Banking Efficiency Determinants in India: A Two-stage Analysis

Abstract

This study aims at measuring the technical efficiency of banks in India and examining its determinants. Efficiency is said to be achieved if a bank is able to maximise its output subject to limited inputs. To obtain technical efficiency score, input-oriented Malmquist Data Envelopment Analysis is applied on two outputs and three input variables, based on a VRS (variable returns to scale) assumption. Three foreign banks—namely, A B Bank Ltd, Bank of Ceylon, and Citibank N A—and two Indian banks—namely, HDFC Bank and State Bank of India—are found to be most efficient during the study period. The efficiency scores when subsequently used as the dependent variable along with independent variables—bank size, capitalisation, liquidity risk, returns on assets, interest rate, credit risk, market concentration and gross domestic product (GDP)—in a panel regression analysis found the fixed effect model to be more appropriate in explaining the determinants. The results reveal that liquidity risk, returns on assets, credit risk, market concentration and GDP have a significant effect on the technical efficiency, while banks size, interest rate and level of capitalisation are found to be insignificant variables. JEL Classification: G21, C13, C60

Technical efficiency, intellectual capital efficiency and bank performance in emerging markets: the case of India

“…Further, we use the Malmquist index (MI) to obtain technical efficiency, which is more appropriate in panel data. MI draws a production frontier for each DMU in each year, thereby measures levels of and efficiency change over time (Coelli, 1996;Goswami et al, 2019). Thus, for estimation, we employ DEA and MI on our data set using a computer programme -DEAP, version 2.1developed by Tim Coelli.…”

Bank Profitability and Efficiency in Portugal and Spain: A Non-Linearity Approach

“…The size of the banks is also the subject of study regarding the determinants of efficiency. From the analyzed literature, it appears that Defung et al (2016), Dell'Atti et al (2015 and Goswami et al (2019), andPhan et al (2018) find a positive relationship, justifying that larger banks are more efficient, as they manage to achieve economies of scale. It should be noted that Aiello and Bonanno (2016) also document a positive relationship, also exploring a possible non-linear relationship, which they do not find for Italian cooperative banks.…”

“…Moreover, as the size is important to differentiate banks and there are mixed findings (e.g., Alshatti 2016;Athanasoglou et al 2008;Ding et al 2017;Goswami et al 2019;Gulati and Kumar 2017) of size on banking profitability and efficiency, this study seeks to answer the following research question: is there a non-linear relationship between bank size and performance?…”

“…Concerning efficiency, Defung et al (2016); Sufian and Kamarudin (2015) find a positive relationship between GDP and efficiency, justifying this relationship because the growth of the economy increases deposits and cash flows, which will increase efficiency. Aiello and Bonanno (2016); Dell 'Atti et al (2015), and Goswami et al (2019) document a negative relationship between GDP per capita and efficiency, since the greater the development of the greater the operational and financial costs that banks will incur.…”

The Efficiency of Indian Banks: A DEA, Malmquist and SFA Analysis with Bad Output

“…Along the similar lines, Ariff and Luc ( 2008) also find that large sized banks perform less efficiently than the smaller banks. Goswami et al (2019) also find that bank size is not a significant factor. Thus existing literature suggests that the sign of the coefficient of size is expected to be negative and insignificant.…”