Determining Spatial Distribution of the BSP Supervised Banks in the Philippines: A Multivariate Cluster Analysis

https://doi.org/10.55529/jcfmbs.43.1.15

Authors

  • Vivian Sesgundo Graduate School, Polytechnic University of the Philippines.
  • Peter John Aranas Graduate School, Polytechnic University of the Philippines.

Keywords:

Financial Institutions (FIs), Spatial Distribution, Ordinary Least Squares (OLS), Cluster Analysis, Applied Statistics.

Abstract

The goal of this study was to determine the significant variables that contribute to the number of Bangko Sentral ng Pilipinas (BSP) Supervised banks in the Philippine regions. A model that can predict the number of banks needed in the region was also presented. Spatial distribution of the banks was also analyzed. These analyses determined if the current number of banks in the region is sufficient to provide the financial services needed by the people. The ArcGIS Pro was used to perform Ordinary Least Square Regression, Global Moran’s I and Multivariate Clustering Analyses to the Regional Distribution of BSP Supervised banks in the Philippines and the categorized economic, demographic, labor market and potential market variables from the Philippine Statistics Authority (PSA) in 2020. Results of this study show that the population density, economically active population, functional literacy rate, and families’ ownership of personal computer are the significant factors, which represent every category of the independent variable, that contributed to the number of banks in the region. Using the chosen passing model, the difference between the actual and estimated number of banks was used as the indicator by which regions need more physical banks to promote financial inclusion. Regions X, CAR, and BARMM are the best locations for the future physical bank to be established. Furthermore, the results from Global Moran’s I analysis showed that there is a clustering of high number of banks in the Philippines. There were 7 clusters formed for the number of banks based on population density, economically active population, functional literacy rate, and families’ ownership of personal computer. Among these explanatory variables, population density is the greatest contributor in forming the clusters.

Published

2024-04-01

How to Cite

Vivian Sesgundo, & Peter John Aranas. (2024). Determining Spatial Distribution of the BSP Supervised Banks in the Philippines: A Multivariate Cluster Analysis. Journal of Corporate Finance Management and Banking System ( JCFMBS) ISSN : 2799-1059, 4(03), 1–15. https://doi.org/10.55529/jcfmbs.43.1.15