India’s monetary policy architecture underwent a structural transformation in April 2022 with the introduction of the Standing Deposit Facility (SDF), which replaced the fixed reverse repo rate as the floor of the Liquidity Adjustment Facility (LAF) corridor. Simultaneously, total digital payment transactions grew from 2,071 crore in FY 2017-18 to 18,737 crore in FY 2023-24 at a compounded annual growth rate of 44
This study examines the economic and institutional determinants of agricultural growth in India using annual time-series data from 1990 to 2024. The analysis employs the Autoregressive Distributed Lag (ARDL) framework along with unit root, structural break, and Granger causality tests. The results indicate that institutional credit and electricity consumption significantly drive long-run agricultural growth, while short-run effects of irrigation, subsidies, literacy, and technology remain weak. The error correction mechanism confirms a rapid adjustment toward long-run equilibrium. The findings highlight the central role of financial and infrastructural factors in shaping agricultural performance. Policy implications suggest strengthening rural credit systems, expanding infrastructure, and promoting sustainable technological adoption to ensure inclusive and resilient agricultural growth in India.
India has initiated several publicly funded health insurance schemes to work towards achieving universal health coverage (UHC), reflecting its commitment to the United Nations Sustainable Development Goals (SDGs). Globally, the realization of UHC has typically involved both demand-side and supply-side financing. However, the escalating costs of healthcare combined with low public expenditure have rendered supply-side models unsustainable, highlighting the necessity for alternative demand-side financing approaches. As a result, numerous public health insurance schemes have been established, primarily designed to cover hospitalization expenses for vulnerable populations. This paper evaluates the efficacy of these health insurance schemes in India. We assess their performance by analyzing hospitalization rates and the duration of hospital stays. The study leverages data from the 71st, and 75th rounds of the National Sample Survey (NSS) on Health to explore two distinct models: Model I utilizes the NSS 71st round and Model II employs the NSS 75th round. To mitigate the issue of selection bias, we have applied the Heckman Sample Selection model. Our findings provide compelling evidence of selection bias within our sample, highlighting the presence of adverse selection in scheme enrollment. We observed that being enrolled in these schemes correlates with a higher incidence of hospitalization, although it does not significantly influence the duration of hospital stays. Our state-level analysis confirms the same results. Furthermore, we found that the likelihood of hospitalization is more strongly associated with the availability of hospital beds than with participation in these insurance schemes. Policymakers should focus on enhancing health infrastructure because implementing insurance schemes without adequate facilities may cause inefficiencies in providing this essential public service.
The relationship between market share inequality and intangible investment is underexplored in the previous literature, despite its critical role in understanding market phenomena. This study explores the changing dynamics of the market in manufacturing industries, shedding light on intangible investment, which is increasingly acknowledged as a significant driver of competitive advantage. Analyzing company-level data from the Centre for Monitoring Indian Economy (CMIE) prowess and applying a dynamic panel data model, this paper examines the association between market share inequality and intangible investment. The study estimates iGINI coefficient to understand the individual contribution of firms to industrial inequality in Indian manufacturing sector. Estimates from a dynamic panel GMM reveal the heterogeneity in the allocation of intangible investment such as research development (R D), marketing, and advertising across firms. The findings uncover that companies with higher investments in intangibles obtain greater revenue, intensifying revenue disparities within the industries. Interestingly, the results suggest that intangible input is key to a firm’s success, while small firms are restrained with limited access due to the fixed and bulk nature of such inputs. Policy implications need to focus on enlarging opportunities to invest in intangibles for laggard firms while preventing the front-runner firms from indulging in rent-seeking.
In recent years, the importance of commercial crops has been gradually increasing in pace with the growth of the agro-based industry, the commercialization of agriculture, and the export sector of the Indian economy particularly in the post reform period after 1991. The large-scale transition from traditional agriculture to commercial crop farming has emerged as a key catalyst of agricultural growth. The present study tries to ascertain the contributions of eight major commercial crops (MCC), including tea, coffee, raw jute, Mesta, cotton, groundnuts, tobacco, soybeans, and sugarcane to Agricultural Gross Value Added (AGVA) in India for a period spanning from 1991 to 2023, with electricity consumption, pesticides, and inflation as control variables. The study employs the ARDL bounds test and the Error Correction Model (ECM) to establish the long and short-term relationships among variables. The findings of the study reveal a significant positive impact of cotton, groundnut, sugarcane, and soybean on AGVA in the long run. Further, cotton, raw jute, mesta, and soybean demonstrate a positive and significant impact on AGVA in the short run. Among other factors, EC is found to be positive and significant only in the short run. The reliability and credibility of the ARDL findings are further verified with the Fully Modified Least Squares (FMOLS) technique. The significant contribution of MCC to AGVA suggests prioritizing the production and marketing of commercial crops by emphasizing oilseed processing units, cotton value chains, and plant-based industries for sugar and ethanol production, to build an inclusive and sustainable agricultural economy in India.
