Comperative Efficiency using Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) in the Banking Industry

Abstract

This study’s objective is to employ data envelopment analysis (DEA) and stochastic frontier analysis (SFA) to investigate the efficiency accomplishments of Indonesian commercial banking from 2018 to 2019. The first method of measuring efficiency employing a non-parametric data envelopment analysis (DEA) technique reveals that the average efficiency of 71 banks fell from 2018 (0.82) to 2019 (0.81). According to DEA findings, major banks outperform small banks on average. According to the approximated SFA Cobb-Douglas (CD) function, interest expenditure and labor expense have a positive and considerable influence on interest income. This occurs when deposit interest rates rise, banks gain interest revenue by raising lending rates, and banks increase non-interest income. According to the SFA of the Cobb-Douglas function, many banks are inefficient, particularly the first to 49th banks that arise from small banks. The Gamma value is near one (0.999), while the LR test yields a significant result of 36.14. The Cobb-Douglas SFA model is therefore applicable. The efficiency performance findings from the two models above reveal the same thing: large banks are more efficient than small banks.