Improving agricultural green total factor productivity in China: do environmental governance and green low-carbon policies matter?

Strengthening environmental governance and green low-carbon policies is a key measure to improve agriculture green total factor productivity and develop sustainable agriculture. Against this background, this study explores the relationship between agriculture green total factor productivity (AGTFP), environmental governance, and green low carbon policies based on panel data of 30 Chinese provinces from 2005 to 2019, and the system generalized method of moments model is adopted. The empirical results are as follows: (1) Environmental governance will not only directly affect AGTFP, but also indirectly affect AGTFP by influencing green technology innovation. (2) Environmental governance can strengthen the promotion of green low-carbon policies to AGTFP. (3) There are regional differences in causality among AGTFP, environmental governance, and green low-carbon policies. These empirical results offer Chinese policymakers scientific and normative recommendations for improving AGTFP and developing sustainable green agriculture.

Assessing the effect of the coal-to-gas program on air pollution: evidence from China.

This paper studies the relationship between the coal-to-gas program and air pollution in China and provides micro-evidence of the mechanism from the perspective of households. Using daily air pollution and meteorological data between January 1, 2016, and January 1, 2020, we assessed the effect of the coal-to-gas program on air pollution by introducing the regression discontinuity designs in time (RDiT). We found that the coal-to-gas program significantly improved air quality and brought significant economic benefits. In the short term, the coal-to-gas program can lead to more than 10 units of reduction in SO2, PM2.5, and AQI in the treatment group, while it can lead to more than 50 units in the long term. Using the difference-in-differences approach, we found that the coal-to-gas program has significantly reduced air pollution. Combined with the micro-panel data of the China Health and Retirement Longitudinal Study from 2011 to 2018, we found that the coal-to-gas program changes the household heating energy choices and that the probability of coal-fired heating of households in pilot areas is decreasing. The study suggests that non-clean energy in households should be further replaced to continue improving air quality.

How does risk perception of the COVID-19 pandemic affect the consumption behavior of green food?

Attention to health is on the rise with the global pandemic of COVID-19, especially in food security. Green food is viewed as a healthy, safe, and nutritious food, which plays a significant role in enhancing immunity. This study aimed to investigate how risk perception affects the consumption behavior of green food. Risk perception and health awareness were added to the original model based on the extended theory of planned behavior. And an online survey about the influence of COVID-19 on consumers' green food consumption behavior was conducted with 612 valid respondents recruited. The results indicate that risk perception has a positive effect on both consumption intention and behavior. The mediating effect analysis shows that risk perception influences green food consumption intention by improving people's attitudes, subjective norms, and health awareness. These findings can not only help clarify the relationship between green food consumption behavior and the risk perception of COVID-19 but also provide some valuable implications for policymakers and marketers in promoting green food.

Dynamic Linkages among Climate Change, Mechanization and Agricultural Carbon Emissions in Rural China.

Climate change has become a major environmental issue facing all countries, having a significant effect on all aspects of agricultural production, such as the agricultural mechanization process and fertilizer use. Greenhouse gases produced by agricultural machinery and fertilizers during agricultural production are an important cause of climate change. On the basis of the above facts, researching the connection between agricultural mechanization, climate change, and agricultural carbon emissions is crucial for the development of low-carbon agriculture and for addressing climate change. We used a variety of econometric models and methods to analyze data from China's multiple provinces (cities) covering the years 2000 through 2019, in order to meet the research objectives. Furthermore, we utilized rainfall and sunlight as variables to assess climate change and adopted Granger tests to establish the link between rainfall, sunlight, agricultural mechanization, and carbon emissions in farming. The findings indicate a bidirectional causality relationship between rainfall, sunlight, agricultural mechanization, and carbon emissions in farming. Rainfall and sunlight are Granger causes of agricultural mechanization. Furthermore, agricultural mechanization has favorable effects on carbon emissions of agriculture, and climate change has long-term implications on agricultural mechanization and carbon emissions of agriculture. Finally, this paper investigated the green path suitable for the low-carbon development of Chinese agriculture, arguing that the government should formulate low-carbon agricultural policies by region and actively promote the upgrading of agricultural machinery.

Knowledge Mapping and Institutional Prospects on Circular Carbon Economy Based on Scientometric Analysis.

The circular carbon economy is receiving increasing research attention as an essential tool for reducing carbon emissions and mitigating climate change. However, there is no research on the literature distribution and the current situation of the circular carbon economy studies. This paper presents a scientometric analysis of 1452 academic papers on the circular carbon economy and their references from 2010-2021 using the Citespace visualization network. The results show that research on the circular carbon economy has experienced a relatively gradual growth from 2010 to 2016, followed by an explosive growth from 2016 to 2021. Research cooperation among countries is close, forming a relatively concentrated cooperation network, while the core author group has not yet formed. Furthermore, the research on circular carbon economy strongly correlates with relevant international hotspots and national policy changes, reflecting the instrumental characteristics of circular carbon economy research. We summarized three main research topics through keywords clustering. In addition, we point out the future research directions from technical progress considering industry differences and cooperation, multiple environmental policies and legal system construction, interregional and international cooperation, etc., from an institutional research perspective. This article provides an essential and valuable reference for related research.

Assessing the Relationship among Land Transfer, Fertilizer Usage, and PM2.5 Pollution: Evidence from Rural China.

Concern for environmental issues is a crucial component in achieving the goal of sustainable development of humankind. Different countries face various challenges and difficulties in this process, which require unique solutions. This study investigated the relationship between land transfer, fertilizer usage, and PM2.5 pollution in rural China from 2000 to 2019, considering their essential roles in agricultural development and overall national welfare. A cross section dependence test, unit root test, and cointegration test, among other methods, were used to test the panel data. A Granger causality test was used to determine the causal relationship between variables, and an empirical analysis of the impulse response and variance decomposition was carried out. The results show that the use of chemical fertilizers had a significant positive impact on PM2.5 pollution, but the impact of land transfer on PM2.5 pollution was negative. In addition, land transfer can reduce the use of chemical fertilizers through economies of scale, thus reducing air pollution. More specifically, for every 1% increase in fertilizer usage, PM2.5 increased by 0.17%, and for every 1% increase in land transfer rate, PM2.5 decreased by about 0.07%. The study on the causal relationship between land transfer, fertilizer usage, and PM2.5 pollution in this paper is helpful for exploring environmental change-they are supplements and innovations which are based on previous studies and provide policy-makers with a basis and inspiration for decision-making.

Effects of Risk Perception of Pests and Diseases on Tea Famers' Green Control Techniques Adoption.

Green control techniques support the concept of green plant protection, advocate for the safe and reasonable use of pesticides, and finally achieve the goal of controlling pests and diseases and protecting the environment. The purpose of this study is to explore the effect of risk perception of pests and diseases on farmers' usage intention of green control techniques. Based on 747 samples of tea farmers in Sichuan province, China, introducing the Unified Theory of Acceptance and Use of Technology (UTAUT) framework and using the Partial Least Square-Structural Equation Modeling (PLS-SEM) approach, this paper found that risk perception has a negative impact on behavioral intention. Performance expectancy, effort expectancy, and social influence can positively affect behavioral intention, and facilitating conditions can also positively influence usage behavior. Moreover, the mediating analysis indicated that the higher the risk perception is, the less performance expectancy of green control techniques and the weaker the behavioral intention. Meanwhile, risk perception also plays a mediating effect on the relationship between effort expectancy and behavioral intention. This study could help to provide references for policymaking to improve the adoption of green control techniques.

The Impacts of COVID-19 on Distance Education with the Application of Traditional and Digital Appliances: Evidence from 60 Developing Countries.

Educational disruptions from the COVID-19 pandemic during school closures have become a remarkable social issue, particularly among the developing countries. Ample literature has verified the adverse effects of the long-lasing epidemic on school education. However, rare studies seek to understand the association between the severity of COVID-19 and distance learning, an alternative education pattern, and foster policy designs to promote educational transition, particularly targeting the post-crisis phase of the COVID-19. By combining four data surveys, this article empirically examines the impacts of COVID-19 on children's distance education with the application of various appliances across 60 developing countries. The results suggest that, after controlling socio-economic, geographic, and demographic variables, a higher level of mortality rate of COVID-19 contributes to more households participating in distance education. In particular, this positive term is larger for distance education by using TVs and radios compared with the usage of digital appliances. To explore the potential channel of the above linkage, this article argues that the positive association between mortality rate and the use of traditional appliances is weakened through higher levels of stringency in lockdown measures. Timely policies are, therefore, recommended to guide towards distance learning with economic and technological supports to guarantee a wave of inclusive educational recovery in the ongoing post-COVID-19 era.

Assessing the relationship between air pollution, agricultural insurance, and agricultural green total factor productivity: evidence from China.

As a favorite means to promote the development of green agriculture, agricultural insurance can not only encourage farmers to adopt green production technology and improve production efficiency, but also achieve the purpose of reducing the input of chemicals to protect the environment. This article aims to study the dynamic relationship between agricultural insurance, air pollution, and agricultural green total factor productivity using the panel vector auto-regressive method (PVAR) and panel data of 30 provinces in China from 2005 to 2018. The empirical results show that there is a significant cross-sectional dependence and the co-integration relationship between agricultural insurance, air pollution, and agricultural green total factor productivity. The increase in agricultural insurance can improve agricultural green total factor productivity and aggravate air pollution to a certain extent. However, serious air pollution does not improve agricultural green total factor productivity. Panel Granger causality test results show that agricultural insurance has a one-way causal relationship with green total factor productivity and air pollution, and so does air pollution with agricultural green total factor productivity. In addition, impulse response results show that increasing agricultural insurance or reducing air pollution can improve agricultural green total factor productivity. These conclusions have long-term practical implications for both agricultural policymakers and environmental managers.

Financial Support for Agriculture, Chemical Fertilizer Use, and Carbon Emissions from Agricultural Production in China.

In the past 15 years, China has emitted the most carbon dioxide globally. The overuse of chemical fertilizer is an essential reason for agricultural carbon emissions. In recent years, China has paid more and more attention to financial support for agriculture. Therefore, understanding the relationship between chemical fertilizer use, financial support for agriculture, and agricultural carbon emissions will benefit sustainable agricultural production. To achieve the goal of our research, we selected the panel data of 30 provinces (cities) in China from 2000 to 2019 and employed a series of methods in this research. The results demonstrate that: the effect of chemical fertilizer consumption on agricultural carbon emissions is positive. Moreover, financial support for agriculture has a significantly positive impact on reducing carbon emissions from agricultural production. In addition, the results of causality tests testify to one-way causality from financial support for agriculture to carbon emissions from agricultural production, the bidirectional causal relationship between chemical fertilizer use and financial support for agriculture, and two-way causality between chemical fertilizer use and agricultural carbon emissions. Furthermore, the results of variance decomposition analysis represent that financial support for agriculture will significantly affect chemical fertilizer use and carbon emissions in the agricultural sector over the next decade. Finally, we provide several policy suggestions to promote low-carbon agricultural production based on the results of this study. The government should uphold the concept of sustainable agriculture, increase financial support for environmental-friendly agriculture, and encourage the research and use of cleaner agricultural production technologies and chemical fertilizer substitutes.

Dynamic Linkage between Aging, Mechanizations and Carbon Emissions from Agricultural Production.

The trend of aging is intensifying and has become a prominent population phenomenon worldwide. The aging population has an important impact on carbon emissions, but at present, there is little research on its ecological consequences, especially the relationship with agricultural carbon emissions. For a long time, China has been dominated by a scattered small-scale peasant economy. Currently, the aging population also means that the agricultural labor force will gradually become scarce, and the agricultural production will face reform. This article is intended to find the long-term impact of aging and mechanization on agricultural carbon emissions and construct a more comprehensive policy framework for sustainable development, hoping to contribute to environmental and ecological protection. The research sample in this article is from 2000 to 2019, covering 30 provinces (cities, autonomous regions) in China. We adopted methods and models including Fully Modified General Least Squares (FMOLS), Dynamic General Least Squares (DOLS), Panel Vector Autoregression (PVAR) model, etc., and used the Granger causality test to determine the causal relationship between variables. Results show that aging is the Granger cause of agricultural carbon emissions and agricultural mechanization. Agricultural carbon emissions and agricultural mechanization have a bidirectional causal relationship. In the short term, agricultural mechanization and aging both have made a great contribution to carbon dioxide emissions from agricultural production. However, in the long term, the impact of aging on agricultural mechanization is significantly negative. Therefore, it is generally beneficial to improve the environmental problems of agricultural production. Our research focuses on the latest background of population trends and global climate issues and finally provides suggestions and a theoretical basis for the formulation of government agricultural policies according to the research conclusions.

Forecasting Carbon Price in China: A Multimodel Comparison.

With the global concern for carbon dioxide, the carbon emission trading market is becoming more and more important. An accurate forecast of carbon price plays a significant role in understanding the dynamics of the carbon trading market and achieving national emission reduction targets. Carbon prices are influenced by many factors, which makes carbon price forecasting a complicated problem. In recent years, deep learning models are widely used in price forecasting, because they have high forecasting accuracy when dealing with nonlinear time series data. In this paper, Multivariate Long Short-Term Memory (LSTM) in deep learning is used to forecast carbon prices in China, which takes into account the factors affecting the carbon price. The historical time series data of carbon prices in Hubei (HBEA) and Guangdong (GDEA) and three traditional energy prices affecting carbon prices from 5 May 2014 to 22 July 2021 are collected to form two data sets. To prove the forecast effect of our model, this paper not only uses Multivariate LSTM, Multilayer Perceptron (MLP), Support Vector Regression (SVR), and Recurrent Neural Network (RNN) to forecast the same data, but also compares the forecast results of Multivariate LSTM with the existing research on HBEA and GDEA forecast based on deep learning recently. The results show that the MAE, MSE, and RMSE obtained by the Multivariate LSTM are all smaller than other prediction models, which proves that the model is more suitable for carbon price forecast and offers a new approach to carbon prices forecast. This research conclusion also provides some policy implications.

The role of crop insurance in reducing pesticide use: Evidence from rice farmers in China.

Pesticides play a significant role in increasing agricultural yields. However, the overuse of chemical pesticides on crops is a major challenge faced by China, which damages human health, threatens food security, and increases production costs. This paper provides empirical evidence on the relationship between crop insurance and pesticide use. Based on micro-survey data collected from 3410 households, we estimate a control function (CF) approach and find that farmers who purchase crop insurance use 33.30% lower pesticides than those who do not. A series of robustness tests confirm these findings. The results of the moderating effect analysis suggest that rice cultivation training, experience, schooling years, and agricultural laborers can negatively moderate the effect of crop insurance on pesticide use. Furthermore, we also find that the treatment effect of crop insurance is stronger for farmers who are most inclined to purchase crop insurance.

Study on the impact of environmental pollution on farmland abandonment.

Farmland abandonment, as a manifestation of the low efficiency of the rural economy, has a profound impact on the process of agricultural and rural modernization. This study uses the 2016 China Labor Force Dynamic Survey data based on 8116 samples from 104 cities, constructs the Tobit model and IV Tobit model to analyze the land abandonment quantitatively from the perspective of environmental pollution. The results show that (1) environmental pollution can significantly increase the probability and area of land abandonment, (2) there is significant regional heterogeneity in the impact of environmental pollution on land abandonment, (3) the impact of environmental pollution on land abandonment varies significantly with different family sizes and land management scales, but the land management scale is relatively more sensitive. This study provides a deeper understanding of the relationship between environmental pollution and land abandonment in China and provides a basis for formulating relevant policies to strengthen the treatment of environmental pollution to solve the dilemma of land abandonment, which is of great practical significance to sustainable development of rural economy and the guarantee of food security in China.

Heterogeneous Driving Factors of Carbon Emissions Embedded in China's Export: An Application of the LASSO Model.

With the steady growth of CO2 emissions embedded in trade, the driving forces of emissions have attracted extensive attention. Most of the literature has verified a bundle of the influential factors; however, further analyses are necessary to understand the predominant and heterogeneous driving factors in different economies and/or industries. Accordingly, by applying the multiregional input-output (MRIO) model, this article firstly evaluates the embodied carbon emissions of China's export from 1992 to 2020 in total volumes and by 14 industries. Then, the Least Absolute Shrinkage and Selection Operator (LASSO) estimations allow us to discover that urbanization, technology update and gross domestic product (GDP) are the leading three prioritizing factors in generating China's export emissions. Interestingly, this paper discovers that raising the proportion of female parliamentarians contributes to an abatement of emissions. Furthermore, the empirical results suggest that the heterogeneities of those factors do exist among industries. For example, the percentage of females in parliaments turns out to have a larger effect among labor-intensive industries only. In facing with rapid globalization and economic development of China, this paper provides important policy implications towards specific industries in terms of mitigating trade emissions. It guides policy-makers to achieve "carbon neutrality" by avoiding carbon leakage in net-export countries such as China.

Effect of agricultural subsidies on the use of chemical fertilizer.

Agricultural subsidies lead to changes in the use of chemical fertilizer by farmers. Using data from a household survey conducted annually by the Rural Economy Research Center of the Ministry of Agriculture of China from 2014 to 2018, Control Function (CF) approach and Heteroskedasticity-based identification strategy were employed to analyze the impact of agricultural subsidies on chemical fertilizer use by rice farmers. After addressing the problem of endogeneity, we found that agricultural subsidies have a significantly negative impact on the use of chemical fertilizer. Precisely, every 100% increase in agricultural subsidies would result in an average decrease of 3.4% in chemical fertilizer use. In addition, results of heterogeneity analysis showed that agricultural subsidies had a stronger negative impact on fertilizer use as rice-planting experience increases. But the ability of rice-planting management and off-farm labor within household could reduce this negative impact. We also found that the effect of arable land productivity conservation subsidies policy was short-lived. Furthermore, based on the frame of structural equation model (SEM), the results of mediation analysis showed that agricultural machine and rice-planting area had partial mediation of 5.3% and 41%, respectively. It implied that agricultural subsidies reduced fertilizer use by promoting the adoption of agricultural techniques and expanding the planting area. In brief, agricultural subsidies had both technical effect and scale effect. But the mediating effect of household income was not significant. This study is intended to assist the concerned authority and agriculture sector to understand the positive role of agricultural subsidies in sustainable production, and provides some feasible policy proposals.

Effects of haze pollution on pesticide use by rice farmers: fresh evidence from rural areas of China.

Recently, severe haze pollution has not only threatened human health and food security, but also seems to have aggravated the unscientific use of pesticides by rice farmers in rural areas of China. Using original data on haze pollution across China, combined with rural household survey data collected from 2014 to 2018, we conducted a detailed empirical study on the effects of haze pollution on pesticide use by rice farmers based on the theory of risk aversion. The empirical results revealed that haze pollution with higher levels of PM2.5 positively impacted the use of chemical pesticides in rice cultivation. More precisely, with each 100% increase in PM2.5 concentrations, the use of pesticide per mu increased by 7.9%, and the average pesticide cost per mu increased by 2.3%. The results were robust to a series of tests that addressed potential endogeneity concerns, including omitted variable bias, measurement error, and reverse causality. We then examined the heterogeneous effects of haze pollution increases on the use of chemical pesticides and found that for rice farmers without rice insurance, haze pollution has a stronger effect on pesticide use and a weaker effect on pesticide cost. However, for rice farmers with more experience in rice cultivation and small-scale rice planting, the effect of haze pollution on pesticide use and cost is relatively small. Our findings provide important policy implications for pesticide risk management in rural areas of developing countries.

The impact of the COVID-19 outbreak on the air quality in China: Evidence from a quasi-natural experiment.

The outbreak of coronavirus (COVID-19) in early 2020 posed a significant threat to people's health and economic sustainability in China and worldwide. This study investigated whether the lockdown measures precipitated by the COVID-19 pandemic affected air pollutants in the short term. Moreover, we investigated the impact of the heterogeneity of cities and regions. Using city-level daily panel data for the 2018-2020 lunar calendar, we employed a two-way fixed effects model and interrupted time-series analysis to inspect the effects of the lockdown measures. Interesting empirical findings emerged from our analysis. First, compared with the base period from 2018 to 2019, the COVID-19 lockdown measures significantly reduced air pollutants. In 2020, compared to 2018, PM10 and SO2 dropped by 15.28 µg/m3 and 6.55 µg/m3, and compared to 2019, PM2.5, PM10, and SO2 declined by 7.4 µg/m3, 19.34 µg/m3, and 1.41 µg/m3, respectively. Second, our dynamic analysis showed that as more time elapsed since the start of the lockdown, the associated reduction in air pollution became more significant. Third, the proportion of secondary industries and the cumulative number of confirmed cases had a considerable heterogeneity impact on lockdown measures. Policymakers should encourage investment in new infrastructure and initiatives to boost efficiency and enhance environmental outcomes.

Estimating effects of cooperative membership on farmers' safe production behaviors: evidence from the rice sector in China.

The current agricultural system in China highly depends on chemical fertilizers and pesticides. Consequently, agricultural production activities cause various environmental issues. Carrying out safe production provides vital support for sustainable development of agriculture, which may improve this situation. The past decades have witnessed the fast development of rural cooperatives organization in China. Given the fact that rural cooperative organization plays a crucial role in agricultural production, however, there is little empirical evidence on the relationship between cooperative membership and safe production of smallholders in China. This study aims to investigate whether the participation in farmer cooperatives contributes to safe production in agriculture in China. Using survey data covering 623 rice-producing farm households in Sichuan province in China, this study employs the endogenous switching regression model to examine the effects of the participation in farmer cooperatives on safe production in rice agriculture. The results show that cooperative membership has significantly positive effects on safe production in rice agriculture. In particular, the average treatment effects demonstrate that without the participation in cooperatives, the members' adoption of the green control techniques would reduce by 74.491%, the application of artificial weeding would reduce by 38.768%, and organic fertilizer input would reduce by 23.448%. Furthermore, the marginal treatment effect is employed to evaluate the heterogeneous effects of the participation in farmer cooperatives on safe production in rice agriculture. Heterogeneous effect analyses suggest that farmers who are more likely to participate in farmer cooperatives are easier to adopt green control technology, while farmers who are less likely to participate in farmer cooperatives are easier to adopt artificial weeding and increase organic fertilizer input. To improve safe production in rice agriculture, the Chinese government is expected to encourage rice farmers to participate in rural cooperative organizations, and to stimulate rice farmers to take collective action to address environment issues arising from agricultural production.

Triple-hurdle model analysis of the factors influencing biogas digester building, use and processing by Chinese pig farmers.

Because of the pollution associated with pig manure, pig farmers are being encouraged to adopt environmentally friendly manure management solutions such as biogas digesters. However, as the correlations and influencing factors associated with the different manure disposal stages remain unclear, these solutions have failed to positively change farmer disposal behaviors. Therefore, this paper constructed a triple-hurdle model to empirically analyze the pig farmer manure disposal behaviors and the associated relationships under the belief that the three stage biogas digester decisions were driven by structurally different processes. This paper adds to the literature in three ways: (1) it provides a dynamic framework that identifies pig farmer manure disposal behaviors; (2) it applies a recently developed econometric method that corrects for conditional correlations between error terms; and (3) proves that certain factors might have opposite impacts in different behavior stages. It was found that cultivated land area and farm income ratio had statistically significant positive impacts on biogas digesters construction behavior but a negative influence on the farmers' use of the biogas digesters. Farmers who joined a cooperative were found to be statistically more likely to be biogas digester users, and the unconditional expected share of the actual treated manure was significantly higher. This study can assist policymakers in formulating and implementing strategies to encourage greater biogas digestor use by pig farmers.