Clustering analysis of the distribution characteristics of unobserved economic regions in China——Based on multi-indicator panel data

Yang Fan

doi:10.1051/e3sconf/202127501072

All issues

Volume 275 (2021)

E3S Web Conf., 275 (2021) 01072

References

Open Access

Issue		E3S Web Conf. Volume 275, 2021 2021 International Conference on Economic Innovation and Low-carbon Development (EILCD 2021)


Article Number		01072
Number of page(s)		4
Section		Energy Application and Ecological Resource Sustainability
DOI		https://doi.org/10.1051/e3sconf/202127501072
Published online		21 June 2021

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[1] Dai Dayang, Deng Guangming. Panel data clustering method based on principal component feature extraction [J]. Statistics and Decision, 2018, 34(21): 72-76. [Google Scholar]

[2] Hou Diqing. Clustering method and application research based on panel data [D]. Nanjing University of Aeronautics and Astronautics, 2016. [Google Scholar]

[3] Wang Yongxing, Jing Weimin. Regional development differentiation of China’s underground economy: cluster analysis test based on multi-index panel data[J]. Nankai Economic Research, 2014 (06): 44-57. [Google Scholar]

[4] Bordignon, M., Zanardi, A., 1997, “Tax Evasion in Italy”, Giornale Degli Economisti e Annali di Economia, Vol.56, pp.169—210. [Google Scholar]

[5] Dell’Anno, Roberto. THE SHADOW ECONOMY IN PORTUGAL: AN ANALYSIS WITH THE MIMIC APPROACH.[J]. Journal of Applied Economics, 2007, 10 (2):253-277. [CrossRef] [Google Scholar]

[6] Wang Yongxing. Has China’s economic scale been overestimated-Based on the counter-evidence of the underground economy [J]. Nankai Economic Research, 2018 (06): 74-92. [Google Scholar]