Panel clustering analysis has been widely used in the study of difference categories in the economic and social fields due to its advantages of analyzing data in both individual and time dimensions. After elaborating on the theory of Univariate panel data and Multivariable panel data clustering method, taking the 2008-2018 provincial panel data of Chinese residents' consumption index as an example, the R software implementation methods, procedures and specific steps of the single index and multiple indices of panel data clustering was investigated in this paper, hoping to provide a reference for the workers and researchers in economic and social statistics analysis.

Weifeng Wang, Yugui Lu. Application of Clustering Analysis of Panel Data in Economic and Social Research Based on R Software. Academic Journal of Business & Management (2021) Vol. 3, Issue 10: 98-104. https://doi.org/10.25236/AJBM.2021.031018.

[1] Bingyun Zheng. (2008). The Clustering Analysis of Multivariable Panel Data and Its Application. Application Statistics and Management, 27(02), 265-270.

[2] Zelei Xiao, Bangyi Li, Sifeng Liu. (2009). The Discussion on the Clustering Way Based on the Multi-dimensional Panel Data and Empirical Analysis. Application Statistics and Management, 28(05), 831-838.

[3] Juan Ren. (2013). Fusion Clustering Analysis of Multivariable panel data. Application Statistics and Management, 32(01), 57-67.

[4] Jianping Zhu, Minken Chen. (2007). The Cluster Analysis of Panel Data and Its Application. Statistical Research, 24(04), 11-14.

[5] Yinguo Li, Xiaoqun He. (2010). Panel Data Clustering Method and Application. Statistical Research, 27(09), 73-79.

[6] Zedong Wang, Guangming Deng. (2019). Discussion on Panel Data Clustering Based on Trend Distance. Statistics and Decision, 35(08), 35-38.