A dynamic analysis of household debt using a self-organizing map.

ABSTRACT: The Korean consumer credit panel offers a well-organized set of microdata representing various characteristics of individual borrowers. To overcome the difficulty of fragmented microdata details, we construct a cluster of Korean consumers' credit, to develop a self-organizing map that visualizes individuals' characteristics along two dimensions. The result of cluster analysis reveals that most borrowers belong to one large cluster representing diligent borrowers who honor their loan payments. Conversely, several small clusters that represent borrowers with high default probability are identified, and we also found that these borrowers' characteristics vary. No significant change is found in the structure of the cluster, even when the aggregate amount of consumer credit is increased. Moreov

SUBMITTER: Kim HH 

PROVIDER: S-EPMC8391868 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature