1. Introduction
China has a vast territory and several river basins, thus forming many rivers basin economic zones, such as the Yangtze River Economic Belt and the Guangdong-Hong Kong–Macao Greater Bay Area, which are relatively important development strategic areas in China and provide a strong driving force for China’s development [
1]. In 2019, Chinese President Xi Jinping emphasized that “protecting the Yellow River is a long-term plan for the great rejuvenation of the Chinese nation” and has hosted several special conferences to study the ecological protection and high-quality development of the Yellow River Basin. As a result, ecological protection and high-quality development in the Yellow River Basin have become a primary national strategy [
2].
At present, the regional economy has transformed from a stage of high-speed growth to a stage of high-quality development, with the inherent requirements of quality first and efficiency prioritizing development [
3]. Environmental regulation plays an essential role in this transition. Environmental regulation regulates various behaviors that pollute the public environment to protect the ecological environment. The international community has gradually realized the importance of environmental regulation. For example, the United States has controlled pollution from the source [
4] and began to gradually transition from implementing mandatory order regulations to incentive policies in the form of rewards and punishments. Japan and Germany arouse the protection awareness of the public and enterprises through incentive mechanisms to achieve longer-term and adequate environmental protection [
5,
6]. China has incorporated environmental regulation into government performance assessment, including energy conservation, emission reduction, and environmental protection in the performance assessment of local leaders, which can more effectively promote energy conservation, emission reduction, and environmental protection [
7].
Appropriate environmental regulation can stimulate innovation, promote technological innovation, and improve efficiency. It can also promote the upgrading of industrial structure through screening effects and spillover effects, thereby affecting the efficiency of high-quality regional development [
8]. However, the excessive intensity of environmental regulation may reduce production efficiency and hinder the region’s improvement of high-quality development efficiency. If the intensity of environmental regulation is too low, it is impossible to improve and protect the regional ecological environment, thereby reducing the efficiency of a comprehensive evaluation of high-quality regional development [
9]. Appropriate environmental regulation depends not only on the strength but also on the matching of the transmission mechanism to the efficiency of high-quality development [
10].
Efficiency is a comprehensive indicator for evaluating high-quality regional development, and social resource allocation needs to be considered. Researchers can analyze the strength of the development level and the space for sustainable development by weighing and comparing regional inputs and outputs. At present, research on high-quality development efficiency generally focuses on the high-quality development efficiency of industries, industries, and resource utilization, such as the high-quality development efficiency of manufacturing, high-quality development efficiency of commercial banks [
11], and high-quality efficiency of rural land use [
12]. For the high-quality and efficient development of the region, it focuses on a specific aspect of development, such as the high-quality economic development efficiency [
13,
14] and the high-quality development efficiency of the urban environment [
15]. A limited number of pieces of literature discuss the high-quality development efficiency of cities and economic belts [
3,
16,
17].
In terms of efficiency measurement methods, the Stochastic Frontier Analysis (SFA) proposed by Aigner et al. (1977) is often used as a measure of efficiency [
18]. Since SFA needs to assume the specific form of the production function, most researchers prefer the data envelopment method (DEA), which introduces the input–output slack problem to avoid bias in the model set [
19]. However, the non-radial and non-angular SBM model proposed by Tone (2001) found that this method easily ignores environmental factors and cannot be comprehensively measured by comprehensive indicators [
20]. Although these research methods have certain shortcomings, they also lay a research foundation for measuring high-quality development efficiency. Combining the advantages of the super-efficiency DEA model and the SBM model [
21,
22], this paper adopts the super-efficiency SBM model to measure the high-quality development efficiency of the region comprehensively and comprehensively from the input and output of high-quality regional development combined with undesired output.
Early studies on environmental regulation, industrial structure, and high-quality development focused on the relationship between environmental regulation, industrial structure, and high-quality development. For example, some studies have found that environmental regulation has a promoting effect on the industrial structure by analyzing the role of environmental regulation in technological progress, international trade, FDI, and other aspects [
23,
24,
25]. Other studies have found that environmental regulation has spatial spillover effects, fixed effects, and spatial transfer effects on industrial structure [
26,
27,
28]. With the rise of high-quality development, scholars have begun to pay more attention to research on the impact of environmental regulation on high-quality development. Most studies believe that environmental regulation can significantly affect the high-quality development of the regional economy through factors such as industrial transformation, transaction costs, technological innovation, human capital, and energy efficiency [
29,
30,
31,
32,
33,
34,
35]. In the process of promoting regional economic development, environmental regulation can lead to poverty reduction and enrichment effects, innovation effects, energy effects, adjustment effects, mediation effects, threshold effects, and two-way feedback effects [
36,
37,
38,
39,
40]. Research on environmental regulation, industrial structure, and high quality currently focuses on the relationship between the three. For example, whether environmental regulation can affect high-quality development through industrial structure [
39], environmental regulation and industrial structure have a non-linear relationship with high-quality development [
34].
In the current research, there are still the following problems: the efficiency measurement often needs to pay attention to the problem of undesired output; the interaction term between environmental regulation and industrial structure is rarely used as the active path that affects the efficiency of high-quality development. Studies on environmental regulation, industrial structure, and high-quality development efficiency rarely study the non-linear relationship among them. This study adopts the SE-SBM Model that introduces slack variables, which can be solved in a larger feasible region. We consider the undesired output in the development of the river basin while also addressing the efficiency ordering problem between effective decision-making units and comprehensively and dynamically measuring the high-quality development efficiency of the Yellow River Basin. Second, we constructed a panel data model to analyze the impact of environmental regulation, industrial structure, and their interaction on the efficiency of high-quality development. We theoretically analyze the non-linear relationship between environmental regulation, industrial structure, and their interaction terms on high-quality development efficiency and determine the threshold value from the whole watershed and sub-watershed. Finally, according to the research results, we put forward countermeasures and suggestions to promote the high-quality development of the river basin.
2. Materials and Methods
2.1. Overview of the Study Area
The Yellow River Basin covers a vast area. It flows through nine provinces in China, namely Qinghai, Sichuan, Gansu, Ningxia (upper area), Inner Mongolia, Shanxi, Shaanxi (midstream), Henan, and Shandong (downstream). The Yellow River Basin is a prominent grain-producing area with significant energy, chemical, raw material, and industrial bases in China. It is also one of the essential protection areas for the country’s energy and environment. The basin pays attention to environmental regulation. It has issued policy documents such as the “Plan for Ecological Environmental Protection in the Yellow River Basin” and “Outline of the Plan for Ecological Protection and High-Quality Development in the Yellow River Basin.” The provinces in the basin have also introduced environmental regulations suitable for their development.
The Yellow River Basin attaches great importance to optimizing and adjusting industrial structures. However, from the industrial development data of 9 provinces in the Yellow River Basin (2019 data): the proportion of the primary industry is higher than the national average [
41,
42], the contribution rate of the primary industry to the regional GDP has always been low. Except for Sichuan Province and Gansu Province, the contribution rate of the primary industry to the regional GDP in other provinces (autonomous regions) is less than 10%. The Yellow River Basin is a crucial energy production base in China, with abundant natural and mineral resources, a robust industrial base, and obvious development advantages. The GDP of the secondary industry in the basin accounts for 41% of China’s GDP, and it is also a significant driving force for economic growth in the basin. The development of the tertiary industry in the Yellow River Basin is slow. The tertiary industry in the Yellow River Basin accounted for 44.4%, lower than the national average of 53.3% and the Yangtze River Basin of 54.1%. The tertiary industry in the Yellow River Basin only accounts for 23.4% of the national tertiary industry, which is on a downward trend. The industrial development in the Yellow River Basin has yet to form its distinct advantages, and the development level of the tertiary industry needs to be further improved [
43]. The data in this paper come from the 2010–2019 provincial statistical yearbooks, national databases, and EPS databases.
2.2. SE-SBM Model
Efficiency is analyzed from the perspectives of input and output and considers the allocation of social resources to evaluate the comprehensive level of high-quality regional development. Efficiency measurement can effectively evaluate the high-quality development efficiency of the region, which is conducive to the horizontal comparison between regions and finding the natural source of power or the crux of the problem.
In the SE-SBM model, it is assumed that there are decision-making unit (DMU), each DMU has inputs denoted as , and each input has a weight of , where can be taken from 1 to . Each decision-making unit has outputs, denoted as , and each output has a weight of , where can be taken from 1 to . According to the efficiency value solved by the Model, the result can evaluate the efficiency level of each decision-making unit and its importance in the Model.
Regarding selecting measurement indicators for high-quality development, refer to Zhang (2021)’s [
16,
44,
45,
46] research on high-quality development. The indicators for selecting input and output are shown in
Table 1.
2.3. Panel Regression Model
Panel regression models are widely used to analyze whether there is a significant relationship between independent and dependent variables. They can also analyze the strength of the influence of multiple independent variables on a dependent variable [
47,
48]. This study uses panel regression to explore the correlation between each variable and the high-quality development efficiency of the Yellow River Basin, laying the foundation for constructing the threshold model in the following. The core variables of this paper are environmental regulation, industrial structure, and the interaction of environmental regulation and industrial structure. Unlike previous studies, this study introduces the interaction between environmental regulation and industrial structure. It explores whether environmental regulation can affect the efficiency of high-quality regional development by affecting the industrial structure. If the influence result is positive, it means that the interaction between environmental regulation and industrial structure can promote the high-quality development efficiency of the Yellow River Basin. Otherwise, it means that the interaction between environmental regulation and industrial structure inhibits the high-quality development efficiency of the Yellow River Basin. The panel model is set as follows:
where
,
represent region and time respectively,
represents the individual characteristics of the observed value,
represents the high-quality development efficiency value of
province in
year,
represents the environmental regulation intensity of
province in
year. The intensity of environmental regulation is expressed as the proportion of investment in industrial pollution control to regional GDP,
represents the industrial structure level of
province in
year,
is the interaction term between environmental regulation and industrial structure of
province in
year.
represents the control variable introduced. ε is the random disturbance term.
Many factors affect the efficiency of high-quality development in a region. Referring to existing research, we selected the indicators of opening-up level, population density, and economic development level as control variables: index of the level of opening to the outside world (IAE): improving the level of opening to the outside world can promote the adequate flow of resources; population density index (PD): the regional population density is relatively high, indicating that the population can be effectively attracted, indicating that the regional development situation is good; economic development level (GDP): the improvement of economic development level will promote the increase in the high-quality development efficiency value.
2.4. Threshold Model
Panel regression analysis verifies the impact of the interaction between environmental regulation and industrial structure on the efficiency of high-quality development. However, considering that industrial development is profitable, environmental regulation and regional high-quality development efficiency are non-profit, there is a theoretical nonlinearity between the two, also known as the theoretical threshold effect. The threshold model can measure the non-linear phase relationship between explanatory variables and explained variables. According to Hansen’s threshold estimation method, the primary model of the threshold effect is set as follows:
where
and
represent region and time respectively;
Represents the explained variable;
represents the indicative function,
represents the threshold value,
represents the threshold variable;
denotes the random disturbance term. According to Hansen’s basic threshold model and combined with the research in this paper, the Model is constructed as follows:
The explained variable represents the high-quality development efficiency value of province in year. Core explanatory variables: industrial structure , environmental regulation , the interaction term between environmental regulation and industrial structure , and the selection of control variables are the same as formula (1). Using Stata software, the threshold effect test was carried out through the panel model introducing time, region, and other observation variables.
4. Conclusions
This study focused on the impact of environmental regulation, industrial structure, and interaction on the high-quality development efficiency of the Yellow River Basin. We obtained the following conclusions and provide corresponding recommendations based on the conclusions.
Although the development level of the Yellow River Basin fluctuates, it is generally on a rising trend. The development process of different watershed segments presents stages and heterogeneity. From the perspective of sub-basins, the high-quality development efficiency of the downstream areas of the Yellow River Basin is significantly higher than that of the middle and upper reaches. The level of economic development and financial investment plays an essential role in the efficiency of high-quality development. The research suggests that we should improve economic development and increase financial investment.
From the analysis results of panel regression results, we can see that the interaction between environmental regulation and industrial structure dramatically impacts the efficiency of high-quality development, and the interaction between upstream and downstream environmental regulation and industrial structure has a more significant impact. From the regression results of the control variables, there is heterogeneity in the influence of each control variable on the high-quality development efficiency of the Yellow River Basin. The level of opening to the outside world has a positive effect on the efficiency of high-quality development. In contrast, population density and regional GDP negatively affect the efficiency of high-quality development. The study believes that in the process of high-quality development of the Yellow River Basin, regional import and export levels should be reasonably improved. Second, the introduction of high-quality foreign capital to promote regional economic development should take place. Finally, enterprises in the basin should be encouraged to develop into resource-saving and environment-friendly enterprises.
The analysis of the threshold regression results shows that the interaction term of the industrial structure and environmental regulation of the whole basin has a significant single threshold effect on the high-quality development efficiency of the Yellow River Basin. The analysis of the threshold regression results of the sub-basins shows that when the upstream industrial structure is on the left side of the threshold value, the interaction term of industrial structure and environmental regulation has a significant role in promoting high-quality development efficiency. At the same time, there is no threshold effect on the right side of the threshold value. The threshold effect of high-quality development in downstream areas is very significant. Whether the industrial structure is on the left or right side of the threshold, the interaction between the industrial structure and environmental regulation negatively impacts the efficiency of high-quality development. In this regard, we put forward the following suggestions: the upstream area needs to improve the technical level, optimize the industrial structure, and promote the rationalization and advanced nation of the industrial structure. In the development process of the midstream region, it is necessary to effectively control the population density and reduce the adverse environmental effects caused by population agglomeration. Since there is no significant threshold effect in the midstream region, it is only necessary to focus on the diversified development of industries and change the structure of a single industry.