Abstract
This paper investigates the determinants of credit growth in the ASEAN banking sector by employing the Method of Moments Quantile Regression (MM-QR) on an unbalanced panel of 185 banks from ten Southeast Asian countries over the period 2000–2022. Unlike traditional mean-based approaches, MM-QR captures distributional heterogeneity by estimating the effects of both bank-specific and macroeconomic variables across different quantiles of credit growth. This methodology is particularly effective because it provides more comprehensive insights into how determinants influence banks with different levels of credit growth. The findings reveal that non-performing loans (NPLs) negatively impact credit expansion across all quantiles, with the effect intensifying at higher levels of credit growth. Bank size, capital ratio, income diversification, and profitability exhibit non-linear effects that vary depending on a bank’s position within the credit growth distribution. On the macroeconomic front, M2 growth consistently stimulates credit, while GDP growth primarily benefits banks with lower lending activity. Inflation exerts a disproportionately negative effect on low-growth banks. The effects of financial crises also diverge: while the 2008 global crisis allowed high-growth banks to expand, the COVID-19 pandemic severely constrained their lending. These findings underscore the need for targeted regulatory and risk management policies that recognize structural differences in bank behavior and resilience across the region.