Do corporate social responsibility practices contribute to green innovation? The mediating role of green dynamic capability

Green finance and environmental regulation can reduce CO2 emissions and promote the sustainability of economic development. Based on panel data of 126 resource-based prefecture-level cities in China from 2005 to 2017, the current study used a dynamic panel data model to empirically determine the CO2 emission reduction effects of different green finance instruments under different environmental regulatory intensities. The results showed that green finance tools had significant negative effects on the intensity of CO2 emissions, and green finance can adapt to environmental regulations of different intensities, which cooperated to promote carbon emission reduction. Moreover, in comparison, the debt-based green finance instrument had a stronger effect than the equity-based green finance instrument, and they did not show a coupling relationship. An administrative adjustment in green finance and environmental regulation is required to reduce environmental emissions and to improve sustainable development.

Do Green Finance and Environmental Regulation Play a Crucial Role in the Reduction of CO2 Emissions? An Empirical Analysis of 126 Chinese Cities

The concept of agricultural and environmental sustainability refers to minimizing the degradation of natural resources while increasing crop productions; assessment of inflow and outflow energy resources is helpful in highlighting the resilience of the system and maintaining its productivity. In this regard, the current study evaluated the amount of energy input–output of cotton productions and their environmental interventions. Data are randomly collected from 400 cotton farmers through face-to-face interview. Results suggested that the major energy is consumed by three culprits, i.e., chemical fertilizer, diesel fuel, and irrigation water (11,532.60, 11,121.54, and 4,531.97 MJ ha −1 , respectively). Total greenhouse gas (GHG) emission is 1,106.12 kg CO 2eq ha −1 with the main share coming from diesel fuel, machinery, and irrigation water. Stimulating data of energies, e.g., energy use efficiency (1.53), specific energy (7.69 MJ kg −1 ), energy productivity (0.13 kg MJ −1 ), and net energy gained (16,409.77 MJ ha −1 ). Further analysis using data envelopment analysis (DEA) showed that low technical efficiency, i.e., 69.02%, is the most probable cause of poor energy use efficiency. The impermanent trend in growth of energy efficiency has been witnessed with plausible potential of energy savings from 4,048.012 to 16,194.77 MJ ha −1 and a reduction of 148.96–595.96 kg CO 2eq ha −1 in GHG emission. Cobb–Douglas production function is further applied to discover the associations of energy input to output, which inferred that chemical fertilizer, diesel fuel, machinery, and biocides have significant effect on cotton yield. The marginal physical productivity (MPP) values obliged that the additional use in energy (1 MJ) from fuel (diesel), biocides, and machinery can enhance cotton yield at the rate of 0.35, 1.52, and 0.45 kg ha −1 , respectively. Energy saving best links with energy sharing data, i.e., 55.66% (direct), 44.34% (indirect), 21.05% (renewable), and 78.95% (nonrenewable), further unveiled the high usage of nonrenewable energy resources (fossil fuels) that ultimately contributes to high emissions of GHGs. We hope that these findings could help in the management of energy budget that we believe will reduce the high emissions of GHGs. 

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Analysis of Energy Input–Output of Farms and Assessment of Greenhouse Gas Emissions: A Case Study of Cotton Growers

Green finance is an essential way to cope with environmental pollution, promote the transformation of industrial structure and upgrade, and finally construct a resource-conserving and environment-friendly society and achieve the goal of sustainable development. This study explores the influence of green finance on industrial reasonability and is based on sample data of 30 provinces in China from 2009 to 2019. Through the application of the spatial panel Durbin model with the weight matrix based on the geographical distance, the influence of green finance on the industrial structure as well as its spatial spillover effects are analyzed. The degree of industrial reasonability and the index of green finance development are also examined by applying the Theil index and the entropy method. The empirical results demonstrate two things. First, there is a strong aggregation of the spatial distribution of industrial reasonability, and the spatial pattern remains relatively constant over the 11 years. The main aggregated types are the H-H and L-L between the regions. Second, green finance can promote the industrial reasonability of this region, while it has a significant negative spatial spillover effect on the process of industrial reasonability in adjacent regions. 

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The impact of green finance on industrial reasonability in China: empirical research based on the spatial panel Durbin model

Does fiscal expenditure promote green technological innovation in China? Evidence from Chinese cities

Does the extended producer responsibility system promote the green technological innovation of enterprises? An empirical study based on the difference-in-differences model

The study estimates the impact of disaster shocks and risk perception on farmers’ willingness for insurance. Based on data of 328 farmers from the Shandong province of East China, the study uses cluster analysis, analysis of variance, hierarchical linear model and structural equation model to determine the impact of disaster shocks and risk perception on farmers’ willingness for insurance. A bootstrap method of bias correction was used to test the mediating effect of risk perception between disaster shocks and insurance willingness. Results revealed that the overall willingness of farmers for crop insurance was low. However, the farmers’ willingness for crop insurance increased with an increase in disaster shocks and risk perception. The parametric analysis also confirmed that disaster shocks and risk perceptions have a significant and positive impact on the farmers’ willingness for crop insurance. Risk perception has a partial mediating effect between disaster shock and farmers’ willingness for crop insurance. It indicates that disaster shock not only impacts on farmers’ willingness for crop insurance directly but also has an indirect impact on farmers’ willingness for crop insurance through risk perception. Farmers are encouraged to participate in the early warning disaster programs to increase awareness of climate change and resilience against weather aberrations.

Does disaster shocks affect farmers’ willingness for insurance? Mediating effect of risk perception and survey data from risk-prone areas in East China

Yinyin Zhao

Papers

Does the extended producer responsibility system promote the green technological innovation of enterprises? An empirical study based on the difference-in-differences model

Does disaster shocks affect farmers’ willingness for insurance? Mediating effect of risk perception and survey data from risk-prone areas in East China