Empirical investigation of bad loans of Indian public sector banks By using panel data approach

The banking system’s soundness is essential for economic growth and financial stability. The Indian banking system has been plagued by large amounts of non-performing assets (NPAs) in recent years, particularly in public sector banks (PSBs). This article investigates the panel data regression analysis was used to investigate the financial causes of bad loans in Indian PSBs.The study used a panel dataset of 21 Indian PSBs spanning eight years, from 2010 to 2017. In this case, net financial indicators as a dependent variable and non-performing assets (NNPAs) as an independent variable are used. The credit–deposit ratio, loan maturity, and return on investment are discovered using the random effect model. NNPAs and assets have a negative association. These variables are linked to a lower level of NPAs. Operating costs and the capital adequacy ratio have little impact on NNPAs. Priority sector loans, collateral values, and non-interest revenue, on the other hand, have a beneficial impact.NNPAs are affected. These indicators point to an increase in problematic loans, which is adding to the problem. PA build-up in PSBs.