Improving the efficiency of maize production is of great significance for global food security and the effective supply of agricultural products. Based on the survey data of 381 rural households, this study uses a stochastic frontier analysis to estimate the efficiency value and empirically analyze the factors affecting the technology efficiency of maize production in the Hengshui area of the North China Plain. First, higher costs were found to be related to extensive production methods of fertilization, pesticide application, and irrigation. Second, the results showed that there was an inverted U-shaped relationship between the irrigation cost and maize output. Specifically, when the irrigation cost was about 938 yuan/hectare, the maize output per unit area was optimal. Third, there was also an inverted U-shaped relationship between the fertilizer cost and maize output, and the loss of technical efficiency of maize output was minimal when the fertilizer cost is 2547 yuan/hectare. In addition, the findings of the inefficiency influencing factor model suggested that temperature and humidity were all positively associated with the non-efficiency of maize production. These findings can provide empirical support for improving the efficiency of maize production in North China or arid and semi-arid regions around the world.

Between 2003 and April 2016, 37 of 47 prefectures (i.e., sub-national local governmental units) introduced forest environmental taxes—local payment for environmental services (PES) schemes. These introductions are unique historical natural experiments, in which local governments made their own political decisions considering multiple factors. This study empirically evaluates models that explain normalized expenditures from forest environmental taxes as well as other PES schemes (subsidies for enhancing forests’ and mountain villages’ multifunction, and green donation) and traditional forestry budgets for Japan’s 47 prefectures based on the median voter model. Results demonstrate that the median voter model can particularly explain forest environmental taxes and forestry budgets. Specifically, the past incidence of droughts and landslides is positively correlated with the levels of forest environmental taxes. The higher the number of municipalities in a prefecture, the lower the amount of forest environmental tax spent on forests. Moreover, the number of forest volunteering groups, possibly an indicator of social capital in the forest sectors, had strong positive correlations with the levels of forest environmental taxes and forestry budgets. Other PES schemes and forestry budgets had unique patterns of correlations with the examined factors.

Although urban agriculture (UA) has been gaining greater attention as part of an effort toward sustainable urban development in China, empirical knowledge is limited. We conducted a discrete choice experiment with 756 residents of Shanghai. Overall, the results indicate that respondents supported UA as they tended to favor one of the UA scenarios presented. Residents prefer UA facilities that utilize environmentally friendly production, offer farming activities, and are equipped with dining facilities. Regularly scheduled educational activities hosted by UA facilities are preferred to those on an irregular basis. In terms of location, residents prefer UA facilities that are close by but do not necessarily want UA facilities to be right in front of them. There is a stronger preference for UA among highly educated populations, those with primary and secondary school students, and those with agricultural work experience. Additionally, various UA attributes affect residents' preferences; overall, there is a high degree of homogeneity in residents’ preferences for various UA attributes. The marginal willingness to pay value is slightly higher than expected among the estimation results. There are three reasons for this outcome: the characteristics of UA as a recreational facility in China, the relatively high price level in Shanghai, and the impact of the COVID-19 pandemic.

Green infrastructure (GI) provides considerable benefits, including stormwater runoff management, biodiversity conservation, and urban sustainability promotion, and thus has garnered widespread attention. However, the limited research on residents’ preferences for GI constrains further promotion in China. To address this issue, data were collected from 436 residents in Wuhan, China, through an online survey. This study employed a comprehensive analytical framework that integrates best–worst scaling (BWS) with the contingent valuation method (CVM) to assess the preferences of residents in Wuhan, China, for six types of GI and estimate their willingness to pay (WTP) for GI enhancements. The conditional model and mixed logit model results indicated that residents preferred GI facilities that offer direct benefits, such as street trees and permeable pavements, and showed a lower preference for structures less suited to a Chinese context, such as eco-roofs. Regarding heterogeneity, only permeable pavements showed significant variation in preferences. Furthermore, the average WTP for GI enhancement was 142.28 RMB/household/year. Factors including familiarity with GI, information sources, and air quality improvement perceptions positively influenced the WTP, while low income negatively impacted the WTP. These findings offer insights for urban planners to develop effective policies to enhance public support for GI and promote urban sustainability.