The banking sector of the emerging economies is continuously confronted with the puzzle of non-performing loans (NPLs). To solve this puzzle, researchers have investigated various determinants of non-performing loans; however, the issue persists. The current study explores the impact of the shadow economy, institutional regulatory framework, government stability, and corruption on NPLs among emerging economies from the period 2000-2017. We have employed a novel dynamic common correlated effect (DCCE) model to estimate the long-term relationship, which produces reliable estimates in the presence of cross-sectional dependence (CSD). We found that the shadow economy, institutional regulatory framework, and government stability negatively influence NPLs, whereas corruption is positively associated with NPLs. It implies that a 1 per cent increase in the shadow economy, institutional regulatory framework, and government stability reduces NPLs by 0.06 per cent, 0.81 per cent, and 1.87 per cent in emerging countries. The study also highlights that ignoring the issue of CSD in panel data provides unreliable estimates. It is an original work and provides reliable estimates in understanding the implication of shadow economy, institutional regulation, and corruption on NPLs among emerging countries. Besides, the findings of our study also offer several policy implications.