Corruption and anti-corruption efforts are intertwined with political and economic concerns. From an economic and political perspective, as the government strives to enhance its governance capabilities, it becomes crucial to consider the costs of anti-corruption supervision and the losses incurred from corruption. This evaluation is essential for formulating a scientifically sound anti-corruption strategy that maximizes government benefits. To address this issue, the paper presents a model that incorporates levels of supervision and associated costs. The findings reveal that in the case of homogeneous officials, the optimal level of supervisory input, which maximizes government benefit, is nearly zero when per capita income is low due to budgetary constraints on anti-corruption control. However, as per capita income reaches a certain threshold, the optimal level of supervisory input suddenly rises to its maximum and decreases as per capita income increases. Alternatively, if the government adopts a zero-tolerance approach towards corruption and provides adequate remuneration to its employees, ensuring that all competent authorities can resist corruption, then corruption can be eliminated. Moreover, when officials exhibit heterogeneity in terms of their honesty levels, certain conditions give rise to a middle per capita income range, resulting in an optimal level of supervisory input that leads to a phenomenon known as “partial corruption.” During this phase, the wages paid by the government to its employees promote honesty, preventing them from engaging in corruption. However, they are unable to curb the corrupt activities of more dishonest officials. To some extent, this model also explains the challenges associated with eradicating corruption in several middle-income countries.

Based on Beijing’s Air Quality Index (AQI) and concentration changes of the six major pollutants from 2019 to 2021, the results are visualized through descriptive statistics, and the air pollution status and influencing factors of Beijing’s AQI are analyzed using the ARIMA model and neural network. A forecast system is built and the fitting effects of the two models are compared. The results show that PM2.5, PM10, and O₃ of the six major pollutants have the greatest impact on AQI. Beijing’s air quality now shows a trend of improvement in recent years; however, there is obvious seasonal evidence that the summer pollution index has been high. Therefore, special attention should be paid to the treatment of ozone pollution in summer. Both models are useful for the forecast of AQI, but the forecast effect of the neural network model is better than that of the ARIMA model. Moreover, when using the additive seasonal model for the long-term forecast of monthly data, it is found that the Beijing AQI still shows seasonal cyclicality and has a slightly decreasing trend in the next two years. This research provides a basis for the forecast of air quality and policy enlightenment for environmental protection departments to deal with air pollution.

Collectivist culture serves as a significant cultural foundation in China. It could, to some extent, shape public attitudes toward the environment and thus influence the implementation of related policies. To examine this hypothesis, this study constructs the collectivist culture intensity index for 25 Chinese provinces spanning from 2010 to 2020. Through a fixed-effect model, we explore how the collectivist culture intensity affects pollution emissions in China. The empirical results indicate the significance of collectivism in enhancing emission reduction through environmental regulations. This conclusion remains robust even when excluding the impact of endogeneity concerns by adopting the instrumental variable approach. Heterogeneity analysis shows that collectivism is more effective in enhancing market-based environmental regulations rather than those driven by policies. Further mechanism analysis confirms that green innovation is a crucial pathway through which collectivism influences pollution emissions. These findings here will offer guidance to policymakers when formulating environmental policies for contexts with different regional cultures.

The severity of haze pollution has increased along with the growth of the economy and urbanization. Studying the relationship between urbanization and environmental pollution is extremely important from a practical standpoint in the context of encouraging new urbanization development in China. In this paper, we explore the impact mechanism of urbanization on air pollution, using a spatial Durbin model (SDM) build on panel data of 277 cities from 2010 to 2019. The findings demonstrate that urbanization significantly inhibits haze pollution across the country, with energy consumption structure and industrial structure upgrading acting as mediating factors. Moreover, economic growth, population aggregation, and openness to foreign investment aggravate pollution, whereas transportation facilities, urban vegetation areas, and wind speed reduce air pollution. Furthermore, foreign direct investment increases pollution nationwide while alleviating haze pollution in the eastern region. According to analysis of regional heterogeneity, there is a nonlinear relationship between urbanization and pollution in the central and western cities, while development and pollution in the eastern cities show a tendency to decouple. On this basis, this paper puts forward some policy recommendations to attenuate the vicious linkage between urbanization and pollution in order to promote high-quality urbanization development.

This study investigates the nexus between household head gender and poverty vulnerability in the context of China's eradication of absolute poverty. Using a sample of 5061 rural households from the 2018 CFPS database, poverty vulnerability is quantitatively measured through the VEP model and the 3FGLS method. Additionally, the Probit model is employed to elucidate the ties between household head gender and rural household poverty vulnerability. The study uncovers an absence of significant disparity in poverty vulnerability between female-headed and male-headed households overall. However, heterogeneity is observed within female-headed households: de jure female-headed households exhibit greater vulnerability, while De facto female-headed households display the opposite trend. Notably, health risks are accentuated as a decisive factor, with female-headed households, especially de jure ones, experiencing significantly higher health risks than their male-headed counterparts. Moreover, the education level, household income, and assets are positively correlated with reducing poverty vulnerability and facilitating households' escape from poverty. These findings provide important references for formulating poverty alleviation strategies and more effective mechanisms to prevent relapse, thereby alleviating vulnerability to relative poverty.