This paper applies a spatial econometric model to measure the impact of environmental regulation on urban innovation capacity from a spatial interaction perspective by using panel data from 41 cities in the Yangtze River Delta urban agglomeration from 2009 to 2018. The study findings are as follows: first, environmental regulation has a significant positive impact on urban innovation capacity and a significant positive spatial spillover effect; second, innovation capacity has significant positive spatial dependence; third, city informatization level, government expenditures on science and technology, city economic scale, and industrial development level all positively affect the innovation capacity of neighboring cities and all have positive spatial spillover effects on the innovation capacity of neighboring cities; and finally, city expansion reduces the innovation capacity of a city and has negative spatial spillover effects on the innovation capacity of neighboring cities.
To promote the development of the western region in China, it is necessary to build an indicator system to scientifically measure the level of sustainable development in Western China. Based on the construction of a sustainable development level evaluation indicator system, this study employs the panel data entropy model to evaluate the sustainable development level of four state-level urban agglomerations in Western China from 2009 to 2018. Then, the geographical detector model is used to measure the spatial heterogeneity degree of the sustainability index and detect the factors influencing the spatial heterogeneity. The results show that (1) the innovation environment and economic growth are the core factors influencing the sustainable development level. (2) The sustainable development level of the cities within the urban agglomerations varies considerably. The sustainability level of central cities and provincial capital cities is significantly higher than that of outlying cities. (3) From the perspective of time, the sustainable development level of the Chengdu–Chongqing urban agglomeration and Guanzhong Plain urban agglomeration shows a rising trend; the Lanzhou–Xining urban agglomeration fluctuates greatly; and the Hohhot–Baotou–Ordos–Yulin urban agglomeration is decreasing. (4) The spatial heterogeneity level of sustainable development among cities in the western urban agglomerations is high, economic factors play a leading role in the spatial heterogeneity of sustainable development, and the western region needs to emphasize regional coordinated development.
This paper uses the Super SBM-DEA model and GML index method with undesirable output indicators to measure GTFP in 288 cities in China. Furthermore, we divide Chinese land into east, central, west, and northeast parts, and analyze their temporal and spatial evolution trends. It is shown that, firstly, China’s overall GTFP shows an upward fluctuating trend, in which green technical efficiency contributes more to the improvement of GTFP in Chinese cities, while green technological progress contributes less. Secondly, the urban GTFP in the eastern, central, western, and northeastern regions shows obvious differences, with the source of GTFP growth in the eastern region being mainly green technological progress, the source of growth in the central region being green efficiency improvement in the early stage and green technological progress in the later stage, while the source of growth in the western and northeastern regions is green efficiency improvement. Finally, combined with spatial distribution characteristic maps and kernel density estimation, GTFP shows spatial disequilibrium characteristics in China.
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