Multi-level Supportive Policy Dataset for China's Resource-Based Cities (2003 to 2023)

Area of Science:

• Environmental Policy
• Public Administration
• Political Science

Background:

• China's governance involves central strategy formulation and local implementation with adjustments.
• Existing policy intensity research lacks comprehensive quantification, often using proxy variables.
• Current indices focus narrowly on policy objectives and instruments.

Purpose of the Study:

• To expand the concept of policy intensity by incorporating policy levels, objectives, and instruments.
• To develop a multidimensional supportive policy intensity index for China.
• To create a dataset for interdisciplinary research on environmental and green transformation performance.

Main Methods:

• Utilized word frequency analysis to quantify policy intensity.
• Analyzed 3788 government work reports from 2003-2023 across national, provincial, and prefectural levels.
• Constructed a multidimensional index covering administrative levels, objectives, and policy instruments.

Main Results:

• Developed a comprehensive, multidimensional policy intensity index.
• Created a dataset with individual and aggregated policy intensity measures.
• The dataset includes policy reports across four administrative levels, four objectives, and five instruments.

Conclusions:

• The new policy intensity index offers a direct quantification method, addressing limitations in prior research.
• The dataset provides valuable resources for analyzing the impact of government policies on green transformation and environmental pollution.
• Facilitates interdisciplinary research by integrating policy data with performance and pollution metrics.