Abstract

Measuring the geographical distribution of economic activity plays a key role in scientific research and policymaking. However, previous studies and data on economic activity either have a coarse spatial resolution or cover a limited time span, and the high-resolution characteristics of socioeconomic dynamics are largely unknown. Here, we construct a dataset on the economic activity of mainland China, the gridded establishment dataset (GED), which measures the volume of establishments at a 0.01° latitude by 0.01° longitude scale. Specifically, our dataset captures the geographically based opening and closing of approximately 25.5 million firms that registered in mainland China over the period 2005–2015. The characteristics of fine granularity and long-term observability give the GED a high application value. The dataset not only allows us to quantify the spatiotemporal patterns of the establishments, urban vibrancy, and socioeconomic activity, but also helps us uncover the fundamental principles underlying the dynamics of industrial and economic development.

Highlights

  • Background & SummaryAn uneven geographical distribution of economic activity has a crucial impact on society[1]

  • The comparability of the statistics from yearbooks across regions has been questioned by researchers due to inconsistent statistical standards in different regions[5]

  • The results show that the gridded establishment dataset (GED) can effectively reflect socioeconomic activity and achieves a better performance than that of the nighttime light (NTL)

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Summary

Introduction

Background & SummaryAn uneven geographical distribution of economic activity has a crucial impact on society[1]. In China, the main sources of socioeconomic data are statistical yearbooks, which only provide aggregated figures at the city level and cannot be used to analyze socioeconomic activity inside cities. In this paper, using approximately 25.5 million firm registration records, we construct a geographically based dataset – the gridded establishment dataset (GED) – on the economic activity of mainland China.

Results
Conclusion
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