The impact of economic policy uncertainty on corporate social responsibility: A new evidence from food industry in China

Oil price uncertainty, oil pricing reform, and corporate profitability: The case of China

This study investigates the impact of oil price uncertainty (OPU) on corporate profitability in China, the world's largest crude oil consumer. Most importantly, we examine how the Chinese government's oil price reform affects this relationship. Using the yearly data of Chinese-listed companies, we find that the uncertainty of oil prices negatively affects corporate profitability but positively impacts operating expenses from 2007 to 2020. This finding holds after robust tests, including alternative profitability metrics and endogeneity model. Most interestingly, implementing the 2013 market-oriented oil pricing reform amplifies the adverse impact of OPU on corporate profitability owing to increased operating costs in the post-2013 period. Moreover, the detrimental effect of uncertain oil prices on corporate profitability is less prominent for large-capitalized companies. This research adds to the body of knowledge on the factors affecting corporate profitability by highlighting the volatility effect of oil prices and government pricing mechanisms. The results offer grounds for legislators and corporate managers to consider how to control the uncertainty surrounding oil price matters to ensure stable corporate profitability.

An evolutionary game theory-based study examining the relationship between fiscal policy, stability of farmers' cooperatives, and environmentally friendly digital management

To increase the degree of implementation of the rural revitalization strategy, it is crucial to conduct a scientific investigation of the relationship between fiscal policy, fiscal decentralization, green digital management, and contract selection. This research develops an analytical framework for the application of fiscal policy and the choice of cooperative association contracts based on the contract theory. On the basis of a theoretical analysis of the external factors that influence the choice of residents' cooperative association contract and behavior, it goes on to investigate the interest game relationship and stability of three different cooperative associations (production type, service type, and industrial chain type). Additionally, it runs an empirical test using survey information from cooperative associations in China's Gansu Province. The findings indicate that the cooperative association is more likely to select the factor contract model depending on the strength of the fiscal policy support, the union's brand influence, and the regional market share change of the primary products. Evolutionary equilibrium is inhibited by the association's input costs, but a stable contract is created more favorably the more average the cost distribution is. The stability of the contract and its detrimental effects on pro-environmental behavior are worse the more damage other residents' breaches of the contract have caused. The research findings in this paper may serve as a basis for decision-making and a source of information for encouraging the high-quality growth of cooperative groups.

Fiscal policy, green finance, and low carbon transformation nexus: a novel study unleashing the synergistic effects of carbon reduction and pollution in China

Under the simultaneous demands of combating environmental pollution and decreased carbon emissions, it is critical to investigate the combined effect of agricultural contamination reduction and fiscal policy carbon reduction to support and promote green agriculture and low-carbon transformation. Based on provincial panel data of 2007 to 2020 in China, this paper employs the spatial Dubin model to empirically examine the pollution reduction and carbon reduction effects of fiscal policies supporting agriculture, as well as calculating the synergistic effect of pollution reduction and carbon reduction. Our study's findings reveal that non-point source agricultural pollution and agricultural carbon emissions have a tendency of growing and subsequently reducing, such as increasing from 2007 to 2015 and decreasing from 2016 to 2020. Second, results demonstrate that agricultural carbon emissions and agricultural pollution have a positive geographical dependency in each province, and fiscal policies supporting agriculture have high-high and low-low spatial clustering features. Furthermore, fiscal policies that promote agriculture can lower local agricultural carbon emissions and pollution while also having a considerable beneficial spillover impact on neighboring provinces. According to the study findings, the fiscal policy for supporting agriculture has a negative pollution reduction impact and a positive synergistic effect, resulting in a synergistic effect of agricultural pollution reduction and carbon reduction. The outcomes of this study can serve to promote carbon-reduction measures and provide recommendations for future policy development.

Can fiscal decentralization and farmers' use of internent be the route to the digitalization performance in China? A novel approach towards unlocking the role of online marketing behavior and performance of agricultural products

It is believed that the respondents' disadvantageous positions and the information asymmetry that exists between them are the bottlenecks that contribute to the stagnation of trades and the poor revenue that respondents receive from agro-products. Digitalization and fiscal decentralization both play an important part in helping to increase the information literacy of respondents who live in rural areas. The purpose of this study is to investigate the theoretical effects that the digital revolution has had on environmental behavior and performance, and it also analyzes the part that digitalization plays in the process of fiscal decentralization. This study investigates the impact that farmers' usage of the Internet has on their information literacy, online sales behavior, and online sales performance using research data collected from 1338 farmers in China primarily produce pears. Primary data was collected and utilized to develop a structural equation model, using the partial least squares (PLS) and bootstrapping methods; according to the findings, the use of the Internet by farmers has a significant positive effect on the improvement of their information literacy, and it will promote their online sales of pear through the improvement of their information literacy. The results show that the use of the Internet by farmers will improve the online sales performance of pear due to the improvement of farmers' information literacy.

A study evaluating the extrinsic and intrinsic determinants of farmers' adoption of climate change adaptation strategies: A novel approach for improving farmers' health

Small-scale farmers living in mountainous areas are particularly vulnerable to climate change. Although governments have implemented various support programs and policies to support a range of farmers to tackle climatic changes, there are still several difficulties in the implementation of these adaptation strategies. Using the survey data of 758 small-scale farmers this paper employs Multivariate Probit (MVP) and Poisson regression models to measure the effects of intrinsic and extrinsic factors affecting farmers adaptation decision in rural Vietnam. The results reveal that the extrinsic factors such as annual rainfall variations and farm size motivate farmers' adoption of their adaptations. The findings also reveal that the political connection has a significantly positive impact on the respondents' selection, while government interference such as extension training programs has a negative association with the farmers adaptation choice. Public extension programs should be simultaneously redesigned to support farmers in mitigating the impacts of climate change.

Spatial and temporal characteristics of rural livability and its influencing factors: implications for the development of rural revitalization strategy

Building livable rural regions is a key objective of China's rural revitalization, and fostering coordinated and sustainable regional development in China necessitates investigating the geographical and temporal distribution and influencing variables of livability in China's rural areas. This paper compares the concept and connotation of rural livability based on regional economic development theory and sustainable development theory, integrates China's rural revitalization strategy, proposes an index system for evaluating rural livability in China, and conducts an empirical analysis of livable rural areas. Firstly, the level of rural livability development is measured by the entropy method; secondly, the aggregation effect of provinces is demonstrated by using the Moran I index, and finally, the spatial Durbin model is used to explore the influencing factors of rural livability and its spatial spillover effects. Findings of our study reveal that the results of the entropy method indicate that the livability of rural China is in a growing development trend in all provinces, but the livability shows some regional disparities. The Moran index reveals that there are obvious spatial autocorrelations in the livability of Chinese rural areas, and the most typical features are the "high" and "low" clusters. The spatial Durbin model suggests that the influences on the development of rural livability are diverse. Besides, other variables such as environmental pollution and per capita housing area show a negative association with rural livability, and investment in fixed assets, cultural atmosphere and medical health show a positive relationship with rural livability. Based on the study findings, it is proposed that in the rural revitalization strategy process, the formulation of monitoring system should be strengthened and intensify the promotion of coordinated inter-regional development.

Unlocking the effects and optimization path of financial support for improvement in environmental quality and rural revitalization development: an empirical analysis based on provincial data of Shaanxi province

This study establishes an economic financial support model for the improvement of environmental quality through the development rural revitalization based on the extended Cobb-Douglas production function. Using statistical data from Shaanxi Province, China, from 2004 to 2019, a vector autoregressive (VAR) model is used to empirically analyze the development effect of financial support for rural revitalization and to give the focus points and optimization paths for financial support for environmental quality, rural revitalization and sustainable development. The research results show that financial support plays an active and long-term role in improving environmental quality and promoting rural revitalization and sustainable development. Specifically, the effect of financial instruments in supporting rural revitalization and sustainable development is continuous. In the insurance system, increasing the scale of agricultural insurance support and expanding the coverage of agricultural insurance are key to improving environmental quality and promoting rural revitalization and sustainable development. Therefore, financial policy makers should improve the targeting of financial instruments to provide the right guidance for improving the quality of rural environment and enhancing rural economy, so as to ultimately realize rural revitalization in China.

Assessing the impact of green tax reforms on corporate environmental performance and economic growth: do green reforms promote the environmental performance in heavily polluted enterprises?

Based on Porter's hypothesis and Pollution Shelter's hypothesis, this paper firstly constructs a mechanism of environmental protection tax law and corporate environmental performance. Secondly, it empirically examines the impact of green tax reform on corporate environmental performance and its internal mechanism through the difference in difference (DID) method. The study findings firstly reveal that environmental protection tax law significantly and progressively promotes the improvement of corporate environmental performance. Secondly, the heterogeneity analysis results show that the promotion effect of environmental protection tax law on corporate environmental performance is significant in enterprises with strong financial constraints and stronger internal transparency. The environmental performance improvement effect of the state-owned enterprises is stronger, which indicates that state-owned enterprises can set an example in the face of the formal implementation of the environmental protection tax law. In addition, the heterogeneity of corporate governance shows that the background of senior executives is an important factor affecting the effect of environmental performance improvement. Thirdly, the mechanism analysis indicates that the environmental protection tax law mainly promotes the improvement of enterprise environmental performance by strengthening the local government's enforcement rigidity, improving the local government's environmental concern, promoting enterprise green innovation, and resolving the collusion between government and enterprise. Further analysis shows that the environmental protection tax law based on the empirical results of this paper did not significantly trigger the phenomenon of cross-regional negative pollution transfer of enterprises. The findings of the study have important enlightenment on improving the green governance of enterprises and promoting the high-quality development of national economy.

Quantifying the effect of administrative approval reforms on SO2 emissions: a quasi-experiment in Chinese cities

The effects of the Administrative Examination and Approval System Reform on economic growth and entry of businesses have drawn much attention. However, few scholars pay attention to the impacts of this policy on SO₂ emissions. Keeping in view the existing research gap, a spatial difference-in-difference (SDID) model is employed to assess the effects of the Administrative Examination and Approval System Reform on SO₂ emissions in 297 Chinese cities during the period 1995-2020 from the perspective of spatial spillover effects. The results show that the establishment of Administrative Examination and Approval Center (AEAC) has significantly positive effects on the local SO₂ emissions. The significant indirect (spatial spillover) effects are confirmed. That is, the establishment of AEAC of a given city has a significant positive impact on the SO₂ emissions of neighboring cities. The findings are confirmed by several robustness tests. Our study findings have significant implications for the cross-border coordination of environmental policies that aim to improve the quality of the environment across borders.

Analyzing the status of multidimensional poverty of rural households by using sustainable livelihood framework: policy implications for economic growth

Poverty is a multifaceted and location-based issue that cannot be quantified using monetary metrics alone. This study aims to evaluate the multidimensional poverty status of poor households in Ha Giang province, Vietnam, by using the DFID (Department for International Development) sustainable livelihood framework, an integrating technique for spatial recognition of multidimensional poverty, was developed and deployed to conduct a county-level poverty assessment in rural Vietnam. The multidimensional poverty standard is considered a novel approach to assess poverty, identify causes of poverty, and encourage poor households to sustainably escape poverty. A household survey was conducted in three rural districts, namely Dong Van, Hoang Su Phi, and Bac Quang in Ha Giang province, Vietnam, during 2016 to 2021. The results of the study show that surveyed households are deficient in all five main sources of livelihood, in which the three most deficient capital sources are natural capital, social capital, and financial capital. The findings revealed that the majority of farming households were classified as multidimensionally poor. The multidimensionally poor regions were not only poorer in single-dimensional and aggregate ratings than the income-poor and recognized poor regions, but they also had several vulnerabilities and insecurity. The assessment of multidimensional poverty, by distinguishing the poor, marginalized, and dispossessed dimensions, should be extremely beneficial for each region to design and execute poverty reduction programs accordingly, and it would contribute to improving the persistence of alleviating poverty. The article also proposes a number of sustainable poverty reduction measures, in which the root is to improve the spirit of self-raising to escape poverty of households.

Spatial Effects of Digital Transformation, PM2.5 Exposure, Economic Growth and Technological Innovation Nexus: PM2.5 Concentrations in China during 2010-2020

Digital transformation can increase lending by commercial banks, which may have an impact on economic development and technological progress, thus affecting air pollution. However, a limited amount of literature has discussed the impact of the digital transformation of commercial banks (DTCB) on air pollution. Based on city-level data from 2010 to 2020, this study used a spatial Durbin model to explore the spatial effects of DTCB on air pollution. This study shows that DTCB significantly increases air pollution in local and surrounding cities. Heterogeneity analysis shows that DTCB increases local and surrounding city air pollution in non-innovative cities and cities with low digital economy development. However, in innovative cities and cities with high digital economy development, DTCB reduces PM2.5 emissions in local and surrounding cities. Mechanism analysis shows that DTCB has no significant impact on technological innovation, but significantly promotes economic development, thus increasing air pollution. From the perspective of DTCB, this paper deepens the research on digital finance and air pollution. Against the background of DTCB, the government should guide commercial banks to apply digital technology to increase lending for technology innovation and promote DTCB to achieve the dual goals of economic development and improvement in air quality.

A study assessing the impact of income relative deprivation and cooperative membership on rural residents' health: A pathway towards improving the health status of rural residents

Rural residents' health status is related to their happiness, socioeconomic status, personal development, and the ideals of living, but individual income relative deprivation has a negative impact on their health. Hence, this study aimed to examine that how to alleviate the negative impact of income relative deprivation on rural residents' health. Based on a literature review, it is the first study to propose that cooperative membership could help alleviate the adverse effects of income relative deprivation on rural residents' health. It survey data from 466 farm households in Shandong Province in China and employs an endogenous switching probit model to solve the endogenous problems. The results show that relative deprivation positively affects farmers' membership in a cooperative but negatively impacts their health. More importantly, the results indicate that membership in a cooperative improves farmers' health and alleviates the adverse effects of relative deprivation. These findings not only expand the empirical research on the positive impact of relative deprivation but also provide a new pathway towards improving the negative impact of income relative deprivation on rural residents' health. That is, the government should guide smallholder farmers to join professional cooperatives and encourage the development of 'multi-functional' cooperatives to play a greater role in improving rural residents' health.

Implementing a novel deep learning technique for rainfall forecasting via climatic variables: An approach via hierarchical clustering analysis

Variations in rainfall negatively affect crop productivity and impose severe climatic conditions in developing regions. Studies that focus on climatic variations such as variability in rainfall and temperature are vital, particularly in predominant rainfed areas. Forecasting rainfall is very essential in the agriculture sector due to the dependence of many people, while it is very complex to accurately predict rainfall due to its dynamic nature. This study aims to present a deep forecasting model based on optimized (Gated Recurrent Unit) GRU neural network to predict rainfall in Pakistan based on the 30 years of climate data from 1991 to 2020. The climatic variables were first extracted and then fine-tuned by eliminating outliers and extreme values from the data set for precise forecasting. Data normalization strategies were further utilized to adjust numeric values into a standard scale without distorting divergences or losing useful information. The proposed model achieved high prediction accuracy by maintaining minimal Normalized Mean Absolute Error (NMAE) and Normalized Root Mean Squared Error (NRMSE) compared to state-of-the-art rainfall forecasting models. Climatic variables used in the forecasting were evaluated in terms of correlation and regression analysis. The correlation results showed that temperature has a negative association and air quality variables have a positive association with rainfall in each quarter of the year. The second and third quarters of the year showed a high association with rainfall, whereas the air quality variables showed a lesser or no association with rainfall during the first and second quarters of the year. The results further showed a strong association of climatic variables with rainfall for all months of the year. The minimal loss achieved by the proposed model also demonstrated the feasibility of selected variables in precise forecasting of rainfall regardless of volatile climatic conditions.

Rural migration, governance, and public health nexus: Implications for economic development

With the deepening of rural aging and the increasing role of human capital in the non-agricultural employment labor market, this paper uses the data of China Health and Retirement Longitudinal Study (CHARLS), ordinary least squares (OLS) and instrumental variable method (IV) to try to examine the impact of rural migrant workers' education on their parents' health. Since a rural family may include more than one child, a sample of migrant workers with a high education level is used in the benchmark regression, and a sample of migrant workers with a low education level is used to test the robustness of the relationship. The results showed that the education of migrant workers had a significant positive impact on parents' health. The sample with the least education was used for the robustness, and the results did not change. The IV-probit method is used to address potential endogeneity, and the results remain stable. Heterogeneity analysis shows that there are significant differences in the impact of migrant workers' education on the health of parents from different groups. This positive effect has a greater impact on the health of parents who are older, less educated, and do not live with their children. Mediation analysis shows that children's economic ability, captured by income and work type, and their parents' health behavior, captured by sleep, alcohol consumption, and physical examinations, mediate this relationship. Thus, migrant workers' education affects their parents' health mainly through relaxing budget constraints and improving their parents' health production efficiency. In addition, this paper also found that education of migrant workers may significantly increase parental depression. Based on the above analysis, this paper argues that increasing investment in rural education is conducive to improving the health of migrant farmers' parents, thereby promoting the transfer of rural labor to non-agricultural industries and cities, curbing the rapid rise in labor costs, and promoting the healthy development of the economy.

Assessing the role of internet in reducing overuse of livestock antibiotics by utilizing combination of novel damage control and 2-SLS approaches: Risk, responsibility, and action

Reducing farmers' overuse of livestock antibiotics is very essential to ensure food, environment, and public health safety. Currently, the "internet + " has emerged as a new initiative to stimulate the development of rural industries by alleviating farmers' information constraints, lack of skills, and knowledge deficiencies. However, very few studies have focused on this issue, and studies specifically focused on the role of the Internet in reducing the overuse of livestock antibiotics are still very limited. To fill this existing research gap, this study aims to investigate the role of the Internet in reducing the overuse of livestock antibiotics using data of 426 farmers based in three provinces, including the Hebei, Henan, and Hubei provinces of China. To analyze the collected data, we first employ a damage control model to estimate the marginal productivity of farmer use of livestock antibiotics and then use a two-stage least squares (2SLS) approach to assess the role of the Internet in reducing antibiotic overuse. The findings of our study show that the marginal productivity of farmers' use of livestock antibiotics by farmers is 0.0079 (approaching 0), indicating that the overuse of antibiotics has become the realistic response of farmers. Our results further reveal that the Internet has a significant inhibitory effect on the overuse of livestock antibiotics by farmers. The Internet can reduce the use of antibiotics by 1.3147 yuan/head by improving your knowledge and skills about antibiotics. The further findings of our study reveal that the educational level and organizational participation of farmers are also important driving factors to reduce the overuse of livestock antibiotics. Furthermore, the findings of this study validate the role of gender, age, and educational level in the non-linear effect of the Internet on farmers' overuse of antibiotics. In conclusion, the findings of this study provide insight for policy makers in motivating farmers to reduce antibiotic overuse by strengthening rural internet infrastructure, implementing skill training, improving supervision, and establishing an incentive mechanism for the standard use of antibiotics.