DETERMINANTS OF BANK COST EFFICIENCY: EMPIRICAL EVIDENCE FROM BANGLADESH

Authors

  • Israth Sultana
  • Mohammad Morshedur Rahman University of Chittagong, Chattogram, Bangladesh

DOI:

https://doi.org/10.32890/ijbf2020.15.1.9931

Keywords:

Cost efficiency, risk, capital regulation, banks, panel data

Abstract

Due to the trust of depositors, banks should be responsible for efficient utilization of resources to achieve cost efficiency (CE) which in turn contributes to raising income. Previous studies found that the average CE of banks in Bangladesh was around 80%. This study aims to find the determinants of CE in Bangladesh from a sample of 33 banks during a period from 2009 to 2016. Stochastic Frontier Approach (SFA) was used to measure CE in the first stage. In the second stage, different types of regression estimations were used like pooled ordinary least square, fixed effect or random effect panel regression, System-Dynamic Panel Data Estimation and Arellano-Bond Dynamic Panel Data Estimation for comparison. The results showed that Generalized Method of Moments (GMM) specifically the Arellano-Bond Dynamic Panel Data Estimation was best suited for problems of endogeneity, serial correlation, heteroskedasticity and cross sectional dependence in data The results revealed that regulatory capital, risk measured by non-performing loan ratio, liquidity measured by total loans to total deposits, and level of operating costs had a significant negative impact on CE. In contrast, lagged cost efficiency, profitability, years of operation, net interest income had a significant positive impact on CE. To attain competitive advantage by performing with higher CE, policymakers should focus on capital regulation measured by capital adequacy ratio, risk level, profit earning capacity, aggressiveness of banks, bank size, years of operation and level of operating costs.

 

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Published

31-03-2020

How to Cite

Sultana, I., & Rahman, M. M. (2020). DETERMINANTS OF BANK COST EFFICIENCY: EMPIRICAL EVIDENCE FROM BANGLADESH. International Journal of Banking and Finance, 15(1), 39–71. https://doi.org/10.32890/ijbf2020.15.1.9931