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A Framework for Spatiotemporal Analysis of Regional Economic Agglomeration Patterns

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  • Rui Jin

    (Department of Surveying and Geo-Informatics, Central South University, Changsha 410084, China)

  • Jianya Gong

    (School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China)

  • Min Deng

    (Department of Surveying and Geo-Informatics, Central South University, Changsha 410084, China)

  • Yiliang Wan

    (College of Resources and Environment Sciences, Hunan Normal University, Changsha 410081, China
    Key Laboratory of Geospatial Big Data Mining and Application, Hunan Province, Changsha 410081, China)

  • Xuexi Yang

    (Department of Surveying and Geo-Informatics, Central South University, Changsha 410084, China)

Abstract

Understanding regional economic agglomeration patterns is critical for sustainable economic development, urban planning and proper utilization of regional resources. Taking Guangdong Province of China as the study area, this paper introduces a comprehensive research framework for analyzing regional economic agglomeration patterns and understanding their spatiotemporal characteristics. First, convergence and autocorrelation methods are applied to understand the economic spatial patterns. Then, the intercity spatial interaction model (ISIM) is proposed to measure the strength of interplay among cities, and social network analysis (SNA) based on the ISIM is utilized, which is designed to reveal the network characteristics of economic agglomerations. Finally, we perform a spatial panel data analysis to comprehensively interpret the influences of regional economic agglomerations. The results indicate that from 2001 to 2016, the economy in Guangdong showed a double-core/peripheral pattern of convergence, with strengthened intercity interactions. The strength and external spillover effects of Guangzhou and Shenzhen enhanced, while Foshan and Dongguan had relatively strong absorptive abilities. Moreover, expanding regional communication and cooperation is key to enhancing vigorous economic agglomerations and regional network ties in Guangdong by spatial panel data analysis. Our results show that this is a suitable method of reflecting regional economic agglomeration process and its spatiotemporal pattern.

Suggested Citation

  • Rui Jin & Jianya Gong & Min Deng & Yiliang Wan & Xuexi Yang, 2018. "A Framework for Spatiotemporal Analysis of Regional Economic Agglomeration Patterns," Sustainability, MDPI, vol. 10(8), pages 1-22, August.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:8:p:2800-:d:162439
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    Cited by:

    1. Lu Yang & Dan Wu & Shuhui Cao & Weinan Zhang & Zebin Zheng & Li Liu, 2022. "Transportation Interrelation Embedded in Regional Development: The Characteristics and Drivers of Road Transportation Interrelation in Guangdong Province, China," Sustainability, MDPI, vol. 14(10), pages 1-18, May.
    2. Chengfu Wang & Lijun Song & Haoqi Lu & Shuxin Zheng & Chengfeng Huang, 2022. "Assessing the Economic Energy Level of the Chengdu–Chongqing Economic Circle: An Integrative Perspective of “Field Source” and “Field”," Sustainability, MDPI, vol. 14(16), pages 1-22, August.
    3. Hongyan Shen & Fei Teng & Jinping Song, 2018. "Evaluation of Spatial Balance of China’s Regional Development," Sustainability, MDPI, vol. 10(9), pages 1-16, September.

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