Funding Costs of Vietnamese Commercial Banks: Traditional and Bayesian Approaches

Abstract

This study investigates the factors influencing the funding costs of Vietnamese commercial banks during the period 2011–2022. To achieve the research objectives, several econometric techniques were employed, including Pooled Ordinary Least Squares (OLS), Fixed Effects Model (FEM), Random Effects Model (REM), and Feasible Generalized Least Squares (FGLS). In addition to these traditional regression methods, the study also incorporates Bayesian regression analysis to enhance robustness. The proxy for funding costs is measured by the ratio of interest expenses to total liabilities. The findings reveal that bank capital and loan loss provisions exert a positive influence on funding costs. Conversely, income diversification, customer deposits, bank size, profitability, state ownership, and GDP growth are associated with lower funding costs. These results offer valuable insights for policymakers and bank managers in optimizing funding strategies.