Non-performing assets and technical efficiency of Indian banks: a meta-frontier analysis

Abstract

Purpose The issue of mounting non-performing assets (NPAs) in Indian banking industry is serious and attracting attention of academia and policy planners. Thus, the purpose of this paper is to test the hypothesis whether NPAs in Indian commercial banking have reached at alarming state where they start affecting the technical efficiency levels adversely or not. Design/methodology/approach The efficiency score have been computed using case model (model with NPAs as bad/undesirable output) vs control model (model without NPAs as bad/undesirable output) methodology under meta-frontier data envelopment analysis framework. Findings It has been noticed that the effect of NPAs on overall technical efficiency and its various components is insignificant. The comparison of the case models (i.e. model with NPAs as bad output) with the control models (i.e. model without NPAs) reveals insignificant difference in average efficiency scores and rank distribution of commercial banks. The major source of inefficiency is technology gap (i.e. structure, setup and objectives of banking) among public, domestic private and foreign private categories of banks. Practical implications Though NPAs are increasing in Indian banking industry and specifically in Indian public sector banks because of their compulsory lending to priority sector yet the banks have huge scope to extend credit to priority sector as the NPAs have not reached at alarming stage where they start affecting adversely the efficiency performance. Originality/value Given the fact that the banking penetrations, structure and objectives differ significantly across ownership, separate frontiers for each ownership (public, private and foreign banks) category has been used to evaluate the technical efficiency levels of 81 commercial banks operating in India over the period 2005 to 2013.

Non-performing Assets and Profitability: Case of Indian Banking Sector

“…Under the efficiency approach, technical efficiency has been employed to measure the performance of banks. Technical efficiency, as suggested by Bhattacharyya, Lovell and Sahay (1997) and Arora, Arora and Kanwar (2018), shows the potential of banking institutions and their management to transfigure resources into various financial services. Cost efficiency has also been employed to assess the performance of banking sector (Mitchell & Onvural, 1996).…”

Productive Efficiency and Non-performing Assets of Indian Banks in the Post-global Financial Crisis Period

“…We analyse the productive performance in the post-GFC period from 2011 to 2017. 3 On account of technology differences between PSBs and PVBs, we follow the meta-frontier literature (e.g., Arora et al, 2018;Casu et al, 2013;Gulati & Kumar, 2016) and treat them as separate groups and calculate their inefficiencies with respect to the group frontiers rather than a common frontier. To facilitate comparison, we include only those banks for which data are available for all the years of the study period.…”

“…In a recent study, Arora et al (2018) examine the TE of 81 SCBs from 2005 to 2013. They calculate the output-oriented TE under both the variable returns to scale (VRS) and CRS assumption.…”

“…• In relation to the previous studies (Arora et al, 2018;Fujii et al, 2014), our study uses less restricted DEA models; and • We investigate inefficiencies at two size extremes to see whether the size of operation has any relation to inefficiency.…”

Efficiency assessment of microfinance institutions: using DEA with weighted Russell directional distance model

“…We have listed a few recent studies related to these sectors. (Gandhi and Sharma, 2018; Arora et al , 2018; Farzipoor Saen and Seyedi Hosseini Nia, 2019; Lee and Joo, 2019; Owusu Kwateng et al , 2019; Tamatam et al , 2019; Ilyas and Rajasekaran, 2019; Duan, 2019; Tamatam et al , 2019).…”