Related Experiment Video
Updated: Aug 15, 2025

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
Published on: January 20, 2023
How the Pilot Low-Carbon City Policy Promotes Urban Green Innovation: Based on Temporal-Spatial Dual Perspectives
Xianghua Yue1, Shikuan Zhao2, Xin Ding3
1School of Economics and Management, Xiangnan University, Chenzhou 423000, China.
Abstract:
Enhancing green innovation levels is an important objective of the pilot low-carbon city policy (PLCC) in China, but the spatial and temporal heterogeneity of the PLCC policy's effect on green innovation is unclear. Based on panel data from 285 Chinese cities during 2005-2020, this paper assesses the impact of PLCC on regional green innovation using the difference-in-difference (DID) method. The empirical results demonstrate that the PLCC can obviously promote urban green innovation. In terms of the temporal dimension, the policy effect of PLCC on regional green innovation shows an inverted "U" shape and peaks in the seventh year after implementation. From the spatial dimension, the PLCC can promote surrounding cities' green innovation through spatial spillover effects within 200 km, and the spillover effect decreases with increasing distance. Mechanism analysis indicates that the PLCC policy can promote regional green innovation by enhancing regional environmental regulations and alleviating financing constraints. This paper explores the temporal and spatial policy effects of PLCC, which can provide effective paths and policy recommendations for China to achieve its "dual carbon" goals.
Related Concept Videos
Design Example: Sustainability in Concrete Building
There are multiple approaches to achieve sustainability in a commercial concrete building. For instance, construct a concrete parking area under the building, utilizing pervious concrete paver blocks in open areas to facilitate rainwater collection through an underground...
Global Climate Change
The Carbon Cycle
Levels of Use of a GIS
Thematic Layering in GIS
Social Traps

