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Fish drying is a traditional method of preserving and utilizing fish in India. Small-scale women processors play a dominant role in production and marketing of dried fish. This paper analyzes the changes in the profile of India's fish processing industry over time focusing on the dried fish segment. We postulate that structural changes in fish production, including the rapid surge in aquaculture production, are closely linked to changes in fish processing and utilization in India. In particular, surge in demand for fishmeal and fish oil (FMFO) as an ingredient in aquaculture feeds has tilted fish utilization from direct human consumption towards feed. We pool data on India's fish production, utilization, and trade to describe these changes and their implications through descriptive analysis and regression modeling. Results from the regression analysis show that the FMFO segment gains market share mostly at the expense of the dried fish segment. [ABSTRACT FROM AUTHOR]

With a total resource of 22,487 million tonnes of haematite (Fe2O3) and 10,789 million tonnes of magnetite (Fe3O4), India ranks seventh among the countries to possess abundant iron ore resources, in the world. India is not only one of the leading producers of iron ore but also at present second largest manufacturer of steel in the world (2021). Though the country can boast of huge good quality iron ore resources, the percentage of reserves to total resources is quite dismal as only 5,422 million tonnes (24%) of haematite and mere 53 million tonnes (0.49%) of magnetite resources are categorised as reserves as on 1.4.2015 as per UNFC categorisation. It is a matter of great concern that with rapid expansion in the steel manufacturing capacity, there will be unprecedented demand for iron ore for domestic consumption, since it is estimated that by the year 2030 India is likely to produce 300 m.t. of steel to meet the ever-growing domestic demand. Besides, India is likely to continue its iron ore export to keep the structural balance in the international market. In such a situation, can India equip itself to meet the surging demand for iron ore and what should be the strategy for the country not only to augment its iron ore resources but also to enhance its reserve base to a respectable level. This paper attempts to analyse the existing iron ore resources vis-a-vis demand-supply balance of iron ore for the year 2029–30, considering the pros and cons of the existing government policies. [ABSTRACT FROM AUTHOR]

Studies on the association between population ageing and health spending are inconclusive. Though per capita health spending has a strong age gradient, evidence from the developed countries attributes increasing health expenditure to high spending in terminal year of life. In India, though studies have examined the level, trends and determinants of health care spending, no attempt has been made on association of population ageing and per capita health spending across the districts of India. The objective of this paper was to examine the spatial dependencies and heterogeneities of population ageing and per capita health spending across 640 districts of India. Data from the Census of India (2011) and the consumption expenditure rounds of the National Sample Survey Organisation (NSSO) (2009–10 and 2011–2012) were used in the analysis. Univariate and bivariate LISA analysis, ordinary least square regression, and spatial error model were used to decipher the spatial pattern of population ageing and health spending in the districts of India. Results suggest that per capita health expenditure is positively associated with the proportion of the older adults (aged 60 years and above) in the districts of India. Districts with less than 5% older adults have an annual per capita health expenditure of ₹629 compared to ₹2432 in districts with older adults 12% or more. Districts of India also exhibit large spatial heterogeneity in household health spending. Bivariate Moran's I statistic of proportion of older adults and per capita annual health expenditure was 0.48, suggesting spatially association of the share of the older adults and the per capita annual health expenditure in India. Results of the spatial error model confirmed that share of urban population, mean wealth score, and mean household size are significant predictors of per capita annual health expenditure in India. This study is important to monitor the progress of universal health coverage across the disadvantaged districts and to integrate age component in universal health coverage programmes. [ABSTRACT FROM AUTHOR]