Bank Disclosures and their Impact on Credit Risk: Evidence from Bangladesh

Abstract

Article History JEL ClassificationC12; C23; G21; G32.The only way to ensure a well-informed response to bank risks is by ensuring transparent disclosures that flourish with potential synergy. This study investigates the impact of bank disclosures on credit risk where panel data are used. PCSE and FGLS regression models are applied to a sample of 32 commercial banks in Bangladesh from 2010 to 2014. The results reveal that bank disclosures index, non-sponsor ownership and advances to total assets are inversely associated with bank risk, whereas government ownership, capital adequacy ratio and tier 1 capital have a positive effect. The study's findings have a twofold implication for the national economy. First, the higher number of disclosures portrays a transparent image in users' minds that decreases stock volatility and the cost of capital. Second, policy makers should rethink government ownership with respect to the absorption of serious risk. Therefore, it is highly recommended either to denationalize or to reduce government ownership. Contribution/ Originality:This study is one of very few studies which have investigated the relationship between bank disclosures and credit risk in the developing country context. It found that bank credit policies are tremendously affected by the government ownership. Thus, this paper will contribute to the research related to credit risk management.

The Common Market for Eastern and Southern Africas (COMESA) Free Trade Area (FTA) and Foreign Direct Investment (FDI) Nexus

“…The parameters yielded by OLS/ PE will be consistent with the real value, but variance problem will not be minimized due to type I error, and that why the FGLS is an efficient methodology to address this problem. Following some relevant methodologies, we conducted the following alternative robustness analysis by applying FGLS (Al-Malkawi & Pillai, 2018;Canarella & Gasparyan, 2008;Schmitz & von Hagen, 2011;Zheng, Sarker, & Nahar, 2017) as shown in the Table 9.…”