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Achieving the 2030 sustainable development goals is a major test facing many national and local governments at present. Countries around the world have achieved sustainable development goal 6 through legal norms and the preparation of environmental pollution control budget trial maps. Past studies rarely comprehensively analyzed industrial production and sustainable development stages simultaneously. Therefore, this research explores 31 administrative regions in China from 2013 to 2017 and uses the dynamic and network super efficiency model to evaluate the impact of water use efficiency in the production stage on the efficiency of sustainable development of water resources (sustainable development stage). The Malmquist productivity index is applied to objectively analyze the productivity changes at each stage. Finally, we employ Moran’s I index to evaluate the spatial correlation between the total efficiency and productivity of the 31 regions. Findings show that the efficiency of the production stage is higher than that of sustainable development, and the efficiency of sustainable development is generally low, which is the main reason for low overall efficiency. However, the productivity of sustainable development shows significant progress, and overall efficiency has a spatial correlation. Improving overall efficiency will help the efficiency performance of neighboring administrative regions. Therefore, relevant policies and regulations should be formulated from the national and regional perspectives, which will help improve the performance of the production stage and sustainable development efficiencies.

As a major city is often the core of a region, its inner spatial economic relationships may be a cause of larger regional disparities in economic development. However, empirical studies of the impact of uneven economic development within the inner city are rare compared to the extensive research conducted for states, provinces, and countries. This paper compares the intra-city spatial economic relationships in Shanghai with those in Beijing using Exploratory Spatial Data Analysis (ESDA). It concludes that Beijing exhibits negative spatial autocorrelation as the economic inequalities are accentuated among its 18 districts, leading to a center-concentrated pattern of development. In contrast, Shanghai shows positive spatial autocorrelation as the 17 districts in the city have synergistically benefitted from its economic growth. Moreover, the agglomeration effect in Shanghai is estimated to be higher than that in Beijing.