Smart City Impact on Public Health: 270 Chinese Cities Panel Data 2007-2020

Aggregating panel data from 270 prefecture-level cities in China from 2007 to 2020, used to evaluate the impact of smart city construction on public health levels. The data was compiled by Peizhi Xiong for a study employing dual machine learning models.

Use Cases

• Analyze the relationship between smart city construction (SCC) and public health level (PHL) using panel data from 270 cities.
• Test the mediating role of ecological environment quality, innovative service level, and healthy human resource structure between SCC and PHL.
• Conduct heterogeneity analysis to compare SCC's impact on PHL across regions like western China, large cities, and key environmental protection cities.
• Apply a dual machine learning model to the panel data for causal inference on urban policy effects.

Strengths

• Panel data spans 14 years (2007-2020) providing longitudinal analysis potential.
• Covers 270 prefecture-level cities in China, offering broad geographic scope.
• Data is structured for empirical analysis with machine learning models, as demonstrated in the associated study.

Limitations

• The dataset is relatively small at 1.7 MB, suggesting limited granularity or a small number of variables.
• Specific column names, row counts, and sample data are unavailable, hindering precise assessment of structure and completeness.
• Data is focused solely on China, limiting generalizability to other national contexts.

Provenance

Source

Peizhi Xiong via figshare.

Collection Method

Compiled for a research study using smart city pilot policies as a natural experiment.

Time Range

2007 to 2020.

Freshness

Data covers up to 2020; the dataset record was last updated in 2026.

Geography

270 prefecture-level cities in China.