Relationship between credit risk and return on assets in Yemeni banks using panel data models for the period (2004 - 2020)

This study examines the optimal econometric model that best captures the relationship between credit risk (CR) and bank performance, measured by Return on Assets (ROA), within Yemeni banks during 2004–2020. Credit risk is proxied by the ratio of loan loss provisions to total loans (PDL/TL), and the ratio of total loans to total deposits (TL/TD). To analyze this relationship, panel autoregressive distributed lag (Panel ARDL) models were employed, namely, the Dynamic Fixed Effects (DFE), Pooled Mean Group (PMG), and Mean Group (MG) estimators. After comparing the model estimates using the Hausman test, the PMG model was found to be the most appropriate for capturing both the short- and long-run dynamics of CR’s impact on ROA. The findings indicate that CR has no statistically significant short-run effect on ROA. However, in the long run, CR has a weak positive impact on ROA. Specifically, a 1% increase in PDL/TL leads to a 3.3% increase in ROA, whereas a 1% increase in TL/TD results in a 1.3% ROA increase. The study concludes that banks should emphasize long-term strategies, including credit portfolio diversification and sound financial policies, to mitigate credit risk and improve their financial performance.