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The paper analyses methodological issues concerning selection of indicators, making them scale-free and construction of composite indices within the framework of measuring human development. It reviews the existing literature in the area and highlights the key areas of concern from the viewpoint of methodology of aggregation. It discusses the implications of the assumptions underlying different techniques, currently being used in India, in the context of an empirical exercise of constructing an index of human development at state level. It examines the advantages and disadvantages of these techniques and proposes improvements therein for bringing them closer to empirical reality and thereby increasing their acceptability among the planners and policy-makers. The study suggests that exercises at determining the levels of human development at the state or district level by official agencies like the Planning Commission, concerned ministries or an international agency must enjoy large acceptability so that these can be used in policy-making. Agreements must be obtained in terms of choice of indicators, scaling, methodology of composition, etc. Establishing certain degree of uniformity in methodology through deliberations in a committee at the highest level (as was done in case of measuring poverty) will accord credence to the results and help clear the uncertainty and inconclusiveness that characterise the current debate.

Based on the recently completed MIMAP all-India household survey, this paper presents a unique and detailed poverty profile for both rural and urban India. It draws from the survey data, a variety of indicators which characterise the poor and assess the implication for the design and targeting of future social sector programmes in India. This paper also identifies and maps out various sets of transmission mechanisms linking adjustment and the welfare levels of poor households.

The paper presents estimates of maternal mortality derived from the NCAER-HDI survey (1994) for rural areas of India by broad geographical regions and by some selected background characteristics of respondents. According to these estimates, maternal mortality was 544 deaths per one lakh births roughly 12 years before the survey. The maternal mortality ratio was more than 600 in eastern and north-central India, while it was between 300 and 400 in north-western and southern India. The survey data suggest that maternal mortality levels were higher among the scheduled tribes and scheduled castes and low among Muslims. The level of maternal mortality was strongly related to amenities and infrastructure available in the village. However, its relationship with poverty and educational levels of respondents was found to be weak perhaps because the characteristics of respondents were not the ideal surrogates for sisters’ attributes.

Attention has been paid to the significance of the non-farm sector in the rural Indian economy since the early 1970s. The importance of earnings from secondary non-farm occupations is not well documented. In this paper an attempt is made to assess the contribution of the nonfarm sector across population quintiles defined in terms of average per capita income. The correlates of employment in the non-farm sector and the direct impact of a growing non-farm sector on agricultural wage rates in rural India have also been examined. The study is based on rural data from 32,000 households belonging to 1765 villages across all parts of India collected by the National Council of Applied Economic Research in 1993-94. Analysis shows that non-farm incomes account for a significant proportion of household income in rural India with considerable variation across quintiles and across major Indian states. Education, wealth, caste, village level agricultural conditions, population densities and other regional effects influence in determining the access to non-farm occupations. Direct contribution of the nonfarm sector to poverty reduction is possibly quite muted as the poor lack the assets. It has also been found that the growth of certain non-farm sub-sectors is strongly associated with higher agricultural wage rates. The analysis presented in this study suggests that the policy makers seeking to maximise the impact of an expanding non-farm sector on rural poverty, should concentrate on two fronts. First, efforts should be focused on removing the barriers to the entry of the poor into the non-farm sector. This involves improving the educational level in rural areas. Second, the policy makers should note the strong evidence of an impact on agricultural wages of the expansion in rural construction employment.