This study investigates the relationship between corruption and nonperforming loans in Pakistan using a sample of 18 commercial banks for period 2000-2017 where panel regression models of OLS estimator, fixed effect and random effect are employed. The results show a significant negative relationship between control of corruption and
credit risk as measured by non-performing loans indicating that tighter control of corruption would lower the non-performing loans. Furthermore, bank size shows a positive impact signifying that larger banks tend to take more excessive risks. In contrast, return on assets and capitalization negatively impacted on the non-performing loans
demonstrating that those banks which generate higher earnings and have higher capital portion could reduce the level of non-performing loans.
In addition, macroeconomic variables of GDP and inflation rate indicate significant relationship with non-performing loans since good economic
situation can increase borrower creditworthiness which leads to lower default payments. Furthermore, both Hausman and Lagrangian
Multiplier tests show that the random effect is preferred over fixed effect and OLS, respectively. The findings provide insights to policy makers
in making strategic decisions regarding non-performing loans with regards to corruption as well as bank-based and macroeconomic indicator
