1. Introduction
Green development has become a shared goal worldwide in recent years [
1], and its essence is centered on the coordinated development of ecology and economy [
2]. Numerous countries worldwide, including the United Kingdom with its Low Carbon Transition Plan, the United States implementing the Clean Energy and Security Act, Japan formulating the 2050 Carbon Neutral Green Growth Strategy, and Germany promoting the Renewable Energy Sources Act, have all actively pursued strategies to advance green development. China is not an outlier in this regard, and ever since the Fifth Plenary Session of the 18th CPC Central Committee introduced the idea of green development, the Chinese government has increasingly prioritized the eco-friendly transformation of the economy.
Pig breeding has long been a fundamental sector of agricultural business in China [
3,
4,
5] and plays a significant role in the rural economy [
6]. China holds the title of being the largest consumer and producer of pork globally. As reported by the China National Bureau of Statistics, pork production in China in 2021 reached a staggering 52.96 million tons. This accounts for 59.59% of the total output of livestock and poultry meat in the country and 44.09% of the global proportion, securing the position of China as the top pork producer in the world. Furthermore, China was projected to obtain over 50% of the worldwide pork supply in 2021 [
7].
Globally, pollution issues arising from pig breeding have become increasingly severe. Notably, the marine environment of South Korea faces significant threats from inland fecal pollution sources [
8]. In Poland, there exists the risk of improper storage and excessive application of pig slurry, which may lead to water, soil, and plant contamination by heavy metals [
9]. China, too, confronts environmental pollution challenges stemming from pig farming, which cannot be overlooked. China has experienced a surge in air and water pollution in recent years [
10]. As the largest producer of livestock globally [
11], China has been recognized for the significant contribution of its livestock industry to air pollution [
12] and water pollution [
13]. The Second National Pollution Source Census Bulletin reported that in 2017, livestock and poultry farming contributed to water pollution by emitting 10,053,000 tons of chemical oxygen demand, 110,900 tons of ammonia nitrogen, 596,300 tons of total nitrogen, and 119,700 tons of total phosphorus. These emissions accounted for 46.67%, 11.51%, 19.61%, and 37.95% of the national total, respectively. Pig breeding, being a significant component of the livestock sector, has resulted in a range of environmental issues with its rapid growth [
4,
6,
14,
15]. For example, the presence of pollutants such as pig manure from pig breeding can lead to a decline in air quality and contamination of water quality [
7].
To tackle the pollution issues caused by pig breeding, which cannot be resolved by market forces alone, the Chinese government has implemented a set of environmental regulations (ER) [
10]. In 2013, the China State Council issued Regulations on Pollution Prevention and Control of Livestock and Poultry Scale Breeding to tackle the problem of pollution caused by livestock and poultry breeding. These regulations are regarded as the most rigorous water pollution prevention and control measures for pig breeding in China up to now [
15]. In 2015 and 2016, the Ministry of Agriculture released two documents titled Guidance Opinions on Promoting the Adjustment and Optimization of Pig Farming Layout in Southern Water Network Areas and Pig Industry Layout Adjustment Program in Southern Water Network Areas. These documents signaled a new phase of ER in the pig industry [
3].
The Yangtze River is the primary river that traverses the west–central and east–central regions of China. It serves as the core point for the economic progress of China, contributing to around 50% of the national total economic output [
16]. Hence, safeguarding the ecological integrity of the Yangtze River Basin is of immeasurable significance in upholding national environmental security and achieving sustainable development for the Chinese country [
17]. Nevertheless, due to the swift economic expansion of China and escalating water contamination, the condition of the Yangtze River Basin ecosystem has persistently worsened, with pig breeding being a notable contributor to water pollution [
18]. For this reason, the Chinese government formally passed The Law of the People’s Republic of China on the Protection of the Yangtze River on 26 December 2020, as the first specialized law for the ecological protection of the basin in China, highlighting the commitment of the state to safeguarding the environment of the area.
Encouraging green development of pig breeding has emerged as a significant approach to achieving high-quality growth in the business [
19]. Furthermore, there is indisputable evidence about the efficacy of ER in fostering green development [
20]. ER is considered to be the non-market mechanism for addressing the issue of pollution externalities [
21], and it can successfully manage the pollution issues associated with pig breeding. The drawback lies in the fact that ER impacts the growth of the pig sector to some degree [
22], especially in production capacity [
15]. In 2019, the China Ministry of Agriculture and Rural Development promulgated the Opinions on Stabilizing Pig Production and Ensuring Market Supply. In 2024, this was followed by the issuance of the Implementation Plan for Pig Production Capacity Control. These documents emphasized the significance of maintaining a stable pig production and ensuring an adequate supply. To incorporate both the objective of green development and the preservation of production capacity in the analysis framework, how can the pig breeding sector effectively embrace this opportunity without causing excessive harm? Which indicators should be utilized to quantify it?
Green total factor productivity (GTFP) offers a potent solution to the aforementioned difficulties. To foster long-term economic growth, a significant reliance is placed on the enhancement of factor productivity [
23]. Furthermore, GTFP, a pivotal component of new quality productive forces, embodies innovative allocation of production factors and profound industry transformation, being essential for modern advanced productivity. However, with the implementation of several environmental rules, the traditional total factor productivity is no longer sufficient to estimate the productivity of pig breeding in the Yangtze River Basin. GTFP incorporates resource consumption, pollution emission, and other resource and environmental limitations, aligning with the concept of green development in the modern era [
21,
24]. It serves as a comprehensive measure of economic and ecological environmental performance [
20,
25]. A higher level of GTFP means that pig breeding is capable of achieving sustainable development by efficiently utilizing resources and minimizing environmental degradation while also promoting economic growth [
19].
Many scholars have conducted extensive research on the impact of ER in different fields, including green total factor productivity [
26], green technological innovation [
27], outward foreign direct investment [
24,
25,
28], industry size [
29], corporate environmental responsibility [
30], economic growth and CO
2 emissions [
31], corporate ecological and innovation performance [
32], and ecological behavior [
33]. Meanwhile, GTFP is also increasingly favored by researchers. Its influencing factors include trade openness [
21], foreign direct investment [
25], green credit [
34], clean technology innovation [
35], green finance [
36], and urban land use [
37]. Some scholars use a linear model to study the effect of ER on GTFP, another group believes that the two have a nonlinear relationship and uses the inclusion of a quadratic term to fit it, but most scholars believe that the inclusion of a quadratic term does not reflect the nonlinear relationship well, and so they use a panel threshold model to construct it [
1,
21,
24]. However, there is a gap in the literature on the specific impacts of ER on GTFP in pig breeding. There is a limited amount of research that has focused on investigating ER in the livestock industry [
10], and even fewer studies have examined the impact of ER on GTFP in pig breeding. Amid the scarce research available, the GTFP of pig farming was measured in China from 2004 to 2017 and the dual roles of ER were examined including pollution reduction and efficiency enhancement [
38], making significant contributions. However, their use of provincial GDP to measure the intensity of ER is less precise than a number of environmental regulatory policies used in this study, and their empirical analysis of ER and GTFP is not thorough, only touching the surface of the impact. By the fixed-window Malmquist–Luenberger (FWML) index, another study measured the GTFP of pig breeding, and, subsequently, the economic benefits and environmental pollution costs under the influence of environmental regulations were analyzed [
6]. Compared to [
38], they did not delve deeply into the relationship between ER and GTFP in pig breeding or the underlying mechanisms of this impact but predicted pig price using long short-term memory (LSTM) neural networks. Therefore, this paper tries to fill critical gaps in the existing literature by systematically and comprehensively analyzing the effects of ER on GTFP in pig breeding.
Based on panel data from 2014 to 2021, this paper examines the impact of ER on the GTFP of pig breeding across 381 counties in the Yangtze River Basin. This paper devotes a significant portion to the application of the threshold models, with further research also encompassing the double difference model and linear model. When the ER increases, it may prompt pig farming entities to develop new technologies or improve production efficiency, resulting in a significant increase in their green total factor productivity. However, once ER exceeds a certain value, input continues to increase, but output efficiency cannot continue to rise efficiently. Therefore, their green total factor productivity may slightly increase or even decrease. Based on this consideration, this paper studies the nonlinear impact of pig ER on their green total factor productivity by using threshold models. To explore the impact of different degrees of ER on green total factor productivity, mainly through efficiency improvement or technological improvement, this article decomposes green total factor productivity into technical efficiency (MLEC) and technological progress (MLTC). The findings reveal there exist double threshold effects of ER on GTFP, MLEC, and MLTC. On the one hand, as ER increases, it first enhances the promotion of GTFP and MLTC. However, this effect later decreases. On the other hand, the impact on MLEC changes from being insignificant to solid promotion, and it eventually becomes a significant inhibitor. In investigating the mechanism, this paper applies two-panel threshold models to explore the effects of the level of pig mechanization and the level of pig industry agglomeration on ER, respectively, and it is proved that both of them have significant single-threshold effects on ER. So, ER enhances the growth of GTFP through two pathways: by increasing the level of pig mechanization and reducing the level of pig industry agglomeration. Furthermore, the heterogeneity tests and moderating effects in this paper also consistently use panel threshold models. The heterogeneity study reveals that various county characteristics, such as whether it spans the Yangtze River main stem, whether it is located in a provincial capital city, and the distance between the government and the Yangtze River, would result in distinct threshold effects. The investigation of the moderating role reveals that parameters such as pig price and transportation operation efficiency both have moderating effects on the impact of ER on GTFP, MLEC, and MLTC. To address the potential issue of endogeneity between ER and GTFP, this paper employs the environmental regulatory intensity of other counties within the province (ERAOP) as an instrumental variable. Based on the combined consideration of the application of the panel threshold model and the principles of the instrumental variable approach, the endogeneity exploration in this paper is carefully divided into two stages. In the first stage, this paper applies a linear model to deeply analyze the effect of the instrumental variable ERAOP on ER, aiming to accurately estimate and obtain the fitted value of ER after incorporating the environmental regulation factors of other counties in the province. In the second stage, this study turns to the panel threshold model to further explore the specific effects on GTFP centered on the fitted values of ER derived in the previous stage, so as to effectively address and circumvent the potential endogeneity problem of the threshold model.
As can be seen from the above, ER has heterogeneous promoting effects on the green total factor productivity of pigs, but whether it increases pig production capacity while reducing its carbon emissions needs further exploration. Additional evaluations indicate that ER has a suppressive impact on both pig production capacity and carbon emissions. However, the advantages gained from reducing carbon emissions surpass the drawbacks of declining production capacity, hence improving GTFP. Moreover, ER efficiently decreases the concentration of ammonia nitrogen in the Yangtze River, hence improving water quality. In order to further reverse validate the potential conflicts in the impact of ER on GTFP and pig production capacity, this study uses a double difference model to examine the impact of the reduction of livestock prohibition zone policy intensity in certain counties in 2019 on GTFP, MLEC, MLTC, and production capacity. The findings indicate that the enhancement of ER helps to increase GTFP of pig breeding but may have some negative impacts on production capacity, whereas when ER decreases, GTFP decreases despite the significant increase in production capacity.
This research makes significant progress in the following four aspects, enriching the findings of previous studies: (1) County data: This paper uses data from 381 specific counties within the Yangtze River Basin to conduct a more precise and detailed study of how ER in pig breeding affects GTFP. This approach not only overcomes the limitations of using provincial data [
19,
25,
34,
39], which makes it challenging to accurately understand the complex relationship between ER and GTFP due to the broad scope of the study but also significantly reduces the statistical error of the data and provides a more detailed and targeted reference for the formulation of environmental regulatory policies. (2) Pig breeding: This paper significantly contributes to the study of how ER affects GTFP in pig breeding. In the existing literature studying the impact of ER and GTFP, most of them focus on the industry [
19,
34,
40,
41,
42], the manufacturing sector in the industry [
20,
41], overall agriculture [
24,
43], and so on. In addition, historical research involving GTFP in pig breeding has only measured and analyzed it [
4,
5,
19,
44], whereas there are few studies on the association between ER and GTFP pig breeding. Only one article on dairy farming [
1] is more relevant to this paper. However, this article only employed provincial data and the urban–rural income gap as a threshold variable to study the impact without studying its impact mechanism and endogeneity. With the aim of addressing the shortage in pig breeding in the area, this paper uses the SBM-ML model to assess the GTFP of pig breeding in the Yangtze River Basin and further decomposes it into two dimensions: MLEC and MLTC. More importantly, the ER discussed in this paper is not the traditional overall regulation measured by economic indicators, but rather, the ER for pig breeding, which was synthesized using the entropy weight method after searching for policies from the national level to the county level. Through the in-depth analysis of these critical variables, this paper not only reveals the influence mechanism of ER on GTFP of pig breeding but also integrates the dual objectives of economic growth and environmental protection to provide reliable suggestions for the green development of pig breeding. (3) Panel threshold model: This research is the first to integrate the panel threshold model into the analytical framework of ER and GTFP in pig breeding. Previous studies on ER and GTFP in other industries have typically used the threshold model as a supplementary or essential extension of the primary model [
39], or very simply to explore whether there is a threshold effect [
40], and they seldom explore in depth the nonlinear relationship between ER and GTFP. Different from them, this paper comprehensively and thoroughly applies the threshold model, validating the reliability of the research results from the dimensions of robustness and endogeneity. Furthermore, threshold models are employed in mediation, moderation, and heterogeneity analyses, ensuring consistency and coherence throughout the analytical framework, thereby providing empirical evidence for the application of the threshold model. (4) Policy evaluation: A large number of studies suggest that since 2017, the policy of prohibiting livestock breeding has become increasingly strict, seriously harming the development of the pig industry, especially in 2019. Due to the sharp decline in China’s pig production capacity in 2019, the government decreased the intensity of environmental regulations, but no relevant research has explored the effectiveness of this policy. This paper tries to fill the gap.
The following sections of the paper are structured as follows:
Section 2 conducts a theoretical analysis by drawing upon existing literature and formulating the research hypotheses.
Section 3 provides an overview of the data sources and research methods employed in this research.
Section 4 includes the threshold effect test, robustness examination, impact mechanism, heterogeneity test, moderating effect analysis, endogeneity discussion, and further research.
Section 5 summarizes the conclusions of the study and puts forward corresponding policy recommendations.
5. Conclusions and Policy Implications
This research conducts an in-depth investigation of the impact of ER on GTFP using panel data from 381 counties in the Yangtze River Basin between 2014 and 2021. During the research process, this paper applies the panel threshold model and conducts a robustness examination, as well as the threshold effect test, including mechanism analysis, exploration of regional heterogeneity, examination of the moderating role, and endogeneity treatment to ensure the comprehensiveness and accuracy of the research results. This research makes the following main conclusions based on our rigorous empirical analysis:
(1) First, this study conducts a nonlinear investigation using the panel threshold model, with ER serving as the threshold variable. The results reveal that as ER intensity increases, the promotion effect on GTFP and MLTC of pig breeding initially rises and then falls, whereas the influence on MLEC varies from negligible to significant positive effect, then to significant negative effect. Based on this, this paper strongly believes that ER has a positive impact on GTFP of pig breeding in the Yangtze River Basin, with the core of this impact being to promote technological innovation among pig breeders to improve MLTC, rather than to improve MLEC by optimizing management level and production realization ability. Furthermore, this article indicates that the intensity of ER should not be maximized but should be controlled within an acceptable range in order to contribute to the green and long-term development of pig breeding.
(2) Secondly, from the perspective of mechanism analysis, this paper argues that the ways for ER to enhance GTFP may include two aspects: First, by increasing the mechanization level of pig breeding in the Yangtze River Basin, we can achieve large-scale development, optimize resource allocation, and reduce carbon emissions, thus enhancing GTFP and achieving the goal of ecological environmental protection. Second, by reducing the level of industrial agglomeration in pig breeding, the concentration of environmental pollution will be reduced, improving the utilization rate of regional resources and creating favorable conditions for breeding entities that can seize green development opportunities, thus increasing their GTFP.
(3) After considering heterogeneity, moderating effects, and further analysis, this paper finds that the threshold effect of ER on GTFP exhibits different characteristics due to regional differences. Specifically, under low-strength ER, compared with the counties that did not cross the Yangtze River main stem, the counties that crossed the Yangtze River main stem showed more significant enhancement in MLTC but also stronger suppression of MLEC, resulting in a limited enhancement effect on the overall GTFP. In addition, the effect of ER on GTFP is more pronounced in non-capital city counties where pig breeding is more developed. At the same time, when the ER intensity is low, the promotion of GTFP is stronger in areas where the county government is farther away from the Yangtze River, but the opposite is true beyond a certain ER intensity. Moreover, the moderating factors such as pig price and transportation operation efficiency also show significant differences in the moderating effects of GTFP, MLEC, and MLTC in different ER intervals. Finally, increasing ER reduces production capacity but significantly reduces carbon emissions, and the environmental benefit of reducing carbon emissions outweighs the economic benefit of losing production capacity, resulting in the final increase of GTFP. However, decreasing ER will substantially boost production capacity while decreasing GTFP. Especially noteworthy is that the ER effectively improves water quality in the Yangtze River Basin and implements the ER of the Yangtze River Basin. This means that the core objectives of ER in the Yangtze River Basin have been achieved.
On the basis of the above conclusions, the paper makes the following three policy recommendations: (1) Optimizing ER policy design. The Chinese government should keep ER within a reasonable range to allow for scientific formulation and timely adjustment of policy intensity. The empirical results show that ER intensity does not improve the higher it is, but there exists an intermediate range, which has the most significant promotion effect on GTFP of pig breeding. In addition, due to regional heterogeneity, the threshold effect of ER on GTFP varies significantly among regions with different characteristics, so the policy formulation needs fully consider the actual situation of each region and formulate and implement the ER policy according to the local conditions. (2) Facilitating the improvement of MLEC in pig breeding. From the results of SBM-ML, it can be seen that the main factor driving the improvement of GTFP in pig breeding is MLTC, so the improvement of MLEC needs to be strengthened. For instance, the Chinese government can encourage the main body of breeding to adopt advanced breeding technology and management mode, optimize the allocation of resources, and improve production efficiency by providing technical support, financial support, and talent training. In addition, the government can also establish a technical exchange and cooperation platform to promote the sharing of experience and technological innovation among pig breeders so as to jointly promote the green transformation of the pig breeding industry as well as the development of new quality productive forces in response to the advocacy of China. (3) Provide suitable environmental subsidies to pig farmers. Further analysis reveals that ER reduces pig production capacity, resulting in lower farmer income. To balance the relationship between environmental conservation and economic development, the Chinese government should provide suitable environmental subsidies to pig farmers. These subsidies can not only compensate farmers for economic losses caused by ER but also serve as an incentive mechanism to encourage farmers to pay more attention to environmental protection within their own means, actively implement environmental protection measures, reduce pollution emissions, and practice green farming. At the same time, the government should tighten oversight and review of subsidized funding to ensure that funds are used transparently and effectively.