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Purpose This paper aims to compute total factor productivity (TFP) growth for India as well as for its 19 major states and to explore the determinants of TFP at the state level by considering the spillover effects. Design/methodology/approach TFP growth has been obtained using growth accounting equation. Further, the TFP growth estimates were used to derive TFP levels using the translog index procedure. Given the policy focus on building infrastructure and expanding financial access, we have estimated the impact of irrigation, electricity, road, health, education and financial depth on TFP using the Spatial Durbin Model to account for spillover effects. Findings Computing TFP growth for two sub periods, namely, 2001-2008 and 2009-2015, the study finds a deterioration in TFP growth for India as well as for 10 of the 19 states under study in the post global financial crisis period. The author find that TFP is positively impacted by irrigation, health and road infrastructure. While financial depth and education were statistically insignificant, installed capacity of electricity had a negative impact on state level TFP. Research limitations/implications 'The author provides rationale for the empirical findings considering the country context. The findings of this study act as pointers for shaping higher growth on a sustained basis in India. The study helps to assess the productivity growth in the new states, namely, Jharkhand, Chhattisgarh and Uttarakhand, that were carved out in 2000 vis a vis their parent states. This assessment is useful especially for the states of Jharkhand and Chhattisgarh which were created to address economic backwardness in certain pockets of the parent states. Originality/value First, it provides TFPG estimates for India as well as 19 major states during the 2000-2015 period. Second, this study helps to understand how TFPG for India as well as each of the 19 states have behaved in the post global financial crisis period. Third, the study helps to assess the productivity growth in the three newly created states in 2000 vis a vis their parent states. Fourth, this is the first attempt which considers the spatial interdependence among the states to estimate the impact of financial and infrastructural development on productivity in the Indian states.

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This paper studies the relationship between infrastructure and output in 28 Indian states divided into general and special categories for the period 2001–2010. It develops a composite infrastructure index for each state in each category by considering both economic and social dimensions. We find that infrastructure only influences output in general category states. Among the different kinds of infrastructures, the social variant has a greater impact on output than the economic. Interestingly, we also find that, for both categories of states, output influences infrastructure more than infrastructure influences output. Causality analysis reveals unidirectional causality from output to infrastructure and from social infrastructure to economic infrastructure. No evidence of a statistically significant impact of infrastructure or any of its variants on output for the special category states was found. These findings question the effectiveness of additional funds provided for the development of special category states.

PurposeThis paper investigates the relationship between market power and efficiency for Indian banks in order to test the validity of the quiet life hypothesis (QLH) during 2005–2019.Design/methodology/approachFirst, the bank-level DEA efficiency scores and three measures of the Lerner index: traditional, efficiency-adjusted, stochastic are estimated. Then, efficiency scores are regressed on Lerner indices plus a set of banking and economic control variables.FindingsRobust evidence against the QLH is obtained. Moreover, the conventional Lerner index suggests that market power of Indian banks, as well as of the different bank groups, increased during the study period, due to a greater reduction in costs compared to that of the price of banking services. The efficiency scores also declined for the banking system as a whole, and for all bank groups except new private banks.Originality/valueThis is the first study testing the QLH for the different categories of Indian banks and also provides robust inferences by using both stochastic and non-stochastic measures of market power.