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

Purpose - This 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/approach - The 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. Findings - The 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/value - This paper in the Indian context examines the influences of technical efficiency and ICE after controlling bank-, industry-specific and macroeconomic factors.