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

Abstract

PurposeThis paper examines the impacts of technical efficiency and intellectual capital efficiency (ICE) on bank performance in India after controlling other bank-, industry-specific and macroeconomic variables.Design/methodology/approachThe authors use secondary data on listed Indian commercial banks for the period 2005–2018. The authors use data envelopment analysis (DEA) technique-based Malmquist index (MI) to obtain technical efficiency and value-added intellectual coefficient (VAIC) model for computing ICE. System generalized method of moments (GMM) (SGMM) model in a dynamic framework is used to estimate the parameters, which takes into consideration issues of endogeneity, heterogeneity and persistence of bank performance. Further, the authors use quantile regression model to examine whether the impacts of covariates are homogeneous at different locations of the conditional distribution of bank performance.FindingsThe authors find positive impact of technical efficiency and negative influence of market concentration on bank performance. The results of the study support the efficient structure (ES) hypothesis (ESH). The authors observe positive influence of intellectual capital (IC) on bank performance, which indicates the relevance of intellectual resources in enhancing banks' value. Further, the results of quantile regression indicate that the impacts of technical efficiency and ICE are more pronounced at higher quantiles of the conditional distribution of bank performance.Originality/valueThis paper in the Indian context examines the influences of technical efficiency and ICE after controlling bank-, industry-specific and macroeconomic factors.

Internet banking intensity and bank profitability: evidence from emerging Indian economy

“…The study also finds find that there is a significant positive association between diversification and bank profitability. This is consistent with the empirical findings of Tan and Floros (2012), and Maji and Hussain (2021), who argue that diversification has become an important source of bank income in the competitive environment that improves profitability.…”

“…This is in accordance with the efficient structure hypothesis (ESH). The results support the findings of Tan (2016), Batten and Vo (2019), and Maji and Hussain (2021) in the context of India and other emerging markets. With respect to economy-specific factor, there is negative impact of growth in GDP on bank profitability which supports the findings of Tan and Floros (2012) and Ghosh and Maji (2019).…”

“…The coefficient of the large bank dummy is negative and significant for ROA. The negative coefficient indicates that large banks are less profitable than small banks and support the findings of Tan (2016), Batten and Vo (2019), and Maji and Hussain (2021). The study finds positive impact of capitalization on ROA, while such impact is negative in case of ROE (insignificant in Table 5).…”

“…The alternative argument is that a high capital ratio (as advocated in the Basel norms) creates pressure for the banks to utilize the resources more productively, which in turn enhances the profitability. Empirically Menicucci and Paolucci (2016) and Maji and Hussain (2021) find a positive impact of capitalization on bank profitability in emerging markets. However, Tan (2016) observe the negative impact of capitalization on ROE in the case of the Chinese banking sector, which is also true in the present context.…”

“…Bank profitability is the dependent variable of the study, which is measured by return on assets (ROA) and return on equity (ROE). These indicators are widely used in the empirical literature to measure bank profitability or performance (Tan, 2016; Ghosh and Maji, 2019; Maji and Hussain, 2021). ROA is computed considering net profit and cash flow.…”