1. Introduction
The world is facing an invisible water quality crisis: the challenge from pollutants keeps pace with GDP (Gross Domestic Product) growth. Environmental pollution not only poses a threat to human and environmental health, but also has a negative impact on economic development, and seriously polluted areas could even lose one-third of their potential economic growth [
1,
2]. According to the Bulletin on the State of the Ecological Environment (2018) issued by the Ministry of Ecology and Environment (MEE) of China, water pollution is common in the seven major river basins in China. Among them, the water quality of the Yangtze River and Pearl River is better; the Yellow River, Songhua River and Huaihe River are slightly polluted; and the Haihe River and Liaohe River are moderately polluted. Moreover, the annual economic loss caused by water pollution in river basins exceeds 200 billion yuan, about 10% of GDP in China. City planners and policymakers in various countries are actively concerned about the impact of water quality changes of river basins on economy and ecology [
3], and even applied some models to restore rivers to reverse urban river syndrome [
4]. This paper aims to explore and design appropriate environmental policies for the water-polluting industry based on the government behavior, so as to achieve the win–win goals of emissions reduction and economic growth in river basins [
5,
6].
Empirical evidence from developed countries showed that the government is the most important source of environmental pressure and a traditional regulatory structure with strict monitoring and enforcement is the first and greatest driving force for many environmental compliance decisions [
7]. It is known to us that environmental factors often have the attributes of public goods. Taking the river basin as an example, it usually has the characteristics of fixed flow direction and pollutant transfer, leading to the typical negative externality of upstream enterprises’ emission behaviors [
8]. Thus, the impact of regulators and legislatures on environmental performance is greater than that of community organizations, rights groups, and the media [
9]. Environmental monitoring and law enforcement activities from government not only reduce pollution violations, but also greatly reduce emissions [
10]. According to the classical decentralization theory, local governments generally have stronger information advantages and supply efficiency than the central government [
11]. Local residents vote with their feet to ensure that public services match their preferences, so as to better manage the environment [
12]. For this reason, the Chinese government has established a decentralized governance system. The emissions targets are set by the central government, and local governments are responsible for formulating and implementing detailed environmental regulations [
13]. Some scholars investigated the emissions reduction effect of vertical reform under China’s water management system, and obtained some positive conclusions [
14]. For some specific environmental policies, such as River Chief System [
15], National Key Monitoring Enterprises, etc., it has also been verified that the implementation of these policies significantly reduced the emissions of pollutants [
16,
17].
Considering that environmental strategy is embedded in the political and economic system in China, it may also reflect the self-interest of local officials. The core of water quality management is to control the amount of pollutants discharged into the water in river basins. The direct cost of reducing pollution is related to the scale and technology of the plant itself, while the social benefits are affected by the amount of pollutants produced and number of people affected. As the local regulators, local governments need to pay more attention to the cost and benefits of governance when they strengthen the governance of polluting enterprises, and they may also be subject to political pressure from polluters [
18]. Therefore, they tend to make strategic responses to constraints from the central government and seek the maximum political support for their behaviors [
19]—that is to say, local governments and environmental protection departments change the environmental law enforcement strength in their jurisdiction according to the pollution emissions level of their adjacent areas [
20]. In addition, local governments may even manipulate the location of polluting enterprises to transfer pollutants downstream, e.g., move polluting enterprises away from the monitoring stations set up by the central government and place polluting enterprises near the administrative boundary of the downstream jurisdiction [
21,
22]. Therefore, local law enforcement activities respond to the benefits and costs of different industry regulations, showing the flexibility of regulatory activities, and there is a limited effect in terms of reducing the actual pollution of enterprises [
23].
It is necessary to explore the basin pollution problem from the perspective of different regulators, combined with the dual objectives of environmental governance and economic growth, and study the impact of environmental factors on the polluting industry in different regions of river basins. Our paper systematically reviews the relevant literature on environmental monitoring and law enforcement activities in China and has two scientific aims: one is to test the governance effect and economic effect of water quality monitoring on water-polluting industries, and the other is to explore the role of local governments in the process of environmental regulation and fiscal competition. The contribution of this paper is mainly reflected in the following aspects. Firstly, based on the data of seven river basins in China, a basin spatial regression model was designed from the perspective of behaviors of regulated subjects, which can be applied in other regions of the world. Secondly, according to the decentralization theory, we analyzed the behavior of regulators—that is, the mechanisms of central government and local government in the process of regulatory constraints and fiscal incentives, so as to achieve the win‒win goals of emissions reduction and economic growth in river basins. Thirdly, the Yangtze River Basin and the Yellow River Basin run across the eastern, middle, and western regions in China, and their high and low economic zones overlap with their downstream and upstream regions. Due to their unique geographic and economic characteristics, they were selected for further discussion to provide a reference for investigating the pollution abatement in typical river basins.
The rest of the paper is organized as follows.
Section 2 briefly introduces the mechanisms from the perspective of different regulators.
Section 3 summarizes the source of data and the establishment of a benchmark model. In
Section 4, we explain the results of the empirical method. Some possible extensions are discussed in
Section 5. Finally, we give some conclusions and suggestions in
Section 6.
4. Empirical Results
4.1. Analysis
The sample is a typical short panel; we applied the system GMM (Gaussian Mixture Model) to estimate it, because it is superior to the differential GMM in terms of estimation performance and computational efficiency. In order to avoid pseudoregression and ensure the validity of the estimation results, we used an LLC (Levin-Lin-Chu) test to check the unit root of each variable sequence. The p-value showed that the original hypothesis is rejected at the 5% confidence interval—that is to say, all variables were stable.
Table 2 reports the results of the benchmark regression, showing the governance effect and economic effect after controlling the geographical and temporal characteristics. It can be seen that, consistent with our expectations, the coefficients of water quality were significantly negative. The coefficients in columns (1) and (2) of
Table 2 indicate that if the average COD rose by 1 mg/L in the past year, plants reduced their discharge by 1.9% and decreased their production by 0.2%, respectively. Overall, we found positive evidence of past downstream water quality influencing polluting plants’ decisions. Moreover, the coefficients of the lag period of the dependent variables were both significantly positive. This indicated that the intensity of initial pollution causes more serious pollution later, which means that the behavior of water-polluting industries is a cumulative and continuous process.
From the regression results of other control variables, we see that the overall conditions of the industry played a positive role in the decision making of polluting enterprises, especially labor cost and industry size, whose coefficients reached 0.328 and 0.304 in the economic effect. The polluting industries screened out are dependent on resources, most of which belong to traditional manufacturing industries, with the characteristics of low technology, low value-added, and high resource consumption. This means that, for them, the abundance of production factors is the most important factor, and the scale effect will promote their agglomeration. In contrast, they have limited requirements for technical advancement.
In terms of regional conditions, regional infrastructure is very important to polluting industries, and its positive effect on sewage discharge reached 0.089, which passed the 1% significance test. Most areas in China are changing from high energy consumption industry to clean service industry; however, the current economic growth still leads to different degrees of resource consumption and environmental pollution. After controlling the pollution of planting and living caused by agricultural production and residential life, the results show that they both had positive impacts on the polluting industry; in particular, the impact of planting scale on pollution emissions was 0.047.
4.2. Robustness Test
In order to enhance the reliability, we checked the robustness of the above results. The categories of polluting industries were revised first. The Bulletin of the First National Census of Pollution Sources (2010), released by MEE, shows that the total amount of COD discharges from the top seven industrial sectors exceeds more than 81.1% of total emissions in China. For this reason, we referred to Cai et al. [
22] and defined these seven industries as polluting industries.
Due to the high correlation between current and lagged pollution emissions, the lagged water quality is determined endogenously. Therefore, upstream water quality is taken as a tool variable because it directly affects the downstream water quality, and is also irrelevant to the pollutant discharge decisions of enterprises [
50].
Table 3 shows the results of using upstream water quality as a tool variable. In terms of the governance effect on the polluting industry, the result is not as significant as the original estimate. For every 1 mg/L increase in upstream COD, the emission intensity of the polluting industry reduced by 1.5%, which was 0.4% less than the coefficient in the first column of
Table 2. At the same time, if the upstream COD increases by 1 mg/L, the economic effect of polluting industries will be weakened by 0.8%, which is larger than that in
Table 2. The results show that our estimation of the causal effects of environmental water quality on emissions and industrial production is robust.
6. Conclusions
In this paper, from the perspective of river basins, the impact of environmental water quality on polluting industry was discussed by using a panel regression model combined with the spatial characteristics of rivers. We found clear evidence that ambient water quality had both a governance effect and an economic effect on polluting industries. If the average COD rose by 1 mg/L in the year prior, the emissions of the polluting industries would be reduced by 1.9% and the output by 0.2%, respectively. The higher the initial pollution intensity, the more serious the later pollution. Due to most of the polluting industries being resource-dependent, some control variables of industry conditions played positive roles in the emissions and production of polluting enterprises. Pollution from agriculture and residences also had the same significant impact. After revising the classification of polluting industries and taking upstream water quality as an instrumental variable, the estimation results still have good robustness.
In terms of local government behavior responses and strategic choices, there was a negative correlation between the local environmental regulation and pollution emissions—that is, improving the intensity of regulations can reduce the emissions of polluting industries to a certain extent, while the local environmental regulations and industrial production showed an inverted U-shaped relationship in terms of the economic effect. However, the governance effect and economic effect of local government fiscal competition showed no difference. Generally speaking, when the regional fiscal competition became more intense, the emissions and output of local polluting enterprises increased.
To our knowledge, the ecological protection and high-quality development of the Yangtze River Basin and the Yellow River Basin are key development strategies in China. Therefore, taking these two typical basins as research objects, it was estimated that the governance effect in the two basins exceeded the average level, and the absolute value was 0.4% higher than the whole sample data. By further dividing relative upstream cities and relative downstream cities, it was found that the former had more significant responses to water environment in terms of industrial pollution emissions, and the gap between regions expanded further after 2013. The interaction term from the aspect of local government was always negative. When the regulation index was equal to its mean value, the partial effect of fiscal competition on pollution emissions was negative, which indicated that the behavior of local officials was conducive to environmental governance.
In general, with the continuous strengthening of water environment management from the central government in China, water quality monitoring has played a direct and positive role in the emissions reduction of polluting industries. Under competition from local governments, the division by administrative boundary leads to the risk of cross-border pollution. Officials tend to gain promotion through economic competition by reducing the threshold of resource supply and even inducing enterprises to overuse environmental resources, which leads to the development of regional economy and restrains the governance effect of the central government. In conclusion, in order to reduce emissions from polluting industries, regulatory authorities need to adhere to water quality monitoring and management. The central government should design both environmental and economic policies in China so as to avoid the unexpected environmental consequences caused by local government competition. Through the establishment of a set of effective restraints on local government’s behaviors, local governments can match environmental governance to local economic development, and fundamentally improve the water pollution governance.