Informatics Publishing Limited

Sanjay K. Mohanty ¹, Bidyadhar Dehury ²

Affiliations
1 Department of Fertility Studies, International Institute for Population Sciences, Deonar, Mumbai 400088, Maharashtra, IN
2 International Institute for Population Sciences, Deonar, Mumbai 400088, IN

Abstract

In October 2010, the United Nations Development Program (UNDP) disseminated the revised methodology of the Human Development Index (HDI) and added three indices, namely, Inequality in Human Development Index (IHDI), the Gender Inequality Index (GII) and the Multi-dimensional Poverty Index (MPI) to the family of human development indices. These changes were justified on grounds of measuring deprivation, poverty and inequality in the state of human development within and across countries. This paper compares the estimated HDI using the old and new (revised) methodology, and examines the feasibility of constructing the new human development indices (IHDI, GII and MPI) in the states of India.

Results indicate that the value of HDI computed using the new methodology is substantially lower than that computed with the old methodology cutting across the states. However, the overall ranks of the states in the new and old HDI are similar. The computation of life table for socioeconomic groups would be helpful to disaggregate HDI and IHDI. The MPI can be computed using data from the National Family and Health Survey-3, but it needs considerable improvement in the conceptualisation and contextualisation of multi-dimensional poverty indicators.

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Shruti ¹, Sanjay K. Mohanty ²

Affiliations
1 Centre for Study of Social Exclusion and Inclusive Policy, Banaras Hindu University, Varanasi 221005, U.P., IN
2 Department of Fertility Studies, International Institute for Population Sciences, Mumbai 400088, IN

Abstract

Using the unit data from 61^st and 66^th rounds of consumption expenditure surveys carried out by National Sample Survey Organisation, this paper examines the change in household health spending of demographically advanced and transitive states of India. Descriptive and multivariate analyses are used to understand the differentials and change in health spending. Results suggest that during 2004-2010 the household health expenditure at constant prices has increased by 25 per cent in India, 32 per cent in Kerala, 33 per cent in Maharashtra and eight per cent in Uttar Pradesh. The institutional health spending in India has increased by 53 per cent compared with 15 per cent for non-institutional health spending. The increase in household health spending is higher among the poor, less educated, labourer households and among elderly households. Results of multivariate analyses suggest that households with elderly members are more likely to incur catastrophic health expenditure compared with households without any elderly member. Based on the findings, the paper suggests an increase in public spending on health to protect the poor, marginalised and elderly households from catastrophic health spending.

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Aishwarya ¹, Sanjay K. Mohanty ²

Affiliations
1 International Institute for Population Sciences, Govandi Station Road, Deonar, Mumbai 400088, IN
2 Department of Fertility Studies, International Institute for Population Sciences, Govandi Station Road, Deonar, Mumbai 400088, IN

Abstract

This paper examines the pattern of Monthly Per Capita Consumption Expenditure (MPCE) by socio-economic and demographic characteristics of households using unit data from 64th Round of National Sample Survey, India, 2007-2008. Household consumption expenditure is analysed with respect to food, non-food items, health and education. The results indicate that the share of health expenditure in India constitutes over five per cent of total consumption expenditure and it increases with age, economic status and educational level of the head of household. Medicine is the largest share of the total Out of Pocket (OoP) health expenditure. Around two-thirds of the households incurred catastrophic health expenditure. State differentials in OoP expenditure on health are large, possibly linking household expenditure to per capita income and share of public spending on health.

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