lower average household wealth index were significantly more likely to have the program.

Within a given state, villages with larger populations and villages with electricity are significantly more likely to have the program. Villages that have development programs such as employment generation programs and “fair price shops’ (selling foodgrains and a few other basic food items at controlled prices), and women’s associations (Mahila Mandals) have a higher probability of being selected into the program. At the same time, such characteristics as the village’s distance to the district centers, accessibility, and the average level of women’s education are not significantly related to the probability of placement in either year.

Our results support the view that program placement follows the official policy of giving preference to villages in poorer administrative blocks, with larger population size. If politicians are modifying the application of these guidelines to meet electoral pressures, this is not to an extent that is perceptible in the data. There also seems little evidence that program placement is geared towards officials’ convenience, as the village’s connection to transport networks or distance from the district center does not increase its likelihood of being selected. A village’s likelihood of being selected is also greater if it has other development programs and community associations in place, possibly partly because this indicates the village’s ability to attract as well as to retain development programs.

# **6. Evaluation of Outcomes: Impact of the ICDS Program**

We turn now to evaluating whether children living in villages with the ICDS program have significantly different anthropometric outcomes from those living in village without the program. The unconditional distributions of child anthropometric measurements in both the 1992 and 1998 surveys is very similar among children living in villages served by the program, and those living in villages without the program (not shown). This suggests little evidence of program impact on child nutrition outcomes.

To investigate this more rigorously, we modeled the impact of the ICDS program on child nutritional status, comparing anthropometric outcomes for the children in the beneficiary villages with those of children from a comparison group of villages. We use the Propensity Score Method, which removes the selection bias due to differences between villages with and without projects (Rubin 1973), to the extent that selection of a village into the program is based purely on observable characteristics. Each child in the villages with the ICDS program (the treatment group in evaluation literature terminology) is paired with one in the villages without the program (the control group), with similar observed characteristics of the child (age, birth order and gender); of the mother (age, education, caste, religion); household wealth; and of the village (population, and development indicators<sup>25</sup> ). We then test for significant differences in nutritional

> 25 The village development indicators include electrification, drainage, road connection, primary health centre, women’s association, controlled-price shops, and development programs such as the IRDP, EGS and NREP for income-generation.

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