PurposeThe purpose of this study is to measure the level of total factor productivity of the Indian banking sector and to identify both the bank-specific and macroeconomic determinants of the total factor productivity after the global subprime mortgage crisis.Design/methodology/approachThe research sample consists of 61 commercial banks including 21 public sector banks, 18 private sector banks and 22 foreign banks. The annual data is collected from the website of Reserve Bank of India from 2008 to 2019. The authors employed the non-parametric DEA approach to estimate Malmquist total factor productivity index for each bank as well as across different ownership groups. The panel data estimation technique was used to identify the determinants of total factor productivity.FindingsThe results suggested that an increase in the technological shift raised the bank's productivity above the optimal frontier. Among the bank-specific determinants, the bank size and bank diversifications are significantly declining productivity, whereas credit-deposit ratio and return on asset significantly increasing productivity. Among the macro-specific determinants, inflation, growth rate and fiscal deficit ratio negatively affect productivity, whereas capital formation to the GVA ratio boosts the level of productivity.Research limitations/implicationsThe authors have used intermediate method to select the inputs and outputs as per the suitability to the context. However, the disaggregate level such as state and district level analysis can be done using production and value-added approaches to explore the regional variations of the banking performance. Furthermore, the parametric methods such as stochastic frontier analysis can be used to examine banking performance, which the authors left for the future research.Practical implicationsThis study suggested that banks should increase the economies of scale of their total assets and focus on the interest-earning activity. The banks need to proactively operate the business policy by following the changing path of inflation. The banks need to reduce their rate of fiscal-deficit to the GVA with the purpose to boost their level of productivity.Originality/valueThe study provides an important implication for bankers and policymakers in terms of heightening the banking performance during the period of dynamic economic events.

This study attempts to examine the adaptive market hypothesis and evolving predictability of stock returns using four decades of daily data from the Bombay Stock Exchange (BSE) and the National Stock Exchange (NSE) in India. The recent developed automatic portmanteau ratio (AVR) and wild bootstrap automatic variance ratio (WAVR) test are used for analysis. We also estimate both the AVR and WAVR statistics in the rolling window framework to examine evolving predictability. The results revealed that BSE and NSE are informationally inefficient in the weakform. The results of rolling window analysis suggested that the degree of predictable patterns evolves over the period due to global and regional economic and noneconomic events. Further, the study compare which stock market is more efficient and found that NSE is more efficient than BSE. The findings of this study provide essential inputs to investors on trading strategies in dynamic economic situations and policymakers to formulate an appropriate policy that can make the Indian stock markets efficient.

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