Impact of Environmental Protection Tax on carbon intensity in China.

In the context of increasingly severe global climate change, finding effective carbon emission reduction strategies has become key to mitigating climate change. Environmental Protection Tax (EPT), as a widely recognized method, effectively promotes climate change mitigation by encouraging emission reduction behaviors and promoting the application of clean technologies. Based on data from 282 cities in China, this paper takes the official implementation of the EPT in 2018 as the policy impact and the cities with increased tax rates for air taxable pollutants as the treatment group and uses DID model to systematically demonstrate the relationship between the implementation of the EPT and carbon intensity (CI) and further explores the possible pollutant emissions and green innovation mediating effects. The findings show that (1) the implementation of EPT can effectively reduce CI by about 4.75%, and this conclusion still holds after considering the robustness of variable selection bias, elimination of other normal effects, policy setting time bias, and self-selection bias. (2) The implementation of EPT can reduce CI by reducing pollutant emissions and improving the level of green innovation. (3) There is obvious regional heterogeneity in the carbon reduction effect of EPT, and the implementation of EPT has a more significant effect on CI in medium-tax areas, low environmental concern areas, general cities, and eastern regions. This paper not only provides a new analytical perspective for systematically understanding the carbon emission reduction effect of EPT but also provides policy insights for promoting regional green transformation and advancing carbon peak carbon neutralization.

Evaluation the impact of electricity consumption on China's air pollution at the provincial level.

As the world's largest electricity-consuming country, China faces the challenge of energy conservation and environmental pollution. Therefore, it is imperative that China takes decisive action to address these issues. Based on the panel data of 30 provinces (cities, districts) in China from 2011 to 2020, we use the entropy method to measure the air pollution index in different provinces, construct two fixed effects models, panel quantile model, and spatial Durbin model to empirically analyze the impact of electricity consumption on air pollution in China's provincial regions. The experimental results show that: (1) Electricity consumption has a significant positive impact on the provincial air pollution index in China and the higher the index is, the more serious the air pollution is. When the electricity consumption increases 1%, the air pollution index will increase of by 0.0649% as accompanied. (2) Through comparison of different times, we found that the degree of increase in air pollution index caused by electricity consumption would be reduced due to the improvement of environmental protection efforts. From the perspective of different geographical locations, the electricity consumption in the southeast side of the "Hu Line" has exacerbated the impact on air pollution index. (3) According to the panel quantile regression results, the marginal effect of electricity consumption on air pollution is positive. With the increase of quantiles, the impact of electricity consumption on air pollution is increasing. (4) Spatial effect analysis shows that electricity consumption has a significant positive spatial spillover effect on air pollution index. The increase in electricity consumption not only increases the air pollution index in the local region, but also leads to an increase in the air pollution index in surrounding areas. These findings contribute to the governance of air pollution and the promotion of sustainable economic, environmental and energy development.

The impact of foreign direct investment on green innovation efficiency: Evidence from Chinese provinces.

Improving green innovation efficiency (GIE) is the key to achieve high-quality economic development in China, and the introduction of foreign direct investment (FDI) has become an important path choice to promote the GIE. Based on the data of 30 provinces in China, this paper explores the linear and nonlinear effects of FDI on GIE from both quantity and quality perspectives, and further analyzes the mediating role of environmental regulation level. The results show that: (1) From 2011 to 2020, the GIE of all provinces in China generally shows an upward trend. (2) The quantity and quality of FDI have a significant positive impact on the improvement of GIE in China's provinces, and this impact has regional heterogeneity. (3) The quantity and quality of FDI can promote the improvement of GIE in China through the level of environmental regulation (ER). (4) With the level of knowledge accumulation and GIE as the threshold variables, the quantity and quality of FDI have a single threshold effect on the GIE of China's provinces. The conclusions of this study provide some policy implications for local governments to make full use of FDI to perform green innovation activities.

The impact of digital economy on environmental pollution: Evidence from 267 cities in China.

Environmental pollution has become a pressing global issue, severely threatening human health and ecosystems. As an emerging driver of economic development in countries worldwide, the digital economy (DE) has the potential to enhance resource utilization efficiency and promote the development of clean technologies, thereby reducing environmental pollution. Based on the panel data of 267 cities in China from 2012 to 2021, the spatial econometric model is used to test the impact of DE on environmental pollution. The mediating effect model is used to explore the transmission mechanism of DE affecting environmental pollution. The panel threshold model is used to examine the threshold effect of marketization. The results are as follows: (1) DE can significantly reduce environmental pollution. The conclusion is still valid after conducting robustness tests such as selecting historical data as instrumental variables and the "Broadband China" pilot as a quasi-natural experiment. (2) From the perspective of transmission mechanism, DE can reduce environmental pollution through green technology innovation and industrial structure upgrading. (3) From the perspective of spatial spillover effect, DE can reduce the environmental pollution level of surrounding cities. (4) From the perspective of threshold effect, DE has obvious market-oriented single threshold effect on environmental pollution. When the marketization level crosses the threshold of 11.6611, the emission reduction effect of DE is significant. (5) From the perspective of heterogeneity, DE has a heterogeneous impact on environmental pollution in cities with different geographic locations, resource endowments and administrative level. Regarding geographical heterogeneity, DE can effectively reduce environmental pollution in eastern and central regions, but has no significant impact on environmental pollution in western regions. Regarding the heterogeneity of resource endowment, compared to non-resource-based cities, resource-based cities suffer more from the negative effects of DE on their environment. Regarding the heterogeneity of administrative levels, compared with non-central cities, the DE of central cities has a greater emission reduction effect. Based on empirical results, this paper proposes strategic recommendations in areas such as enhancing the application of DE in emission reduction, upgrading industrial structures, promoting green technology innovation, and improving the level of marketization. This study not only enriches the research of DE and environmental pollution, but also provides a reference for the formulation of environmental pollution control policies.

The efficiency of China's freshwater fishery breeding: nonparametric data envelopment analysis based on interprovincial data.

Studying the economic efficiency of freshwater fishery breeding is of great significance to the sustainable utilization of freshwater fishery resources. Based on the nonparametric research method, this study combines the super-SBM data envelopment analysis (DEA) model with the global Malmquist index (GMI) to evaluate the total factor productivity of freshwater fishery breeding (FTFP) of China from 2004 to 2019, so as to reflect the economic efficiency of freshwater fishery breeding in China. The empirical results show that (1) in general, FTFP has reached the effective level in China with a fluctuating trend in time, but it lacks a breakthrough value. (2) In China, FTFP shows significant differences in space, and its spatial development pattern has gradually evolved from "high in the south and low in the north" to "high in the north and low in the south." (3) The change of FTFP in China mainly depends on technological progress, while the change of scale efficiency and pure efficiency has no significant impact on it. (4) When environmental factors are taken into account, the FTFP value will decrease as a whole. Therefore, it is very important to optimize the structure of freshwater fishery breeding and strengthen the construction of aquatic science and technology system.

Impact of digital finance on energy-based carbon intensity: Evidence from mediating effects perspective.

This research measures energy-based carbon intensity based on energy consumption of 30 Chinese provinces and investigates the impact of digital finance. First, the baseline results were examined through panel data model. Second, we reveal the "black box" system of digital finance and energy-based carbon intensity through mediating effects model. Third, by employed panel quantile regression model, we examine the heterogeneity of the effects of various factors under different carbon intensity quantile. The main quantitative results are as follows: (1) Digital finance shows significant sustainable effect, and its growth of 1% will reduce the carbon intensity by about 0.092%. (2) The intermediary effects of technological innovation and energy structure are -0.0663 and 0.007, respectively, accounting for 41.88% and 19.36% of the total effects. Both are significant transmission mechanisms. (3) When the carbon intensity in >0.9 quantile, digital finance shows a positive coefficient. On the contrary, the coefficient at <0.75 quantile is negative and its absolute value increases with the decrease of quantile. It shows that with the reduction of carbon intensity, the positive impact of digital finance gradually increases. (4) In the eastern, central and western regions, a 1% increase in digital finance will reduce the carbon intensity by 0.147%, 0.096% and 0.089% respectively. This research provides a reference for regional governments to use digital finance tools to promote sustainable development.

Impact of urban innovation ability on industrial pollution governance in Chinese cities: taking the Yangtze River Economic Belt as an example.

This paper uses spatial measurement method, by selecting panel data from a total of 106 cities in 11 provinces and municipalities in the Yangtze River Economic Belt from 2006 to 2018, to conduct an empirical study on the impact mechanism of urban innovation ability on industrial pollution governance. The results show that there is a significant negative correlation between urban innovation ability and the degree of industrial pollution, and cities in the Yangtze River Economic Belt have a significant spatial connection. Specifically, this paper finds that urban innovation ability can have a positive impact on urban industrial pollution governance through industrial selection, production technology innovation, pollution discharge technology innovation, and environmental pollution treatment, which will help cities reduce industrial pollution; The industrial pollution governance level of individual cities is not only affected by the innovation ability of the city, but also by the innovation spillover of the surrounding cities. Area surrounded by cities with high urban innovation ability will benefit from the spillover of the surrounding cities. The industrial pollution governance level of individual cities is not only affected by the innovation ability of the city, but also by the innovation spillover of the surrounding cities. Areas surrounded by cities with high urban innovation ability will benefit from the spillover of the surrounding cities, thus improving the industrial pollution control and regional ecological environment. Based on this, this paper proposes relevant policy recommendations for urban industrial pollution governance from the perspective of improving urban innovation ability.

Measure on innovation efficiency of China's pharmaceutical manufacturing industry.

Pharmaceutical manufacturing industry is an important industry to ensure human life safety. The innovation efficiency is a significant factor to stimulate the development of pharmaceutical manufacturing industry. At present, there are few studies on the innovation efficiency of pharmaceutical manufacturing industry. To fill this gap, this paper estimates the innovation efficiency of China's pharmaceutical manufacturing industry in 23 provinces of China from 2010 to 2020 based on the super-network SBM model and Global-Malmquist index. The results show that: (1) From the perspective of efficiency of research and development stage (ERDS), the ERDS of China shows an increasing trend, with the most prominent growth in the western region. (2) From the perspective of efficiency of economic transformation stage (EETS), although there are fluctuations in the EETS, the overall development is good. The EETS of the central region and western region is better than that of the eastern region. (3) By comparing the efficiency of the two stages, it is found that the change direction of the efficiency of the two stages is not necessarily the same in some provinces.

The inhibitory effect of agricultural fiscal expenditure on agricultural green total factor productivity.

Sustainable development of agriculture is the basis for achieving social sustainable development. As the basic industry of national economy, green development of agriculture has become an important support for building an environment-friendly society. Agricultural fiscal expenditure is a direct channel for the government to support agriculture and promote agricultural transformation. It is important to analyze the impact of agricultural fiscal expenditure (AFE) on agricultural green total factor productivity (AGTFP) for sustainable agricultural development. Therefore, this paper employs the random effect model and spatial Durbin model to empirically analyze the direct effect and spatial spillover effect of AFE on AGTFP by using the agricultural panel data of 30 provinces in China from 2008 to 2020. Then, by taking the policy proposal as the time node, this paper also conducts a time heterogeneity analysis to measure the impact of policy enactment on AFE and AGTFP. The main conclusions are as follows: (1) AGTFP exists significant positive spatial spillover effect. The "radiation effect" of agricultural green development is significant. (2) AFE can significantly reduce the AGTFP in the local area, that is, 1% increase of AFE in the local area will reduce AGTFP by 0.037%. At present, agriculture is still yield-oriented. The improvement of AFE in the local area will lead to the expansion of local agricultural production and increase pollution emission. (3) AFE has a significant negative spatial spillover effect on AGTFP, that is, for every 1% increase in AFE, the AGTFP will decrease 0.123% in geographically similar areas, while the AGTFP will decrease by 0.116% in economically and geographically similar areas. It is obvious that AFE will promote the optimization of agricultural production conditions in the province, with the "demonstration effect" on the surrounding areas, the enthusiasm of production in the surrounding areas will increase, thus expanding the pollution emission. (4) According to the analysis of different periods, AFE has a negative impact on AGTFP mainly before the reform innovation is proposed in 2015. It indicates that reform policies have a significant impact on agricultural sustainability.

Does digital inclusive finance promote industrial transformation? New evidence from 115 resource-based cities in China.

Industrial transformation (IT) is the inevitable course for the sustainable development of resource-based cities, while digital inclusive finance (DIF) provides essential capital elements for industrial transformation. Based on the panel data of 115 resource-based cities in China from 2011 to 2019, this paper discusses the influence mechanism of digital inclusive finance on industrial transformation from the perspectives of the optimization of industrial structure (OIS) and the rationalization of industrial structure (RIS). The empirical results show that digital inclusive finance has a positive effect on both the optimization of industrial structure and the rationalization of industrial structure. Digital inclusive finance influences industrial transformation through residents' income and technological innovation. In addition, in the analysis of income gap and innovation gap, low-income regions have a better effect on the industrial transformation of industrial structure optimization, while high-income regions have a better effect in manufacturing upgrading, thus resulting in a more significant effect of industrial transformation on the rationalization of industrial structure. Obviously, the development of high-innovation regions has relative advantages with more channels for industrial transformation, which have significant effect of industrial transformation. Therefore, it is necessary to provide differentiated reform on the basis of unified development reform.

Does green innovation suppress carbon emission intensity? New evidence from China.

The sustainable development of human beings is facing severe challenges in the context of a new era. The effective reduction of carbon emission intensity is essential to achieve the goal of sustainable development. Obviously, green innovation is an important factor in mitigating carbon emission intensity. It is important to measure the effect of green innovation on carbon emission intensity for accelerating industrial transformation and building a circular economy system. Therefore, this paper uses the data of 30 provinces in China from 2000 to 2019, obtained by the State Intellectual Property Office, using fixed effects model quantile regression model and Spatial Durbin Model to empirically verify the theoretical hypothesis. The conclusions are as follows: (1) Green innovation inhibits carbon emission intensity. Instrumental variable model and robustness test support this conclusion. (2) For carbon emission intensity under different quantiles, green innovation has a more significant effect on provinces with high carbon emission intensity through "target accountability system" and "reverse coercive system." (3) There is a significant spatial correlation between green innovation in China's provinces. The reduction of carbon emission intensity in the region will benefit from the improvement of green innovation in surrounding cities.

Industrial green total factor productivity in China's Yangtze River Economic Zone: Temporal and spatial difference analysis based on 108 panel data.

As China's strategic support belt, the green development of industry in the Yangtze River Economic Zone is of great significance to promote the construction of China's ecological civilization, build a modern industrial system and accelerate high-quality economic development. The study of green total factor productivity of industry in the Yangtze River Economic Zone has important theoretical and practical value for exploring the green development path of China's industry. This Paper takes the Yangtze River Economic Zone, a key strategic region in China, as the research object, selects the input and output data of industrial production from 2006 to 2018, based on DEA model. To construct an MML index considering expected and unexpected output, and to quantitatively analyze the changes of industrial GTFP in the Yangtze River Economic Zone. The results show that: (1) During the sample period, the industrial green total factor productivity in the Yangtze River Economic Zone shows the spatial characteristics of differential growth and the temporal characteristics of volatile growth. It shows the fluctuation characteristics of "N" shape. (2) According to the order of "upper, middle, and lower" reaches, the spatial pattern of industrial green total factor productivity is characterized by "lower ladder". But the difference between the upper and middle reaches is small. (3) Cities with higher green total factor productivity and lower green total factor productivity each form the characteristics of "club convergence" of spatial agglomeration. (4) Technological efficiency and technological progress efficiency have heterogeneous effects on different river basins in the upper, middle, and lower reaches, and technological progress efficiency is conducive to promoting the evolution of green total factor productivity to a high level. According to the above empirical results, this paper finally puts forward the policy recommendations to improve the industrial green total factor productivity of the Yangtze River Economic Zone and the policy recommendations to reduce the industrial differences between the Yangtze River Economic Zone.

The spatial spillover effect of environmental regulation on the total factor productivity of pharmaceutical manufacturing industry in China.

As an important embodiment of a country's economic strength and national health, pharmaceutical manufacturing industry has made rapid development in China in recent years. But at the same time, the pharmaceutical manufacturing industry is facing many environmental problems, such as large pollution emissions, complex pollution components, controlling difficulties and so on. This paper measures the total factor productivity of pharmaceutical manufacturing industry (HTFP) by using data envelopment analysis with unexpected output, which is more accurate and effective than the traditional model. It also studies the effect of environmental regulation on the total factor productivity of pharmaceutical manufacturing industry (HTFP) by establishing panel data regression model and spatial econometric model based on 30 provinces in China from 2004 to 2019, which enriches the research results in the field of cleaning in pharmaceutical manufacturing industry. The conclusions are as follows: (1) Environmental regulation and total factor productivity of pharmaceutical manufacturing industry have significant spatial autocorrelation, showing "high-high" or "low-low" spatial aggregation characteristics; (2) Environmental regulation has a significant promoting effect on improving pharmaceutical manufacturing total factor productivity in local and surrounding areas, and there are differences in the impact of eastern, central and western regions; (3) Green technology, production technology and industrial structure play an important role in the impact of environmental regulation on pharmaceutical manufacturing total factor productivity, which provides theoretical guidance and policy recommendations for improving the level of total factor productivity of pharmaceutical manufacturing industry in the environmental aspect.

Analysis on the green total factor productivity of pig breeding in China: Evidence from a meta-frontier approach.

The pig industry occupies an extremely significant position in agriculture. The input cost, output income and the amount of pollution emitted by pig farming of different scales are unequal. It is of great practical importance to reduce pollutant emission by improving efficiency for the development of hog breeding industry in China. With the addition of undesirable output, this paper uses the Slack Based Measure- Metafrontier Malmquist Luenberger index model considering scale heterogeneity to explore the evolution characteristics of China's green total factor productivity of pig breeding (GTPB) based on the data of China's 17 major pig producing provinces from 2004 to 2018. The results indicate that: (1) From 2004 to 2018, China's large-scale GTPB is the highest, the medium-sized is the second, and the small-scale is the lowest. (2) In terms of regional distribution, China's GTPB in western region is the highest, in eastern region is the second, and in central region is the lowest. (3) China's GTPB shows efficiency growth and technological decline from 2004 to 2018. The pig breeding industry is generally fragile, which is greatly affected by emergencies. (4)The TGR of large-scale pig breeding is closest to 1, followed by middle-scale, and finally small-scale. According to the above empirical results, this text puts forward some policy suggestions to improve GTPB and environmental protection recommendations of hog breeding.

Effects of innovation efficiency of high-tech industries on CO2 emissions in China: A spatial Durbin econometric analysis.

As a responsible country, China should take on heavy responsibility of energy conservation and emission reduction, and it is an inevitable choice for China to develop high-tech industries and improve the innovation efficiency of high-tech industries in order to alleviate the current environmental pressure. Therefore, this paper takes the panel data of 30 provinces in China from 2005 to 2016 as the research sample, on the basis of using DEA Global-Malmquist index to measure the innovation efficiency of high-tech industries, it constructs three spatial weight matrices, by including spatial geography, spatial economic geography nesting and innovation, and then it uses Spatial Durbin Model to empirically analyze the effect of innovation efficiency of high-tech industry on CO2 emissions in China from spatial perspective. The results indicate: firstly, in China, CO2 emissions gradually increase from 2006 to 2012, however, some provinces have declined after 2012. And CO2 emissions present a descending trend from eastern coastal area to central and western region. Secondly, affected by "warning effect", CO2 emissions show a significant negative spatial spillover effect. Thirdly, the overall level of innovation efficiency of high-tech industries in China is not high, and its impact on CO2 emissions is not a simple linear relationship, but shows an "inverted N-shaped" curvilinear relation, and its decomposition index EC and TC also have similar characteristics. Obviously, the research in this paper provides a necessary theoretical support for China and some emerging developing countries to rational formulating and effective implementing the energy conservation and emission reduction policies.

Can digital finance reduce industrial pollution? New evidence from 260 cities in China.

Industrial pollution reduction is a crucial issue in the pursuit of sustainable economic and environmental development. As a product of the deep integration of traditional finance and Internet information technology, digital finance has become an effective tool for regulating the use of funds and strengthening the effectiveness of policies in the context of the digital era, which has obvious effects on industrial pollution emissions. Using panel data of 260 prefecture-level cities in China from 2011-2019 and the digital inclusive finance index jointly compiled by Peking University and Ant Financial Services Group, this paper empirically analyzes the impact of digital finance on industrial pollution emissions through fixed effects model, mediating effects model and threshold effects model. The empirical results show that digital finance can effectively reduce industrial pollution and part of the impact is achieved through industrial structure. In the process of reducing industrial pollution by digital finance, there exists double threshold effects. When the development of digital finance breaks the threshold value, the industrial pollution emission reduction effect appears to accelerate. Finally, this paper puts forward targeted suggestions to promote industrial pollution reduction and environmental economic development.

Impacts of land finance on green land use efficiency in the Yangtze River Economic Belt: a spatial econometrics analysis.

This paper uses the Global Malmquist-Luenberger Index (GMLI) based on directional distance function (DDF) super efficiency model to measure the urban green land use efficiency (UGLUE) of 108 cities in the Yangtze River Economic Belt (YREB) from 2007 to 2018, and it utilizes the spatial economic model to analyze the impact of land finance on the UGLUE and its mechanism of action. The results show that, firstly, the UGLUE in the YREB shows a steady development trend, the overall efficiency level is high, and there are spatial agglomeration characteristics. Secondly, the impact of land finance on the UGLUE presents "inverted U-shaped." With the continuous expansion of the scale of land finance, the impact of land finance on the UGLUE in the city has changed from positive to negative. Thirdly, land finance has a spatial spillover effect. Land finance will inhibit the improvement of UGLUE in surrounding areas through the "peer effect." With the continuous expansion of land finance scale, land finance will promote the improvement of UGLUE in surrounding cities through the "warning effect."

Effects of special fiscal revenue on industrial pollution and the spatial spillover: evidence from 30 provinces in China.

In China, industrial pollution is a prominent source of environmental pollution, and the important goal of sustainable development is to reduce industrial pollutant emissions, while ensuring economic stability. Special fiscal revenue (SFR) is the direct channel of government environmental regulation and the main source of environmental protection investment; it is of great significance to analyze the influence of special revenue on industrial pollution for industrial sustainable development. Therefore, this paper uses panel data from 30 provinces in China from 2005 to 2018 to empirically analyze the impact of SFR on the comprehensive industrial pollution index (CIP) and the spatial spillover effect by combining traditional regression and spatial econometric model. The empirical results show that: (1) The increase in SFR will significantly reduce the level of regional CIP emissions, and it verifies the role of SFR as a channel of government environmental regulation and a major source of special funds for environmental protection. (2) SFR exists a significant negative spatial spillover effect. For every 1% increase in SFR in surrounding provinces, the local CIP will decrease by about 0.448%, reflecting SFR has a stronger inhibition effect on CIP for surrounding areas. (3) According to the analysis of different periods, the main impact of SFR on CIP is after the new round of reforms in 2012. The sources and expenditure channels of SFR are more transparent, indicating that the institutional policies have a significant effect on emission reduction. (4) The analysis of individual heterogeneity finds that the increase of SFR in economically underdeveloped areas has a stronger inhibitory effect on CIP, and the space for technological progress in economically developed areas is small, so it is difficult to inhibit CIP in a short period of time. In addition, the instrumental variable model and robustness test support the above conclusions.

Industrial green total factor productivity based on an MML index in the Yangtze River Economic Belt.

The environmental problems caused by industrial development in the Yangtze River Economic Belt in China have become a bottleneck for urban economic development. Therefore, the measurement of the green efficiency of the urban industry in the Yangtze River Economic Belt can provide a reasonable basis for future industrial green development paths. Based on the DEA model, this study measures the industrial green total factor productivity of 108 cities in the YREB by combining the meta-frontier infrastructure framework and the Malmquist-Luenberger index. The results indicate the following: (1) The industrial green total factor productivity of cities in the Yangtze River Economic Belt declined at first and then increased from 2009 to 2016. The overall performance indicated that the structures of the technological efficiency change index and technological change index were unreasonable. The industrial green total factor productivity of midstream cities is the highest, and the difference between cities is influenced by economic development level, industrial base, transportation convenience, labor quality, and the government's emphasis on green development of industrialization. (2) Different regions have different decomposition efficiency to promote the improvement of ITFP. Considering regional heterogeneity, the industrial green total factor productivity in the middle and lower reaches of the region relies on the advantages of technical efficiency, whereas the upper reaches rely on the improvement of management efficiency. (3) The technology gap in the upper and lower reaches is small, and in the middle reaches is relatively large. Thus, according to the above empirical results, this study finally presents some policy suggestions for industrial green development in different cities of the Yangtze River Economic Belt.

Measurement of green total factor productivity on Chinese pig breeding: from the perspective of regional differences.

China has a vast territory and abundant resources, and there are significant differences in the development of pig breeding in different regions. Chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) produced in the process of pig breeding will affect China's environmental quality. In view of this, based on the Minimum Distance to Weak efficient frontier model, this paper constructs Metafrontier-Malmquist-Luenberger (MML) index considering negative output under the common frontier to comprehensively evaluate the green total factor productivity of Chinese pig breeding (GTCP). This has guiding significance for improving China's pork production and reducing pollution emissions. The results manifest that (1) no matter under the common frontier or the group frontier, GTCP presents large temporal and spatial differentiation characteristics. Compared with the central region and the western region, the eastern region has obvious advantages in GTCP. (2) GTCP has shown an upward trend as a whole, which is mainly due to the technical progress. (3) Compared with small-scale and medium-sized GTCP, large-scale GTCP has apparent superiorities. Based on the above outcomes, this paper finally raises policy recommendations for improving GTCP: (1) give full play to the advantages of pig breeding in different regions, (2) increase the research and introduction of pig breeding clean technology and improve the application efficiency, and (3) give full play to the scale effect and vigorously develop large-scale pig breeding.