1. Introduction
Sustainable development is the “golden key” to resolving today’s global issues, achieving a balance between the environment, society, and economics. However, in the hog-feeding supply chain, accomplishing this goal is more challenging. According to data made public by the American Farm Bureau database, in 2021, pork consumption was 3.1 times greater than the global per capita level in China, and over half of the world’s pork is supplied there. China has long been the largest global producer and eater of pork as a result. Nevertheless, hog manure from excessive pig production and consumption is associated with the risks of poor air quality and contaminated water supplies [
1]. According to the Food and Agriculture Organization of the United Nations (FAO), carbon emissions contribute 5% of the total global emissions [
2]. Organic compounds in pig manure are the main culprits in water eutrophication [
3]. The communique of the second national pollution source census published by China in 2020 shows that in 2017, the total pollutant loads generated from livestock and poultry were 1000.53 million tons of chemical oxygen demand, 110,900 tons of ammonia nitrogen, 596,300 tons of total nitrogen, and 119,700 tons of total phosphorus (Data from
https://www.mee.gov.cn/gkml/hbb/bgg/201002/t20100210_185698.htm (accessed on 13 December 2022)), topping the list of agricultural pollution sources. Widespread rural household scatter breeding is one of the prime causes of livestock pollution [
4], compared with North America and Europe, which have a high proportion of large-scale farms. Even China recently established several regulations to increase the proportion of large-scale farming to achieve industrial transformation and upgrading, with the percentage of large-scale farming rising from 36.6% in 2011 to 57.1% in 2020 (Data from
http://www.moa.gov.cn/ (accessed on 14 December 2022)). The sustainable growth of China’s pig industry continues to have far to go because of the characteristics of low-scale efficiency, the low automation level, poor capital formation, high labor intensity, and high carbon emissions [
5].
China will steadfastly adhere to the road of high-quality growth with an ecological priority, as well as green and low-carbon development, to completely implement the new development concept. In September 2020, the central government released its Opinions on Promoting the High-Quality Development of the Animal Husbandry Industry. It stated that it would speed up the development of contemporary livestock and poultry breeding, animal epidemic prevention, processing, and circulation systems; boost the industry’s quality, efficiency, and competitiveness; and establish a new pattern of high-quality development oriented toward green development. According to studies, there are two main paths to green transformation: enterprise-independent technology innovation and government-led environmental regulation [
6], and the latter aids in overcoming “market failures” [
7]. Simultaneously, environmental policy can promote sustainable innovation and help achieve the objective of green transformation [
8]. The Chinese government has implemented several “green agreements” in the context of the ecological pollution-driven transformation of the livestock industry (
Table 1), including increasing pollution control inputs, establishing emission standards and associated penalties, and stepping up pollution oversight. From the standpoint of environmental protection, pollution associated with livestock and poultry breeding has greatly decreased, but the rate of pig farming has gradually increased. The new objective of China’s pig industry is synergistic development, which includes economic growth, resource use, supply stability, environmental protection, livestock and poultry health, quality, and safety.
When investigating the impact of environmental regulations on the development of the pig industry, it is required to study the government’s possible arbitrary regulation strategy based on the short-term goal of suppressing the “pig cycle” and the overall impact of the new behavioral characteristics of breeding subjects under environmental regulations on the industrial chain. First of all, local governments are motivated to make arbitrary decisions when implementing environmental regulatory standards, which may lead to the deterioration of environmental pollution in the “reverse pig cycle” [
9]. Due to the possible conflict of policy objectives in different pig cycle stages, local governments are hesitant to implement regulation policies. On the one hand, to achieve the emission reduction goals, local governments need to actively respond to the environmental regulation policies issued by the central government; on the other, In 1998, China’s Ministry of Agriculture proposed the construction of the “Vegetable Basket Project” to solve the problem of food market supply shortages. The local government has the responsibility to ensure supply and price stability as pigs are part of the basket. As a result, local governments tend to choose between environmental regulation and pig supply. Secondly, the specific effect and realization method of environmental regulation driving industrial chain transformation and upgrading needs to be further clarified. The compliance cost effect and innovation offset effect are the two categories used to categorize the formation mechanisms of environmental regulation effects in the literature [
10]. The expense of pollution control will rise because of environmental regulation, and businesses will scale down production to maintain profits or force businesses to make green innovations to compensate for environmental management costs, thus improving green productivity [
11]. It is necessary to systematically study the dynamic impacts, heterogeneity, and impact mechanisms of environmental regulation on the whole pig industry chain for the process of scale transformation in the context of dual carbon targets.
We used data from China from 2005 to 2019 to analyze the effects of ER on DPI to close this research gap. The following aspects show how the donations were accomplished. First and foremost, this is the first attempt to gauge the pig industry’s development level from the standpoint of the industrial chain, which includes feed, medical care, breeding, slaughter, consumption, etc. Secondly, the dynamic panel model is utilized to analyze the impacts and variety of ER on the DPI, taking into account the dynamic sustainability of the DPI. Thirdly, it is crucial to explore whether technological innovation and large-scale breeding form the innovation offset effect in the process of pig industry transformation. Finally, the amount of local environmental regulations is utilized to further assess how provincial governments will implement national environmental regulations.
The remainder of the essay is organized as follows:
Section 2 provides a literature review, followed by theoretical analysis and the research hypothesis in
Section 3, and the building of the model and indicators in
Section 4. While
Section 5 analyzes the empirical findings,
Section 6 offers the conclusion and policy consequences.
3. Theoretical Analysis and Research Hypothesis
Environmental regulations are laws created and put into effect to address the negative externalities that environmental pollution has on the economy and society [
41]. There are two opposing viewpoints in the academic community on the policy impact of environmental regulation: “cost-effectiveness” and the “innovation compensation effect.” Some academicians emphasize the “compliance cost hypothesis” concerning “cost-effectiveness” to highlight how the enforcement of environmental legislation will raise the expenditures of businesses and other micro-entities and also stifle innovation and technological advancement [
42,
43]. The second is the “innovation compensation effect”, which is supported by academicians who believe that reasonable environmental restrictions might encourage businesses to advance their technology and so increase productivity and competitiveness [
44,
45]. As a result, this paper develops a framework for the theoretical analysis (see
Figure 1) and suggests a research hypothesis.
From the short-term perspective, environmental regulations support the “follow the cost hypothesis”. First and foremost, the taxation of environmental legislation will raise the expenses of production for businesses and farmers, thus decreasing the profitability of pig-participating entities and lowering the enthusiasm of pig farmers [
20]. Moreover, the division of prohibited areas for pig farming directly restricts enterprises’ and farmers’ breeding areas and forces them to withdraw from breeding and transfer breeding sites [
46]. Finally, the cost of upgrading pollution control equipment, sewage technology applications, and system maintenance will go up as a result of emission reduction and pollution control laws. Pollution control spending’s “crowding out” effects on investment in R&D will temporarily take place, and financial limitations will prevent businesses and farmers from using their productive inputs, further reducing production efficiency [
47]. Environmental regulatory pressure from the environmental protection department on the primary pig farming body will weaken farmers’ trust in production in the short term, affecting the pig industry’s upstream and downstream development. Excessive economic penalties will drive farmers to seek compensation from pig welfare, such as reduced feed quality, medical services, and so on. The above will run counter to the original intention of environmental protection regulations and is not advantageous for the sustained growth of the pig business. As a result, the following theories are proposed in this paper:
Hypothesis 1. In the short term, environmental regulations will reduce the development of the hog industry chain through cost-effective and crowding-out effects.
From a long-term perspective, environmental regulation forms the “innovation compensation effect” [
48]. First, long-term supervision will progressively alter producers’ expectations for policy and knowledge of the environment [
7] and improve pollution control technology and equipment input. Secondly, due to the adverse impact of environmental regulations on corporate profitability, companies are forced to alter their business strategies and expand upstream and downstream into the production of veterinary medicines, piglet breeding, slaughtering and processing, distribution, and consumption to reduce transaction costs, as well as look for economies of scale. Finally, the subsidy policy reduces the dilemma of long-term financing constraints, stabilizes the confidence of businesses in green production, expands green credit, and eases the dilemma of pollutant emission investment, crowding out green R&D investment. In a nutshell, the compensatory impact of innovation will be gradually boosted by green technological innovation, investment in anti-pollution infrastructure, and public knowledge of environmental issues [
49].
Hypothesis 2. In the long run, environmental regulation will improve the development of the hog industry chain through the innovation compensation effect.
The market selection mechanism will gradually eliminate the low-efficiency, high-pollution, and low-standard aquaculture retail and enterprises because of the implementation of environmental regulations. As a direct consequence, capital will flow to the capital-intensive or knowledge-intensive aquaculture enterprises, forming a new type of large-scale transformation and upgrading. The “reversed transmission” green technology innovation used by scale management companies as a response to environmental stress generates more than just “compensatory income” from blowdown costs [
50]. Businesses that adopt green innovations into their production processes are far less reliant on the initial polluting manufacturing mode and can profit from economies of scale [
40].
Hypothesis 3. Large-scale farming and technological innovations play a positive moderating role between environmental regulation and the development of the pig industry chain.
There is no doubt that the considerable differences in resource endowment, technological level, traffic conditions, market, technology, and policy shape the regional development pattern of the hog business [
51]. The eastern and southern areas of China hold the majority of the country’s pork production capability. Specifically, the southwest region is the mainstay of the pig farming hub due to the area’s ideal environmental conditions, inexpensive labor, and low feed transportation costs. The southwest also supplies pork to coastal provinces while maintaining self-sufficiency [
52]. To ensure the supply of hogs, the government in the southwest will therefore loosen its environmental regulations. The northwest, with its large zones, substantial land resources, as well as agricultural and by-product resources, is the origin of cattle and sheep breeding. The cost impact of environmental regulation on pig breeding is minimal because the primary targets of environmental regulation are cattle and sheep. The eastern coastal area is primarily a consuming region with limited production resources, developed transportation, and mass population agglomeration [
5]. As a result, the governments in the eastern region frequently create regulatory measures with the protection of the environment as their main goal. Overall, the development of the hog business is generally impacted differently by the disparities in environmental legislation in each region. When environmental regulations are not as strict, businesses or farmers are more ready to pay the cost of pollution management than to develop innovative production and pollution control technology. As the level of environmental regulation rises, the profit from technical innovation grows more than pollution control. In conclusion, hypothesis 4 is developed.
Hypothesis 4. There is regional heterogeneity in the impact of ER on the DPI.
5. Empirical Results
5.1. Evaluation Results of DPI
Table 4 shows the comprehensive index of DPI in various provinces. The average annual growth rate of the DPI of China from 2009 to 2020 is 2.01%, compared to 2.85%, 2.21%, and 0.96% for the main, middle-, and low-production regions, respectively. According to the ranking, Hunan reaches the highest average level of DPI (0.5346), followed by Sichuan and Guangdong (0.5234 and 0.50440, respectively), and Qinghai has the lowest quality of industrial chain (0.1712). From the mean value of production areas, the DPI of the main production zones is highest (0.4461), followed by the medium-sized (0.3130) and small-sized (0.2421) producing areas. This implies that the live pig industry’s development level and the regional feeding scale are strongly correlated.
Figure 2a clearly shows the development trend of each province. It can be seen that the pig industry layout in China has obvious aggregation characteristics, with the main production area (red mark) mainly concentrated in the southwest, the middle-production area (green mark) concentrated in the east, and the low-production area (yellow mark) concentrated in the northwest. This is different from Zhong et al.’s observation that pig total factor productivity is greatest in the eastern region [
69]. The reason is that the evaluation indexes of the pig industry are different. Compared with green production, this paper pays more attention to the development of the whole hog industry chain.
Figure 2 also shows the pig industry development levels in 2005, 2010, 2010, and 2019, and it can be seen that the industry development levels of the 30 pig provinces are largely dominated by an upward trend, but there is a significant decline in DPI in 2019. The epidemic of African swine disease could be to blame. By the end of 2019, China had killed 1,193,000 pigs overall since the epidemic began in 2018. Because of the severe imbalance between supply and demand brought on by the abrupt decrease in hog stock, China experienced a protracted oversupply problem. Additionally, as a result of farmers’ fear of swine fever, many of them downsized or withdrew from the market, which not only caused a backlog of material stocks upstream in the hog industry chain but also made the supply gap downstream in the chain worse.
Figure 2b shows the DPI of different links in the pig industry chain, with the downstream being the lowest, and the contribution of the middle as the core link being the largest. The overall quality of the industry chain showed an upward trend with time but declined in 2006, 2012, and 2018. Looking back at the Chinese pig industry’s development history, we recognize that the pig industry has been affected by the pathogenic blue-ear disease, pig cycle, and African swine fever in 2006, 2012, and 2018, respectively. This shows that external impacts have a detrimental impact on China’s pig industry’s development.
5.2. Benchmark Empirical Results
The estimates based on OLS, FE, and FGLS tests, and system GMM are reported by models 1–4 (
Table 5). As you can see, all four models obtain nearly the same results. The value of AR(1) is less than 0.1, and AR(2) is greater than 0.1 in model 4. This implies that the perturbation term has no autocorrelation [
70]. The
p-value of the Hansen test statistic of 1.000 shows that the hypothesis of the tool variable is correct and cannot be rejected. The chosen GMM model is feasible, as shown by the estimated coefficient of the first-order lag of explanatory variables in the GMM model, which is between OLS and FE.
The measured coefficient in model 4 shows that although the linear term of ER is notably negative, its squared ER2 is extremely positive in all models. The findings support the “U” dynamic model of DPI increase with ER; hypotheses 1 and 2 are also confirmed. This discovery echoes that of Minton and Schrand [
59], who pointed out a non-linear connection between environmental regulation and the shift in Chinese industrial development patterns. Environmental regulation slows the growth of the pig business in the early stages of environmental policy implementation through “cost effects” and “crowding out effects”. As the regulation level increases, the government will limit the emission behavior of a few heavy polluters or even force companies out of production. Some pollution-intensive companies and farmers will also withdraw from the market due to the high environmental costs. Eventually, some companies and farmers will have to upgrade their pollution control equipment and invest in research and development to meet regulatory requirements. The “anti-driving effect” and “compensating effect” are becoming more and more prominent.
We concluded from the control variable coefficients that schooling was significantly positive at the 5% significant level, indicating that it considerably benefited DPI. In the knowledge economy, knowledge is the primary driver of economic growth. Education is becoming increasingly vital as a means of investing in human capital, contributing to the advancement of production technology, and encouraging industrial innovation [
71,
72]. Through technical improvement and industrial innovation, EDU raises DPI. However, at the 1% level, pork prices were notably negative. The conclusion was in line with Wu et al. ‘s observation that hog prices had a detrimental impact on eco-efficiency [
40].
5.3. Heterogeneity Analysis
Different provinces show considerable discrepancies in the number of pigs. We divide 30 provinces into main, medium-, and low-production areas. In
Table 5, models 5–7 show the regression results of different production areas based on system GMM. From the estimation coefficient, it is clear that ER affects DPI significantly in a U-shape in low- and high-producing locations but not in mid-producing areas. The main producing location is frequently the focal point of the government’s pig supply assurance and environmental rules, which could be the cause. When the initial environmental regulation is increased, the operating cost of the farmers will eventually increase, causing harm to the scale of production, and the late internal vitality will gradually increase. Green technological innovation will accelerate the creation of the innovation compensation effect. For low-production areas, the government prefers a strategy of environmental protection to a long-term policy of stable production capacity. Therefore, companies and farmers in low-production areas prefer to pay the cost of emission of small amounts of pollutants rather than long-term investment such as research and development. Under environmental regulations, low-production areas are mainly experiencing short-term negative shocks.
5.4. Robustness Checks
Given that the proxy for ER is not uniform, we utilized per capita income as an alternative to measuring ER [
62]. Models 8 and 9 in
Table 6 represent the outcomes after replacing the dependent variable using FGLS and GMM. We discovered that the key variables’ significance and sign are similar to the basic regression, indicating that our paper’s findings are reliable.
Another key point to remember is that the effect of ER on DPI may have a time lag. As a result, we applied a one-period lag to the ER and re-regressed the explanatory variables. The FGLS and GMM results for Models 10 and 11, respectively, demonstrate that the ER with a one-period lag continues to have a favorable U-shaped association with the DPI.
5.5. Moderating Effect Analysis
According to the theoretical analysis framework of
Section 3, this study selected the logarithms of technological innovation (TI) and large-scale farming (LSF) to form two interaction terms with ER, and then FGLS and GMM were used for regression analysis.
Table 7 displays the regression results after adding interaction elements.
Firstly, the estimated coefficient for the interaction term of ER and TI in models 12 and 13 are significantly positive at 10%, respectively. TI greatly lessens the detrimental impact of ER on DPI. The negative effect of ER on DPI increased by 0.30–1.06% for every 1% increase in the proportion of TI. The conclusion was in line with Wang et al. [
73]. The green innovation behavior of pig breeding subjects can help the breeding subjects to carry out green production, decrease the pollution cost, and improve the green production efficiency of pig farmers. Improvements in technology can speed up the arrival of the “innovation compensation effect” and reduce the amount of time that environmental regulations must show the “cost-effective effect” to promote the development of the live pig industry chain at a higher level.
Secondly, the estimated coefficients of ER and LSF interaction terms in model 14 and model 15 are significantly positive at 1% and 10%, respectively. The results showed that LSF significantly reduces the negative effects of ER on DPI. The negative effect of ER on DPI increased by 0.59–0.69% for every 1% increase in the proportion of LSF. The reason may be that large-scale pig farms have higher waste disposal rates and lower pollution levels than free-range farms. Under the same environmental regulation framework, large-scale pig farms can better utilize their advantages to expedite the arrival of the inflection point of the innovation offset effect. Large-scale breeding is crucial to the environmentally friendly and long-term growth of the pig industry.
Even though the pig industry has experienced numerous external shocks recently, the implementation of large-scale transformation and an upgrading strategy improves the risk resistance ability of the industrial chain as a whole, weakening the short-term “compliance costs effect” caused by the environmental regulation of negative effects, accelerating the formation of the “innovation effect”, and finally enhancing the development of the overall level of the pig industry chain.
5.6. Further Discussion
To master how provincial governments will implement national environmental regulation, we collected the number of environmental policies about livestock and poultry released by the official government website. We brought central environmental policy (CER) and local environmental regulation (LER) into the model as new ER indicators. The outcomes are displayed in
Table 8. Model 16 shows that the CER and DPI continue to have a U-shaped connection.
It is worth noting that there are still some variations in how local governments implement national environmental legislation. According to the regression results from models 17–20, LER showed a U-shaped relationship for all DPI for non-primary production areas, the same as the total sample regression results in model 17. However, an inverted U-shaped relationship is shown for the main production areas. A possible reason for this is that the efficiency of local government regulation in key production regions frequently varies with economic, political, and ecological aims. Due to “GDP competitiveness” and “vegetable basket responsibility”, the government may also develop subsidy policies to promote farming and expand farming, while enforcing environmental legislation policies. In doing so, it will lessen the financial pressure on farmers to comply with environmental regulations while simultaneously achieving environmental protection and boosting the pig industry’s sustainable development. This is in line with the findings of Zhao et al., who postulate that the impact of ER is positively correlated in those with high levels of economic development and U-shaped in other places [
74]. This shows that under the direction of varied aims, the consequences of environmental control in key production areas produce distinct results.
When reviewing the regional heterogeneity results of models 5–6, the regression results of total environmental input indicators on regional environmental regulation policies are also controversial in the medium-production areas. The possible reason is that most of the middle-producing regions are eastern coastal cities with a concentration of people and industrial development, and industry, as the main output of GDP in the region, is the focus of environmental inputs, which also crowd out the environmental inputs of livestock and poultry farming. From the regression results of the environmental policy for livestock and poultry in the mid-production areas, the implementation of environmental policy in the mid-production areas still follows the assumption of the short-term cost effect and the long-term innovation compensation effect.
6. Conclusions
This study explores the influencing effects of ER on the DPI under multiple dilemmas by using FGLS and system-GMM, using panel data from 30 Chinese provinces collected from 2005 to 2019. To begin with, considering the longer value chain and more multi-dimensional objectives of the pig industry, we created the assessment indicator system for the development of the pig industry chain focused on the seven links of “fine seed breeding, feed production, pig health, pig breeding, resource utilization, slaughter and processing, and consumption” with the entropy weight method. Experimental findings indicate that DPI in the main production areas is higher than in the mid-sized and low-sized production regions. The industrial chain’s middle link has a big impact on DPI, as seen from an industrial chain perspective. Secondly, the empirical findings indicate that in the primary- and low-pig-production zones, ER and DPI have a positive U-shaped connection. Furthermore, to investigate the moderating effect relationship between ER and DPI, the interaction variables of TI and LSF with ER were introduced, respectively. It was discovered that TI and LSF might lessen the detrimental effects of ER on DPI. That is to say, the large-scale transformation strategy’s combined effects hasten the creation of the “Porter hypothesis” and the coming of the environmental regulatory tipping point. Furthermore, there are also considerable differences in how local governments apply national environmental policies. The LER has an inverted U-shaped connection with DPI in the main producing areas and a U-shaped in the non-major producing areas. Based on the aforementioned empirical findings, this article makes the following policy recommendations.
- (1)
The gap in how local governments apply environmental regulation suggests that the environmental supervision mechanism of livestock and poultry needs to be improved. Localities implemented a discretionary decision-making mechanism based on the pig cycle to balance the policy’s multiple objectives. Such subjective government intervention, in turn, tended to accelerate the pig-cycle process. Therefore, it is essential to build an environmental performance evaluation system that takes into account local conditions as well as scientifically constructs and enhances the rules and regulations on animal husbandry environmental protection.
- (2)
Scale transformation benefits the growth of the pig industry. Coordination between short- and long-term policies is essential. Short-term policies focus on the scale-up process of pig production. The long-term policy priority should be to encourage firms and farmers to innovate technologically, raise fundamental R&D investment, and promote green farming via the “innovation compensation” effect, to balance rising production costs. In the transitional period of technical innovation and industrial transformation, we should optimize the centralized treatment mechanism of pig manure pollution under government subsidies, support the large-scale transformation of the industry, and assure stable production and supply.
- (3)
The breeding link is an important link to the development of the industrial chain. Therefore, it is crucial to improve the risk management ability of pig breeding. First of all, based on the core regulatory indicators of breeding sows, dynamic assessment should be carried out in provinces and regions with sudden epidemic risks. Secondly, an industrial chain coordination mechanism should be established to strengthen the comprehensive coordination of factor supply and price stabilization of node enterprises or farmers on the chain through technology, market, and financing relations. Thirdly, it should strengthen the inter-temporal transformation mechanism of systemic risk in the industrial chain based on “live pig futures + insurance,” and guide financial institutions in providing risk management services that encompass the entire industrial chain, such as hedging and insurance.