A gridded establishment dataset as a proxy for economic activity in China

Area of Science:

• Economic Geography
• Socioeconomic Dynamics
• Data Science

Background:

• Measuring economic activity geographically is crucial for research and policy.
• Existing data often lacks spatial resolution and temporal coverage, obscuring socioeconomic dynamics.
• High-resolution, long-term data on economic activity distribution is largely unavailable.

Purpose of the Study:

• To construct a high-resolution dataset of economic activity in mainland China.
• To enable quantitative analysis of spatiotemporal patterns in firm establishment and closure.
• To uncover underlying principles of industrial and economic development dynamics.

Main Methods:

• Construction of the Gridded Establishment Dataset (GED) at a 0.01° resolution.
• Inclusion of approximately 25.5 million firm registrations (openings and closures) in mainland China.
• Data spans the period from 2005 to 2015, providing long-term observability.

Main Results:

• The GED provides fine granularity and long-term observability of economic activity.
• Enables quantification of spatiotemporal patterns of establishments and urban vibrancy.
• Facilitates deeper insights into the dynamics of industrial and economic development.

Conclusions:

• The GED is a valuable resource for studying economic geography and socioeconomic dynamics.
• High-resolution data is essential for understanding complex economic development patterns.
• The dataset supports research into the fundamental principles governing economic growth and industrial change.