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

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.

China’s Gridded Manufacturing Dataset

“…As the quality and quantity of the manufacturing industry grow over time 4 , the manufacturing industry eventually becomes concentrated in a few regions 5 . This industry is the driving force behind migration, industrial upgrading, segregation, and many other social phenomena 6,7 . China's coastal areas are densely populated and thus provide an ideal region for the agglomeration of the manufacturing industry; these regions have thus made major contributions to China's economic growth [8][9][10] .…”

“…As these data collection methods often lack classification systems or accurate geographic data, they have various limitations, which results in poor quality data that are lacking in temporal and spatial resolution. The most accessible databases are from the Industrial Enterprises Database (IED) 6,15 ; however, these data have only been taken at large scales and at a firm's registered address, which can often differ from the address at which the operations of the firm are carried out. For example, records of small-scale branch factories are lacking 6 .…”

“…The most accessible databases are from the Industrial Enterprises Database (IED) 6,15 ; however, these data have only been taken at large scales and at a firm's registered address, which can often differ from the address at which the operations of the firm are carried out. For example, records of small-scale branch factories are lacking 6 . More detailed quantitative data would greatly improve the robustness of industry-related research.…”

“…(Qiliang Mao, 2014) 8 Provinces in China Zhang, 2007) 37 Provinces in China (Ruibo Zhou, 2017) 38 Guangdong, China Industrial Enterprise Database (IED) (Jie Zhang, 2018) 39 Zhejiang, China ✶ ▲ ✶ ▲ Address ▲ ✶ (Xiaoping Zhang, 2012) 40 Beijing, China (Junsong Wang, 2014) 41 The Yangtze River Delta, China Economic Census Data (Xiaohan Yin, 2019) 42 Beijing, China 43 Shanghai, China (Rachel Guillain, 2010) 44 Paris, France Questionnaire (Wenhui Cao, 2016) 45 Jiangsu, China ▲ × ✶ ✶ Latitude and Longitude ✶ ✶ (Tongliang An, 2006) 46 Jiangsu, China (Ilan Elgar, 2010) 47 Toronto, Canada Business Registration Data (Lei Dong, 2021) 6 Provinces in China ✶ ▲ ✶ ▲ Address ✶ ▲ (Fa Li, 2018) 15 Cities in China Night Light Data (Xi Chen, 2011) 48 The US ▲ × × × ✶ ✶ (J. Vernon Henderson, 2012) 49 Countries 57 Cities in Spain Unavailable (Yongqiang Lv, 2021) 58 Cities in China…”

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

“…Data are available at the figshare repository [36]. The repository contains four data files, and the variable descriptions of the main file ('GED_2005-2015_v2.csv') are reported in Table 2.…”