In recent years, many areas of China have suffered from serious haze pollution, which greatly affects human health and daily life. It is of policy importance to understand the factors that influence the spatial concentration of PM_2.5. Based on data from 74 cities with PM_2.5 monitoring stations in 2013 and 2014, this study presents the overall haze situation in China and explores the determinants of PM_2.5 using a random-effects model, as well as a set of OLS regressions. The results indicate that PM_2.5 is significantly correlated with the industrial proportion, the number of motor vehicles, and household gas consumption, while public financial expenditure on energy saving and environmental protection does not show statistically significant effects. The analysis implies that China should adjust its economic structure and optimizes environmental governance to effectively respond to haze pollution.

Over the past decade, cities have emerged as leaders in sustainability and climate protection in the United States. ICLEI, a voluntary network of local governments, played an important role driving this trend. After years of steady growth, ICLEI became a target of political opposition and its membership dropped significantly from 2010 to 2012. This begs the question of whether cities’ termination of their ICLEI affiliation diminishes their implementation of sustainability actions. Two surveys administered in 2010 and 2014 provide data on cities’ implementation of an array of sustainability actions. Using a difference-in-differences (DiD) method, the impact of ICLEI termination on local governments’ administrative and policy commitments to sustainability is assessed. The results suggest that ending ICLEI membership does not significantly impact local sustainability actions, and also indicate that the durability of policy actions may be only loosely linked to the policies that justify them.

Data manipulation is considered one of the most pernicious forms of information distortion that challenges the effectiveness of the principals in monitoring agents. This study investigates factors influencing the behaviors of data manipulation from the perspective of patronage networks. Patronage networks feature a reciprocal exchange between patrons who control appealing resources and clients who ask for protection and benefits from the patrons. We hypothesize that in a three-tier principal–supervisor–agent model, agents favored in the patronage network would receive tacit permission and protection from the supervisor, and hence be encouraged to falsify performance data and game the principal. The empirical results, using panel regression models based on officially reported and satellite-observed environmental emissions data in China, suggest that cities with leaders favored in the patronage network present a stronger tendency for data manipulation. This study has theoretical implications for understanding the impact of informal institutions on performance management.