(untitled) (Journal of Economics and Sustainability, 2019)
This study examined the factors that impact the changes in non-performing loans (NPLs) of conventional banks in Pakistan from 2006 to 2017. The analysis was carried out using Panel Corrected Standard Errors (PCSE) as a suitable regression technique to control the data issues. The unbalanced panel consisted of 20 banks data for 12 years, with seven external variables that made up a total of 235 observations. The predictors were identified from the literature and country-specific relevance. Certain external factors, in particular, the gross domestic product (GDP) and lending interest rate (LIR), were found to exhibit a significant positive impact on NPLs. However, other factors, particularly bank credit to private sector (BCPS) and control of corruption index (CCI), showed a significant negative relationship with NPLs. The impact of unemployment (LagUR) and political stability index (PSI) on NPLs was negative but insignificant. The energy gap impacted NPLs positively but insignificant. The study considered a sample from Pakistan, and only external factors were selected; no bank-specific factors like size, liquidity and profitability were taken into account, which could have explained the variability in NPLs. NPLs are important in the stability of a banking system of a country. Therefore, NPLs and the reasons for changes in the levels cannot be ignored when considering the credit portfolio management of a bank. The negative and significant relationships between BCPS, CCI, and NPLs call for a better approach toward increased lending to the private sector and also better control over malicious lending. This study is thought to be an initial attempt to test the role of external factors identified empirically. This study adds to empirical work in NPLs and provides an insight into the role of various external factors in losses due to NPLs in the context of Pakistani banks. The study provides new evidence of bank credit to the private sector, political stability, corruption, and energy gap impact on NPLs.