• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.349-360
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• 2020

The study aims to empirically examine the determinants of bank margins from Pakistan, an emerging South Asian economy. To elucidate the importance of the Pakistani banking sector, secondary data has been used, which was extracted from the annual accounts of twenty-four Pakistani scheduled commercial banks (20 conventional, four full-fledged Islamic) over a sample period of 2006 to 2017. The factors identified in the dealership model and the subsequent empirical developments in the dealership model categorized as bank-specific, diversification, regulatory, and industry concentration are analyzed by applying the most-common linear dynamic panel-data estimator, the Generalized Method of Moments (GMM) estimator, developed by Arellano and Bond (1991). The findings reveal that, among the bank-specific variables, funding cost, credit risk, managerial efficiency, market share, and operating cost are significant predictors of bank margins. For diversification variables employed in the study, both variables including net non-interest income and asset diversity are as well significant predictors of bank margins. It is also found that the market concentration variable proxied by the Herfindahl-Hirschman Index (HHI) is significantly predicting bank margins. Subsequently, one of the regulatory variables, the opportunity cost of holding reserves, and one bank-specific variable, the degree of risk aversion, are insignificant in the model.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.12
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• pp.95-105
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• 2021

A prerequisite of a sound financial system is effective channeling of financial resources to efficient users; hence maximizing economic and societal welfare. To that end, the prevalence of bad loans in banks in emerging economies is a major policy concern. In an attempt to add to the growing body of literature explaining the interrelationship between macroeconomic and firm-specific factors, and non-performing loans (NPL), this paper examines data from 24 scheduled commercial banks in Bangladesh from 2008 to 2019. Macroeconomic factors as well as firm-specific factors related to profitability, capital strength, and efficiency are considered. Panel data regression analysis is performed to estimate pooled OLS, fixed effects, and random effects models. Following the necessary testing, it was found that the fixed effects model with robust standard error is appropriate. Results show that return on assets and inflation have a negative influence on NPL, but GDP growth has a favorable impact. The paper concludes by asserting that the evidence supports similar findings from studies both in Bangladesh and elsewhere and it is noted that a combination of these macroeconomic and firm-specific factors explains only a small portion of the total variation in NPL.