This paper evaluates whether social capital affects the ability of farm households to obtain formal and informal loans. We test for the impact of two measures of social capital. The first measure, kinship, captures the traditional aspects of bonding social capital in rural areas that might affect the probability of getting informal loans. As the economic reforms in China have changed the traditional rural way of life and weakened the role of kinship, more mobile farmers are likely to develop a different kind of social capital also based in the Chinese tradition but not focused exclusively on kin. This friendship social capital is hypothesized to affect farmers’ ability to get both formal and informal loans. We use the Chinese Household Finance Survey data from 2013 and estimate the probability of obtaining credit, while also accounting for the reverse causality. In addition, we use the Heckman selection model to establish how social capital affects not only the probability of getting loans but also the size of the loan. Empirical results suggest that social capital affects borrowing by farm households. In particular, the friendship social capital has a positive effect on farm household’s ability to get formal loans, and has a substitution effect on informal borrowing, while kinship has a positive effect on farm households’ ability to get informal loans. Friendship and kinship are positively associated with the amount of a farm household’s formal and informal loans, respectively.

Urban-industrial symbiosis (UIS) is an important system innovation via sectors integration, and has been widely recognized as a novel pathway for achieving regional eco-industrial development. Eco-efficiency, as a mature approach and indicator, offers an effective tool to uncover both the status and trends of such a transformation. However, most studies have focused on the whole industry or city as a whole, which has meant that a view from the sectoral level focusing on UIS was missing. To fill this research gap, this paper applied a modified eco-efficiency approach using integrating input–output analysis (IOA) and carbon footprint (CFP) to identify the eco-efficiency benefits of UIS from a sectoral level. Specifically, sector-level economic data (as economic outputs) and CFP (as environmental impacts) are used to calculate the sectoral eco-efficiency. IOA helps to offer sectoral economic data, and, with integrating process-based inventory analysis, to conduct a CFP calculation at the sectoral level. To test the feasibility of the developed approach, urban industrial symbiosis scenarios in one typical industrial city of China were analyzed. This city is held up as the national pilot of the circular economy, low-carbon city, and ecological civilization in China. Scenarios analysis on a business as usual (no UIS) and with UIS implementation in 2012 were undertaken and compared with the change of sectoral CFP and eco-efficiency. The results highlighted a moderate increase in eco-efficiency and trade-offs in certain sectors, indicating that UIS was moderately effective in increasing the urban resource efficiency from a sectoral level, but a refined design was required. Policy recommendations are made based on the analytical results, to inform decision makers and urban and industrial managers seeking to improve the implementation of UIS as a means of achieving greater urban sustainability.

This paper clarifies the relationship between the flow paths of the corresponding ecological flows because of the ecological impact for land consolidation, using external energy methods to measure the external input of the project area or the output of ecological products. The application for nonlinear estimation of partial differential equations to land consolidation, the project ecological flow and system efficiency were quantitatively calculated. It shows that the conflict between fairness and efficiency is caused under conditions and levels of value and ecological compensation mechanism is built as a criterion for this ecological economics. Based on the years of use of the land improvement project, the time evolution of regional net ecological value, natural resource dependence, renewable resource dependence, ecological output ratio, ecological carrying capacity and ecological sustainability after the implementation of the project was assessed.