Abstract:Research on the land use efficiency of rural living spaces is at the core of conflicts about current rural land use and ecological environment construction in China. It can be effectively dealt with through the rational and healthy use of rural land, by promoting sustainable development and urban and rural coordination. Building on the foundation of ecosystem metabolism and sustainable development theories, this paper utilizes the Data Envelopment Analysis (DEA) Malmquist productivity index to divide the land use efficiency total factor productivity (LUTFP) into Malmquist-Luenberger technical change (MLTECH) and Malmquist-Luenberger efficiency change (MLEFFCH) from the perspective of scale change, and uses Kernel Function to measure and study the distribution characteristics of the dynamic evolution and land use efficiency (LUE) in different functional and productive areas and living space subsystem. The results show that, in the process of land use, desirable output growth in the Chongqing city rural living space is lower than the undesirable output reduction rate. Rural human settlement and construction management appears to damage the environment. The LUE in the obtained results showcases an obvious agglomeration effect in Chongqing. Also, there is a very significant "match-up" effect between the LUE and economic development level. In addition, the paper also finds that the technical change index and efficiency change index work together in rural living space LUTFP. The results presented in this paper can provide a basis for the optimization of regional development strategies and rural land utilization.

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The economic and social transition toward modernization is characterized by a massive outflow of rural labor, which raises problems such as rural job–housing separation and rural decline. Few studies have used rural labor employment microdata to quantitatively analyze the degree of separation between housing and jobs in different types of villages, especially in ecologically fragile mountainous and hilly regions. This article is based on a 2021 survey of 6181 rural households in 158 villages of Chongqing, a mountainous and hilly region of China, and divides villages into city edge, suburban, and outer suburban villages. In this study, the separation degree of housing–jobs (SDHJ) measurement model was created in order to explore the degree of separation between rural jobs and housing in terms of space–time dimension separation in these areas, and the different job–housing separation characteristics under different village types were distinguished. The results show the following. (1) The county’s rural SDHJ has a clear regional differentiation law, and the degrees of separation between housing and jobs in all counties are in the following order: main urban area < northeast of Chongqing < southeast of Chongqing. The degree of separation between housing and jobs presents a spatial pattern of “medium–low perimeter high, local prominence” according to both the degree of temporal separation and the degree of spatial separation. (2) The degrees of separation between housing and jobs in various village types are in the following order: urban fringe villages < suburban villages < outer suburban villages. The distance effect was verified. The SDHJ is typically low in urban fringe villages and moderate in suburban villages, with distinct geographical disparities in labor distribution. The SDHJ is typically higher in the outer suburban villages, where laborers choose long-term long-distance employment. (3) This study proposes some countermeasures that could reduce the SDHJ for different types of villages. The findings have important policy implications for China’s mountainous rural development and serve as a model for other developing countries.

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