Carbon Productivity and Mitigation: Evidence from Industrial Development and Urbanization in the Central and Western Regions of China

This paper investigates carbon productivity (CP) from the perspectives of industrial development and urbanization to mitigate carbon emissions. We propose a hybrid model that includes a spatial lag model (SLM) and a fixed regional panel model using data from the 17 provinces in the central and weste...

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Bibliographic Details
Main Authors: Yongjiao Wu, Huazhu Zheng, Yu Li, Claudio O. Delang, Jiao Qian
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/13/16/9014
Description
Summary:This paper investigates carbon productivity (CP) from the perspectives of industrial development and urbanization to mitigate carbon emissions. We propose a hybrid model that includes a spatial lag model (SLM) and a fixed regional panel model using data from the 17 provinces in the central and western regions of China from 2000 to 2018. The results show that the slowly increasing CP has significant spatial spillover effects, with High–High (H–H) and Low–Low (L–L) spatial distributions in the central and western regions of China. In addition, industrial development and urbanization in the study area play different roles in CP, while economic urbanization and industrial fixed investment negatively affect CP, and population urbanization affects CP along a U-shape curve. Importantly, the results show that the patterns of industrial development and urbanization that influence CP are homogenous and mutually imitated in the 17 studied provinces. Furthermore, disparities in CP between regions are due to industrial workforce allocation (TL), but TL has been inefficient; industrial structure upgrades are slowly improving conditions. Therefore, the findings suggest that, in the short term, policymakers in China should implement industrial development policies that reduce carbon emissions in the western and central regions by focusing on improving industrial workforce allocation.
ISSN:2071-1050