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

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 socioeconomi...

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Autores principales: Dong, Lei, Yuan, Xiaohui, Li, Meng, Ratti, Carlo, Liu, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801400/
https://www.ncbi.nlm.nih.gov/pubmed/33431891
http://dx.doi.org/10.1038/s41597-020-00792-9
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author Dong, Lei
Yuan, Xiaohui
Li, Meng
Ratti, Carlo
Liu, Yu
author_facet Dong, Lei
Yuan, Xiaohui
Li, Meng
Ratti, Carlo
Liu, Yu
author_sort Dong, Lei
collection PubMed
description 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.
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spelling pubmed-78014002021-01-21 A gridded establishment dataset as a proxy for economic activity in China Dong, Lei Yuan, Xiaohui Li, Meng Ratti, Carlo Liu, Yu Sci Data Data Descriptor 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. Nature Publishing Group UK 2021-01-11 /pmc/articles/PMC7801400/ /pubmed/33431891 http://dx.doi.org/10.1038/s41597-020-00792-9 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Dong, Lei
Yuan, Xiaohui
Li, Meng
Ratti, Carlo
Liu, Yu
A gridded establishment dataset as a proxy for economic activity in China
title A gridded establishment dataset as a proxy for economic activity in China
title_full A gridded establishment dataset as a proxy for economic activity in China
title_fullStr A gridded establishment dataset as a proxy for economic activity in China
title_full_unstemmed A gridded establishment dataset as a proxy for economic activity in China
title_short A gridded establishment dataset as a proxy for economic activity in China
title_sort gridded establishment dataset as a proxy for economic activity in china
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801400/
https://www.ncbi.nlm.nih.gov/pubmed/33431891
http://dx.doi.org/10.1038/s41597-020-00792-9
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