Uncovering the asymmetric impacts of economic policy uncertainty on green financial markets in China.

Green finance is considered a novel tool of financing to promote the development of the green economy, which has huge investment attractiveness. Previous studies detected the impacts of economic policy uncertainty (EPU) on the green financial markets are mixed. To this end, this study deeply investigates the asymmetric and heterogeneous impacts of EPU on the green bond and green stock markets based on the quantile-on-quantile (QQ) method. Using the data of China Economic Policy Uncertainty Index (CNEPU) and green financial indices, we get some interesting results. (1) EPU has an overall negative effect on the green financial markets, and the green stock market reacts more strongly than the green bond market. (2) For green bond market, the higher quantiles of EPU on a bear market have more significant effect than that on a bull market. (3) For green stock market, a negative effect of EPU on green stock market is observed for the lower quantiles of EPU, while a positive effect is noted at the highest quantiles of EPU. This paper could provide a reference for investors making green investment strategies and for policymakers making policies to promote green development.

Evaluating the Heterogeneity Effect of Fertilizer Use Intensity on Agricultural Eco-Efficiency in China: Evidence from a Panel Quantile Regression Model.

Chemical fertilizer is one of the most important input factors in agricultural production, but the excessive use of fertilizer inevitably leads to the loss of agricultural eco-efficiency (AEE). Therefore, it is necessary to explore the impact of fertilizer use intensity (FUI) on AEE. However, ordinary panel regression, based on the assumption of parameter homogeneity may yield biased estimation conclusions. In this regard, a panel quantile regression model (QRM) was constructed with the provincial panel data of China from 1978-2020 to test the difference and variation of this impact under heterogeneous conditions. The model was then combined with the spatial econometric model to explore the effect of the spatial lag factor. The results are as follows: (1) The QSM has unveiled a great improvement space for AEE that remains low overall, despite displaying a rising trend; the highest AEE is in the eastern region. (2) The FUI has a significant negative effect on AEE with the rise in quantiles, this negative effect tended towards weakening overall, although it rebounded slightly; it was stronger in areas with low AEE. It is necessary to consider the heterogeneous conditions in comparison with the average treatment effect of ordinary panel econometric regressions. (3) The impact of FUI shows significant variability in different economic sub-divisions and different sub-periods. (4) After considering the spatial effect of fertilizer use, the negative influence on local AEE had a faster decay rate as the quantile rose, but could produce a positive spatial spillover effect on AEE in neighboring areas. Local governments should dynamically adjust and optimize their fertilizer reduction and efficiency improvement policies according to the level and development stage of their AEE to establish a complete regional linked agroecological cooperation mechanism.

Application of Delphi method in screening of indexes for measuring soil pollution value evaluation.

Soil pollution is one of the most important issues in environmental governance at present. Using scientific and reasonable methods to estimate the economic losses caused by soil pollution is the basis for maximizing the effectiveness of governance resources. This study combines the methods of mixed group discussion and literature analysis to establish preliminary soil pollution value loss measurement indicators. The Delphi method is used to modify, add, and delete indicators to obtain a set of feasible soil pollution value loss measurement indicator systems. It laid a method foundation for further quantifying the loss of soil pollution value and provided support to related government decisions such as land resource management and soil pollution control. The response coefficients of the two rounds of expert consultations were 81.2% and 77.8%; the degree of expert authority was 0.647 and 0.708; the coordination coefficients were 0.155 and 0.194; the final indicator system included three dimensions of economic, social, and environmental, a total of eight indicators. The experts in the soil pollution value loss measurement index system established in this study have unified final opinions and a good degree of coordination, which can be used to measure soil pollution value loss.

Social Stability Risk Assessment of Land Expropriation: Lessons from the Chinese Case.

Scholars have paid much attention to the problems existing in the land expropriation risk assessment system and the sound countermeasures from a qualitative perspective. Empirical research on land expropriation social stability risk assessment from the micro-level perspective is limited. This study analyzed the Chinese social stability risk assessment system of land expropriation though a case study of a land expropriation project in China. The current social stability risk assessment system of land expropriation, which includes the assessment purposes, principles, contents, methods, and results, was analyzed. We concluded with lessons and deficiencies from the current social stability risk assessment system. The research findings show that: (1) the current land expropriation risk assessment system mostly takes the land administration department as the main body of responsibility, identifies the risks by means of seminars, visits, letters, and visits, and takes the opinion of the masses or experts as the risk assessment result. (2) The current land expropriation risk assessment system should be standardized in terms of defining the risk assessment of land expropriation, improving the land expropriation risk assessment system and optimizing land expropriation assessment procedures. This paper provides a reference for the sustainable development of land use in rural and urban areas in China.

Characteristics, hazards, and control of illegal villa (houses): evidence from the Northern Piedmont of Qinling Mountains, Shaanxi Province, China.

Unapproved and illegal buildings have sprawled into the Northern Piedmont of the Qinling Mountains. The problem of illegal villas has aroused widespread public opinion and concern. The ecological environment of the Qinling Mountains has been seriously affected by the resurgence of illegal villas. This paper introduces the characteristics and distribution of illegal villas, analyzes the hazards caused by illegal villas, and describes control measures for illegal villas and land consolidation and ecological remediation in the Northern Piedmont of the Qinling Mountains. The results show that illegal planning and illegal development, as well as local governments' irregularities, including control, governance, punishment, demolition, and compensation for illegal buildings in the expropriation of premises, have caused the problem of illegal construction of villas in the Northern Piedmont of the Qinling Mountains. Control measures for illegal villas are demolition, land consolidation, and ecological remediation. Policy implications for protection of Qinling Mountains are provided.