This study examines the impact of participation in short supply chains (SSCs) on technical efficiency (TE) and technological change (TC) in cucumber production in China, using data for the period 2011-2016. The meta-frontier model and the two-stage residual inclusion approach are utilized to examine the association between SSC participation, comparable TE, and TC. Accounting for selection bias, we show that SSC participation significantly decreased the comparable TE of cucumber production but accelerated TC.The disaggregated analysis reveals that the comparable TE for SSC participants was generally smaller than that for nonparticipants. Furthermore, comparable TE for nonparticipants consistently increased year-over-year, whereas, for SSC participants, it increased during some years and decreased during others. Last but not least, TC for both SSC participants and nonparticipants increased over time.

A sustainable and pleasant environment is deemed to offer various positive externalities such as scenic, visual and behavioral archetypes and patterns exhibiting in various forms. Such a scenario can significantly relieve households from many psychological and personal complications such as depression. Depression has aroused great concerns in recent years due to its personal and social burdens and unforeseeable damage. Many studies have explored the effects of air pollution caused by traditional fuel consumption on depression. However, limited evidence is available on how household non-traditional fuel choices affect depression. Based on a nationally representative dataset collected from China Family Panel Studies (CFPS) in 2012, this paper employs an endogenous switching regression (ESR) model and an endogenous switching probit (ESP) model to address the endogenous issue and to estimate the treatment effects of non-traditional fuel choices on depression in rural China. The empirical results show that non-traditional fuel users have significantly lower Epidemiologic Studies Depression Scale (CES-D) scores, indicating non-traditional fuel users face a lower risk of depression. Compared to solid fuels, employing non-traditional fuels will lead to a 3.659 reduction in depression score or decrease the probability of depression by 8.2%. In addition, the results of the mechanism analysis show that household non-traditional fuel choices affect depression by reducing the probability of physical discomfort and chronic disease. This study provides new insight into understanding the impact of air pollution in the house on depression and how to avoid the risk of depression in rural China effectively.

Arable land abandonment has been occurring in China in recent years. Although an emerging number of studies have investigated the impacts of urbanization and labor migration on arable land abandonment, little is known about what roles agricultural outsourcing services play in reducing arable land abandonment. Based on the data from the China Labor-force Dynamics Survey (CLDS) in both 2014 and 2016, this study employs a two-stage least squares method to address the potential endogeneity issue and sheds some light on the impact of agricultural outsourcing services for controlling disease and pests in arable land abandonment in China. The empirical results show that disease and pest control outsourcing services (DPCOS) significantly decrease the size of household-level arable land abandonment by 6.59% on average. More specifically, DPCOS mainly reduce the arable land abandonment in regions with the labor shortages, while this does not lead to a significant decrease in arable land abandonment in regions characterized by poor soil quality and steep slopes. Therefore, we may conclude that DPCOS could contribute to the reuse of farmlands suitable for cultivation and the exit of farmlands unsuitable for cultivation.

Climate change is a huge challenge for agricultural production. Climate-adaptive technology is an effective measure for farmers to adapt to climate change and improve their ability to cope with natural disasters. The low adoption rate of climate-adaptive technology has become an important factor restricting the sustainable development of China’s agriculture. Extreme weather may affect farmers' decisions to adopt climate-adaptive technology. This paper uses the survey data of 622 apple growers in Shaanxi Province to study the impact of extreme weather on farmers’ climate-adaptive technology adoption behavior and its mechanism. The results show that extreme weather has a significant positive effect on farmers’ adoption of climate-adaptive technology. This result still holds after robustness checks such as changing the measurement methods of key variables. In terms of the mechanism, one is that extreme weather can improve farmers’ risk perception and promote their adoption of climate-adaptive technology; the other is that extreme weather can promote farmers’ participation in credit, which in turn promotes their adoption of climate-adaptive technology. Heterogeneity analysis shows that compared with areas without policy incentives, extreme weather has a greater effect on farmers’ climate-adaptive technology adoption behavior in areas with policy incentives. Overall, the results suggest that promoting farmers’ adoption of climate-adaptive technology and understanding how well farmers respond to climate shocks can inform policy design and help reduce risks to agricultural production from extreme weather.