The information on the access to ICDS programs is available only at the village level. There is no information on which households and children within the village have actually benefited from the program.

# **_Main constructed variables_**

To assess household economic status in the absence of household income or expenditure data we construct, following the methodology of Filmer and Pritchett (2001), a linear index from a set of asset indicators using principal components analysis to derive the weights for each asset indicator. Our economic status index is the fist principal component of a number of household assets such as clock, radio, TV, VCR, refrigerator, ownership of bicycles, motorbikes, cars, as well as the type of utilities used in the household. The first principal component is an unobserved vector that explains the largest amount of variability in the observed data. The household assets based first principal component derived from NFHS-1 data accounts for 29.6 percent, and from NFHS-2 for 28.3 percent of the total variance of the relevant variables<sup>17</sup> . Availability of electricity, flush toilet, TV, and ceiling fan are the most influential variables in the estimation of the index. This finding is consistent across both surveys. The distribution of other factors in relationship to the economic status index also makes economic sense. For example, households with a higher wealth index are more likely to live in pucca (brick) houses, and have such amenities as refrigerator, motorbike and radio. They are less likely to use kerosene for lightning and wood for cooking, as well as utilize unsafe drinking water.

Our main indicators of children’s nutritional status are two indices that are commonly used to assess this from anthropometrical data. These indices are expressed in standard deviation units (z-scores) from the median for the international reference population (Dibley et al 1987a, 1987b).<sup>18</sup> Height-for-age z-score (HAZ) and weight-by-age z-score (WAZ) are defined as _(mi-mr)/_ σ _rm_ , where _mi_ is the observed height (weight) of a child of a specified age and gender, _mr_ is the median height (weight), and σ _r_ is the standard deviation of the corresponding measurement for the reference population of children in that age-gender group. Low height-for age (stunting) reflects _chronic_ under-nutrition and/or repeated bouts of illness. Low weight-for-age (underweight) reflects either or both _acute and chronic_ malnutrition and /or illness. Children who are over two standard deviations below the median of the reference population in terms of these indices are considered to be severely to moderately under-nourished (stunted or underweight). Anthropometric measurements are, of course, just one way of measuring nutrition

> 17 The first principal component based on NFHS-1 data in Filmer and Pritchett (1998) explains 25.6 percent of total variation. However, their calculation was using a slightly different and smaller set of variables.

> 18 This standard is recommended by the WHO, and the Nutrition Foundation of India (Agarwal et al., 1999) has concluded that it is generally applicable to Indian children (NFHS II India report, page 265). The use of this reference group is based on the empirical finding that well-nourished children in all population groups for which data exist follow very similar growth patterns (Martorell and Habicht 1986).

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