Evaluating China's regional energy and environmental efficiency by considering three internal parallel industries

Area of Science:

• Environmental Science
• Economics
• Industrial Engineering

Background:

• China's rapid economic growth exacerbates energy consumption and pollution.
• Previous studies on regional energy and environmental efficiency overlooked internal industrial structures.
• A nuanced evaluation requires analyzing parallel industrial systems within regions.

Purpose of the Study:

• To develop and apply a parallel data envelopment analysis (DEA) approach for evaluating China's regional energy and environmental efficiency.
• To identify sources of inefficiency within primary, secondary, and tertiary industries across Chinese provinces.
• To assess the impact of environmental variables, specifically CO2 emissions, on efficiency metrics.

Main Methods:

• A parallel data envelopment analysis (DEA) model was employed.
• The model evaluated energy and environmental efficiency across China's provincial regions.
• Analysis considered primary, secondary, and tertiary industrial sectors as parallel systems.

Main Results:

• Overall energy efficiency in China is low, with primary and tertiary industries being major contributors to inefficiency.
• Incorporating CO2 emissions improved efficiency scores in some underdeveloped regions.
• Significant variations in provincial energy efficiency exist, with most regions exhibiting internal industrial inefficiencies.
• Declining total factor productivity is primarily attributed to reduced technical efficiency.

Conclusions:

• China's energy and environmental efficiency requires targeted improvements, particularly in the primary and tertiary sectors.
• The parallel DEA approach offers a more granular understanding of regional economic and environmental performance.
• Addressing technical efficiency decline is crucial for boosting total factor productivity and sustainable development.