Investigating the Relationship Between Liquidity Risk, Credit Risk, and Solvency Risk in Banks Listed on the Iranian Capital Market: A Panel Vector Error Correction Model

In the aftermath of global financial crises and amid increasing complexity in banking operations, understanding and managing various types of risk—especially liquidity, credit, and solvency risks—has become a global concern for financial stability. This study addresses a critical gap in the literature by examining the dynamic interrelationships among these three types of risk in the context of emerging markets. Using data from 21 banks listed on the Iranian capital market from 2011 to 2023, we employ a Panel Vector Error Correction Model (VECM) alongside panel impulse response analysis to assess both short- and long-term dynamics. Our results reveal that an increase in liquidity positively impacts bank solvency, while credit risk negatively affects solvency but does not significantly influence liquidity risk. These findings contribute to the theoretical understanding of systemic risk interactions in banking and provide practical insights for policymakers and financial institutions seeking to enhance risk management strategies in volatile market environments.