Research on Weighted Cluster Analysis Method of Panel Data

Abstract

Panel data is composed of three dimensions: object, index and time, it has no mature clustering algorithm because of its complexity and dynamic data structure. Two clustering methods for multi index panel data are proposed in this paper. These two methods are respectively weighted from the index perspective and time perspective, and on this basis, the two-step clustering method is used for clustering. Then these methods are applied to cluster analysis of regional economy. The empirical results show that these two methods can effectively complete the clustering of the research objects, and have their own emphasis on the feature extraction angle of the panel data.

Driving Factors of Carbon Emissions in G20 Countries: A Weighted Average Structural Decomposition Approach

“…In order to get more accurate eigenvalue weight, this paper uses objective weight determination method, the most commonly used is the entropy weight method. Ao et al (2021) proposed two clustering methods for multi-index panel data, and weighted them by entropy method from the perspective of index and time respectively. Dai and Deng (2018) used wavelet transform to extract four features of the comprehensive score sequence.…”