structure (Chong et al. 2017;Du et al. 2021). In alignment with the 2025 Paris Agreement, China has committed to peaking carbon emissions by 2030, a pledge that necessitates further intensification of its environmental regulations. Presently, China’s environmental regulation encompasses formal regulations, predominantly enforced by the government through coercive measures, and informal regulations led by the public, media, and environmental groups (Pargal and Wheeler 1996). These two forms of environmental regulation can, to a certain extent, complement each other and generate synergistic effects. Delving into further detail, on the one hand, the dissemination of government environmental information and the imposition of penalties for environmental pollution serve to engage the public, media, and environmental groups in environmental protection efforts. On the other hand, the environmental protection demands voiced by the public, the exposure of pollution activities by the media, negotiations between environmental organizations and businesses, and government actions all function as oversight mechanisms for corporate production behavior and government enforcement actions. Consequently, they play a pivotal role in promoting the effective implementation of formal environmental regulatory policies. Thus, can the coupling and coordinated development of formal and informal environmental regulation contribute to the upgrading of the industrial structure? This is a question worth considering. Additionally, De Goei et al. (2010) mentioned that the traditional central place conceptualization has already been outdated. Furthermore, in recent decades, urban agglomerations have emerged as one of the most important economic development carriers (Fang and Yu 2017), and have played an increasingly significant role in regional economic development (Yin et al. 2022a), which prioritizes the need to focus on urban agglomeration. Corresponding with the gradual revolution of “new-type urbanization” and “strategy for coordinated regional development”, the construct of urban agglomeration becomes a crucial opportunity to boost Chinese high-quality economic development, and structure a “dual circulation” development pattern, which aims to make domestic and foreign markets boost each other, with the domestic market as the mainstay. Research indicates that ecological civilization serves as a crucial driving force for the development of new-style urbanization (Yu 2021). Due to the comprehensive and complex nature of urban agglomerations, the implementation of the “new urbanization” strategy and regional development strategy has inevitably led to the emergence of complex and challenging issues that were not present in traditional single-city contexts. These issues include a range of environmental problems (Grimm et al. 2008), such as the urban heat island effect (Thompson and Perry 1997), and environmental degradation (Hashmi et al. 2021). In terms of industry, the main concerns are the demographic transition (Sato and Yamamoto 2005) and structural changes in industries Economies 2024,12, 231 3 of 17 resulting from the of industries concentration from peripheral cities to central cities (Lu and Tao 2009). It is evident that the environmental and industrial structural issues of urban agglomerations are more intricate and representative. Furthermore, urban agglomerations play a leading role in China’s economic, technological, and cultural development, serving as an important platform for China to participate in international market competition. The resolution of environmental pollution and disruption in urban agglomerations, as well as the upgrading of industrial structures, are crucial for enhancing the overall competitiveness of these agglomerations, which in turn affects China’s international status and influence. The remainder of this paper is organized as follows. The second part is a literature review. The third part introduces the methodology. The fourth part analyzes the results of coupling and coordination degree. The fifth part discusses the results of the empirical studies. The final part concludes this study and proposes corresponding policy suggestions. 2. Literature Review Based on research conducted in the academic field, there is a substantial body of literature on the environmental regulations and industrial structure upgrading, primarily focusing on the following aspects: One aspect is considering environmental regulations as a whole and examining their impact on industrial structure upgrading. Some authors indicate that strength environmental regulations can lead to an increase in the proportion of the service industry and the manufacturing industry (Chong et al. 2017). Yin et al. (2022b) argue that the impact of environmental regulation on industrial upgrading exhibits a U-shaped curve. Hu et al. (2020), using the four provinces of the Yangtze River Economic Belt (Hunan, Hubei, Jiangxi, and Anhui) as their research samples, found that in the process of environmental regulation affecting the upgrading of industrial structure, there are both substitution effects and complementary effects. Moreover, the substitution effects are greater than the complementary effects. Environmental regulation has a positive impact on the optimization and upgrading of the industrial structure in second-tier cities, third-tier cities, and cities below the third tier, but the degree of impact varies. Research from Cohen and Tubb (2018) shows that many existing papers are based on the Porter hypothesis, whereby environmental regulation can contribute to innovation. Wu and Liu (2021) indicate that innovation has a significant positive spatial spillover effect on the upgrading of industrial structure. Furthermore, previous research also argues that technological innovation has a significant mediation effect on industrial structure upgrading in some cities in China (Shao et al. 2021). The level of industrial structure optimization may also influence the effectiveness of environmental regulation. For example, based on varying levels of industrial structure optimization, Chen et al. (2019) examined the impact of environmental regulations on carbon dioxide emissions, and found that environmental regulations can contribute to carbon dioxide emissions if the level of industrial structural optimization is low. However, when the level of industrial structural optimization is high, such scenarios are inversed, and environmental regulations have a significant inhibitory effect on carbon dioxide emissions. The second aspect is to categorize environmental regulations and examine their impact on industrial structure upgrading. Many existing studies classify environmental regulation into two types: formal environmental regulation and informal environmental regulation (Cole et al. 2005;Pargal et al. 1997;Ren et al. 2023). Some scholars use these two types of environmental regulations to, respectively, examine their effects on industrial structure upgrading, leading to different conclusions. Existing research indicates that informal environmental regulation can boost the upgrading of industrial structure and such a relationship has regional heterogeneity (Chen et al. 2022). Research from Yuan and Xie (2014) indicates that formal and informal environmental regulation have different mechanisms for influencing industrial restructuring. Li and Liu (2023) also argue that formal and informal environmental regulations have different impact pathways: formal environmental regulations boost economic development through the rationalization of Economies 2024,12, 231 4 of 17 industrial structure (RIS), while informal environmental regulations promote economic development through upgrading industry structure. Some other scholars conduct a more detailed categorization of environmental regulations. For instance, Chen et al. (2020) classify environmental regulation into three types: command and control, market incentive, and voluntary participation, aiming to show that environmental regulation can spur the upgrading of industrial structure, thus promoting high-quality economic development. Furthermore, some authors also suggest that market incentive environmental regulation plays a more important role in the upgrading of industrial structure than the other two types of environmental regulation (Wang et al. 2022). Considering that, compared to other developed countries in Asia like Japan, which has a relatively long history of encouraging individuals, environmental groups, and NGOs to participate in environmental regulation (Moshkal et al. 2023), China lags behind in informal environmental regulation compared to Japan (Lin et al. 2011). Additionally, in policy making, informal environmental regulation has not received sufficient attention in addressing non-compliant behaviors beyond the scope of formal environmental regulation (Shen et al. 2023). Given this situation, there is a need to develop a coupled and coordinated measurement of formal and informal environmental regulations to enable a broader scientific understanding of China’s environmental regulation process and its impact on the economy. Based on existing the literature, many studies focus solely on the linear relationship between environmental regulation and the upgrading of industrial structure (Lin and Xie 2023;Song et al. 2021). However, there could be a non-linear relationship between these two variables (Yang et al. 2021). Additionally, many existing studies adopt a relatively narrow approach to measure industrial structure upgrading. For example, many studies use the share of secondary or tertiary industries to represent industrial structure upgrading (Dong et al. 2020;Hao et al. 2020), but this does not fully capture the overall goal of upgrading, which is to achieve both rationalization and optimization of the industrial structure (Chen et al. 2019). Each dimension reflects a different aspect of industrial structure upgrading: rationalization focuses on internal coordination, balance, and resource allocation efficiency, while optimization directly reflects the outcomes of upgrading, indicating whether the economy is advancing to a higher level. Therefore, both dimensions are essential for a comprehensive evaluation of industrial structure upgrading. Overall, the literature on environmental regulations and industrial structure upgrading is quite ample, but there is still room for further research. Firstly, most studies are conducted at the provincial, regional level, or international level, little research focuses on the perspective of urban agglomerations. This paper takes the ten major urban agglomerations in China as research samples, carefully considering the economic cluster development characteristics in these cities, which offers a fresh research perspective. Secondly, the existing literature mainly focuses on the overall impact of environmental regulations and the effects of different types of environmental regulations on industrial structure upgrading. There is limited research on the coupling and coordinated development of formal and informal environmental regulations and its impact on industrial structure upgrading. This paper, based on the analysis of the characteristics of the coupling and coordinated development of formal and informal environmental regulations, employs fixed-effects models and threshold regression models to empirically analyze the impact of the coupling and coordination relationship between these two kinds of environmental regulation on industrial structure upgrading, which brings novelty to the field and emphasizes the need to further develop both of them, especially informal environmental regulation. Thirdly, the measurement of environmental regulation indicators is currently relatively limited. This paper, based on data availability, selects six micro-level indicators to measure formal environmental regulations and two micro-level indicators to measure informal environmental regulations, providing a more comprehensive and scientifically grounded approach. Based on this, this paper selects the ten major urban agglomerations in China, which were among the first to develop and have a certain scale. These urban agglomerations include the Pearl River Delta, the Yangtze River Delta, Beijing–Tianjin–Hebei, Shandong Peninsula, West Economies 2024,12, 231 5 of 17 Taiwan Strait, the Middle Reaches of the Yangtze River, the Central Plains, the Central and Southern Liaoning, Chengdu–Chongqing, and Guanzhong Plain as research samples. Table A1 details the cities included within these urban agglomerations. Finally, this paper focuses on exploring the non-linear relationship between the coupling and coordination degree of formal and informal environmental regulations and its impact on the upgrading of industrial structure in urban agglomerations. This paper aims to investigate the impact of the coupling and coordinated development of formal and informal environmental regulations on industrial structure upgrading in these urban agglomerations, with the goal of providing insights and recommendations for achieving “peak carbon” and “carbon neutrality” and promoting high-quality development. 3. Methodology 3.1. Explanation of Methodology Steps The methodology contains 8 subsections, and the following 7 sections are organized as shown in Table 1. Table 1. Explanation of methodology steps. Step Explanation Method Establishment of the Evaluation System First, 6 variables and 2 variables were chosen to establish comprehensive indices for formal and informal environmental regulations, respectively. Next, the calculation of complex indices, including the rationalization of industrial structure and the optimization of industrial structure, was introduced. Finally, the process of the entropy method was described. For the comprehensive indices system, please refer to Section 3.2 For an explanation of the indicators, please refer to Section 3.3 For the entropy method, please refer to Section 3.4 Calculation of Coupling and Coordination Degree First, the coupling degree is calculated, followed by the calculation of the coupling coordination degree. Then, the classification criteria for the coupling coordination degree are established. Coupling and coordination model (please refer to Sections 3.5 and 3.6) Modelling First, the baseline regression model is constructed. Then, the panel threshold regression model is constructed. Fixed-effect model and panel threshold model (please refer to Section 3.7) 3.2. Measurement of Environmental Regulation and the Industrial Structure Upgrading Environmental regulation includes two dimensions: formal environmental regulation (FER) and informal environmental regulation (IER). Due to the availability of data, a formal environmental regulation index system comprising six micro-indicators and an informal environmental regulation index system comprising two micro-indicators are constructed. Following the research by Gan et al. (2011), we construct an industrial structure upgrading evaluation system comprising two dimensions: rationalization of industrial structure (RIS) and optimization of industrial structure (OIS). The indicator evaluation system is shown in Table 2. The data used mainly come from the “China City Statistical Yearbook”, “China Statistical Yearbook on Environment”, “China Statistical Yearbook for Regional Economy”, “Statistical Communiquéof the PRC National Economic and Social Development” as well as World Bank Open Data. Economies 2024,12, 231 6 of 17 Table 2. The evaluation system for FER,IERs, and IS. Project Layer Index Layer Unit Impact Formal environmental regulation (FER) Industrial wastewater discharge (x1) metric tons negative Industrial sulfur dioxide emissions (x2) metric tons negative Industrial particulate matter emissions (x3) metric tons negative Harmless disposal rate of household waste (x4) % positive Comprehensive utilization rate of general industrial solid waste (x5) % positive Centralized treatment rate of sewage treatment plant (x6) % positive Informal environmental regulation (IER) Educational attainment (x7) / positive Population density (x8) person/km2positive Upgrading of industrial structure (IS) Rationalization of industrial structure (RIS) / positive Optimization of industrial structure (OIS) / positive 3.3. Indicator Explanation (1) Informal environmental regulation (IER) Educational attainment (x7) = Number of students in regular higher education institutions/Total population at year-end Population density (x8) = Land area of administrative zone/Total population at year-end All data used to calculate these 2 micro-indicators of informal environmental regulation are sourced from the “China City Statistical Yearbook”. (2) Rationalization of industrial structure (RIS) Based on the research by Shen et al. (2020), the calculation formula is as follows: RIS =∑i(Ai×Fi) q∑iA2 i×q∑iF2 i (1) Note that: Airepresents the proportion of the real added value of the ith industry in real GDP. Fi represents the proportion of the employed persons in the ith industry in the total employed persons. (3) Optimization of industrial structure (OIS) Based on the previous research, the calculation process is divided into three steps (Fu 2010): The first step is to use the proportion of the added value of each industry to the regional GDP as three components of a spatial vector, thereby forming a set of threedimensional vectors. X0=(x1,0,x2,0,x3,0)(2) The second step is to separately calculate the angles θ1 , θ2 , and θ3 between the vectors X1=(1, 0, 0) , X2=(0, 1, 0) , and X3=(0, 0, 1) as they are arranged from lower to higher levels within the industry. θj= 3 ∑ k=1 k ∑ j=1 arccos     ∑3 i=1xi,j×xi,0 ∑3 i=1x2 i,j1 2×∑3 i=1x2 i,01 2     ,j=1, 2, 3 (3) The third step is to calculate the optimization of industrial structure (OIS) OIS =∑3 k=1∑k j=1θj(4) (4) Control variables Based on existing research, the control variables that primarily influence the upgrading of the industrial structure include the level of economic development, the level of technolog- Economies 2024,12, 231 7 of 17 ical innovation, the level of information development, the level of foreign direct investment, and the level of fixed-asset investment. These variables are, respectively, measured as follows: per capita real gross domestic product (agdp), the number of patents (lnpatent) (treated by natural logarithm), the ratio of employees in the information transmission, computer services, and the software industry to the total population at the end of the year (inform), the ratio of actual foreign direct investment to the regional real GDP (fdi), and the ratio of the total actual fixed-asset investment in the whole society to the corresponding regional real GDP (fixasset). 3.4. The Measurement of Formal, Informal Environmental Regulation and the Upgrading of Industrial Structure Comprehensive Index Drawing from the research conducted by Wang et al. (2021), we illustrate the process of calculating all three comprehensive indices (FER,IER,IS) using the formal environmental regulation comprehensive index as an example. To begin, we apply standardization to both positive and negative indicators, with the respective formulas as follows: x0 ηij =xηij −xmin j xmax j−xmin j +0.01 (5) x0 ηij =xmax j−xηij xmax j−xmin j +0.01 (6) In the formula, x0 ηij represents the standardized value of the index jfor the iurban agglomeration in η year, xηij represents the original value of the index jfor the iurban agglomeration in η year, xmax j and xmin j , respectively, represent the maximum and minimum values of the index j. To prevent zero values, the standardized results were shifted by 0.01. Then, using the objective weighting method with the information entropy approach to weight the indicators. Denote the weights for the indices of the iurban agglomeration in year ηas wηij. Finally, the comprehensive environmental regulation index Zηi for the iurban agglomeration in year ηis calculated. Zηi=∑ j wηij ×x0 ηij (7) Note that: ∑ j wηij =1 (8) 3.5. The Measurement of Coupling and Coordination Degree (CCD) Referring to the research by Deng et al. (2022), we use 2 steps to calculate the coupling and coordination degree of formal and informal environmental regulation. Firstly, calculate the coupling degree: c=sFER ×IER FER+IER 2 (9) Secondly, calculate the coupling and coordination degree: CCD =qc×(0.5 ×FER +0.5 ×IER)(10) In the formula, crepresents coupling degree, CCD represents coupling and coordination degree, FER stands for the comprehensive index of formal environmental regulations, and IER represents the comprehensive index of informal environmental regulations. Setting the weights for FER and IER to be equal at 0.5 indicates that formal environmental regulations and informal environmental regulations hold an equal level of importance. Economies 2024,12, 231 8 of 17 3.6. Classification Criterion of Coupling and Coordination Degree Based on the existing classification standards and the calculated results of coupling and coordination degree (Shang and Liu 2021), the coupling and coordination levels are divided into ten grades (Table 3). Table 3. Classification criterion of coupling and coordination degree. Range Stage Range Stage [0.000–0.100] Extreme disorder (0.500–0.600] Reluctance coordination (0.100–0.200] Serious disorder (0.600–0.700] Primary coordination (0.200–0.300] Moderate disorder (0.700–0.800] Middle coordination (0.300–0.400] Light disorder (0.800–0.900] Well coordination (0.400–0.500] Near disorder (0.900–1.000] High coordination 3.7. Modeling 3.7.1. The Construction of Baseline Regression Model According to various research findings and preceding text, environmental regulations can influence industrial structure. Environmental regulations can be divided into two dimensions: FER (formal environmental regulations) and IER (informal environmental regulations). FER and IER also have a coupled and coordinated relationship. Therefore, the coupled and coordinated development of formal environmental regulations and informal environmental regulations may have an impact on the upgrading of the industrial structure of urban agglomerations. Thus, this paper constructs model (7) to empirically verify the impact of the coupled and coordinated development of formal environmental regulations and informal environmental regulations on the upgrading of the industrial structure of urban agglomerations. The model is set as follows: structureit =α0+α1dit +α2agdpit +α3lnpatentit +α4in f ormit +α5f diit +α6f ixassetit +εit (11) Note that, iand t, respectively, represent individual cities (i= 1, 2, . . . , 127) and time (t = 2003, 2004, . . . 2019), εas error terms. 3.7.2. The Construction of the Panel Threshold Regression Model The previous analysis indicates that the coordinated development of FER and IER significantly promotes the upgrading of the industrial structure in urban agglomerations. Hence, whether there is a certain non-linear relationship between the level of CCD and the upgrading of the industrial structure in urban agglomerations within different ranges of FER and IER is worthwhile to be discussed. Based on this, two panel threshold regression models are constructed, with FER and IER as threshold variables, and the level of CCD as the core explanatory variable, to verify the non-linear impact of CCD on the upgrading of the industrial structure in urban agglomerations. The two models are set as follows: structureit =λ0+λ1ccdit ×I(FERit ≤γ)+λ2dit ×I(FERit >γ)+λ3agdpit +λ4lnpatentit +λ5in f ormit +λ6f diit +λ7f ixassetit +εit (12) structureit =λ0+λ1ccdit ×I(IERit ≤η)+λ2dit ×I(IERit >η)+λ3agdpit +λ4lnpatentit +λ5in f ormit +λ6f diit +λ7f ixassetit +εit (13) In these formulas, I represents an indicator function, and γ and η , respectively, represents estimated values for the threshold levels corresponding to FER and IER. 4. The Calculation Results and Analysis of Coupling and Coordination Degree 4.1. Summarized Analysis of Coupling and Coordination Degree Table 4displays the overall formal environmental regulation comprehensive index (FER), informal environmental regulation comprehensive index (IER), and the coupling coordination degree (CCD) in the ten major urban agglomerations. It can be visually Economies 2024,12, 231 15 of 17 6.3. Emphasize the Synergy, Coordination, and Effectiveness of Various Policies On the one hand, there should be synergy in the formulation and implementation of different policies within the same urban agglomeration. For instance, environmental regulations should stimulate corporate innovation and drive the upgrading of the industrial structure in the urban agglomeration. Industrial development should reduce investments in highly polluting and energy-intensive industries to minimize environmental pollution and damage. Foreign investment projects should align with the development needs of the urban agglomeration industries, and technological innovation should be translated into productivity to promote the upgrading of the urban agglomeration industrial structure. On the other hand, various policies in different urban agglomerations should complement each other to promote the overall high-quality development of the urban agglomerations. For example, when formulating industrial development policies in the central and western urban agglomeration, consideration should be given to the responsibility of absorbing redundant industries from the eastern urban agglomerations. In the eastern urban agglomerations, when researching and developing new technologies, consideration should be given to the technological needs of economic development in the central and western regions, and so forth. Author Contributions: Conceptualization, X.Z.; data curation, R.L.; formal analysis, R.L.; methodology, X.Z. and R.L.; software R.L.; supervision, X.Z.; validation, H.W.; writing—original draft preparation, X.Z. and R.L.; writing—review & editing, X.Z. and R.L.; funding acquisition, X.Z. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Research Foundation from National Social Science Foundation of China (18CJL014), Ministry of Education, China (20JZD005). Informed Consent Statement: Not applicable. Data Availability Statement: The datasets used or analyzed during the current study are available from the corresponding author on reasonable request. Conflicts of Interest: The authors declare no conflicts of interest. Appendix A Table A1. List of cities contained in the ten major urban agglomerations. Location Urban Agglomeration List of Cities Eastern China Beijing–Tianjin–Hebei Beijing, Tianjin, Shijiazhuang, Tangshan, Qinhuangdao, Baoding, Zhangjiakou, Chengde, Cangzhou, Langfang, Xingtai, Handan, Hengshui Yangtze River Delta Shanghai, Nanjing, Wuxi, Changzhou, Suzhou, Nantong, Yangzhou, Zhenjiang, Taizhou, Hangzhou, Ningbo, Jiaxing, Huzhou, Shaoxing, Zhoushan, Taizhou, Yancheng, Jinhua Pearl River Delta Guangzhou, Shenzhen, Zhuhai, Foshan, Jiangmen, Zhaoqing, Huizhou, Dongguan, Zhongshan West Taiwan Strait Fuzhou, Xiamen, Zhangzhou, Quanzhou, Putian, Ningde, Longyan, Sanming, Nanping, Wenzhou, Lishui, Quzhou, Shantou Shandong Peninsula Jinan, Qingdao, Yantai, Weifang, Zibo, Dongying, Weihai, Rizhao Central and Southern Liaoning Shenyang, Dalian, Anshan, Fushun, Benxi, Dandong, Liaoyang, Yingkou, Panjin, Tieling, Jinzhou, Fuxin, Huludao Central China Middle Reaches of Yangtze River Wuhan, Huangshi, Ezhou, Huanggang, Xiaogan, Xian’ning, Jingmen, Jingzhou, Jiujiang, Yueyang, Xiangyang, Yichang, Changsha, Changde, Yiyang, Zhuzhou, Xiangtan, Deyang, Loudi, Nanchang, Jingdezhen, Yingtan, Shangrao, Xinyu, Fuzhou, Yichun, Pingxiang Western China Central Plains Zhenzhou, Luoyang, Kaifeng, Xinxiang, Jiaozuo, Xuchang, Pingdingshan, Luohe Chengdu–Chongqing Chongqing, Chengdu, Zigong, Luzhou, Deyang, Mianyang, Suining, Neijiang, Leshan, Nanchong, Meishan, Yibin, Ya’an Guanzhong Plain Xi’an, Xianyang, Baoji, Weinan, Tongchuan Economies 2024,12, 231 16 of 17 References Chen, Liang, Wanli Li, Kaibin Yuan, and Xiaoqian Zhang. 2022. 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