Exploring the Spatial and Temporal Evolution of Input Efficiency in China’s New Infrastructure under Carbon Emission Constraints

Recently, China has invested heavily in new infrastructure, and its input efficiency needs to be clarified. In this study, an indicator system for evaluating the input efficiency of new infrastructure (IENI) was established from an input–output perspective. A window data envelopment analysis cross-efficiency model and a global Malmquist production index were combined to evaluate the IENI of 30 provincial-level administrative divisions in China from 2013 to 2021. The spatial and temporal evolution of the IENI was characterized in terms of spatial differences, spatial correlation, and dynamic change. The results are as follows: (1) the overall IENI in China was low during the study period, being higher in the eastern region than in other regions. Shanghai, Beijing, and Guangdong had been at a high level in terms of IENI; (2) the spatial differences in IENI across China have gradually increased and shown spatial clustering; (3) the IENI of China improved by 0.1% overall from 2013 to 2021, which stems mainly from technical change rather than technical efficiency change; and (4) the IENI in 17 provinces has improved, with Shanghai and Fujian being the fastest-improving provinces, by 1.027 and 1.026, respectively. The findings of this study help clarify the overall level, regional differences, and dynamic changes of the IENI in China and can provide a reference for Chinese governments to formulate new infrastructure input and development strategies.