expect that households would be unlikely to borrow prior to birth in expectation of receiving any transfers. Also, while the MODE assessment suggests that funds were released in a timely fashion after applications were approved, this was likely to take place significantly later than birth itself. The program rules suggest that Rs. 500 should be received within three weeks of birth, but in practice seventy-two percent of respondents submitted the application within a month after the delivery, while the rest applied more than one month later. Moreover, applications took between 2-6 months to approve. Further surveys of local community leaders revealed that late disbursement of the immediate cash grants were a major problem, resulting in the perceived loss of their initial purpose (MODE, 2004).

We generate indicators for whether birth took place in any health facility (as opposed to at home) or a private health facility, as well as for having had any antenatal visits. We replicate our analysis for child health investments to see if the program “affects” these outcomes. Any positive and significant “effects” would be a major concern, and would cast doubt upon our previous findings, suggesting positive effects on other types of health investments may be due to some other confounding effects.

When we examine the program effects on prenatal investments (birth in a health facility or any antenatal care) (Table 12), we find no significant positive differences by gender, indeed, the direction suggests that mixed or slight negative effects<sup>13</sup> .

# **5.5 Availability of Facilities: Health Facilities and Health Investments**

The proximity of health facilities in a community is likely to be an important factor in the explaining the decision to take up health investments (Datar et al., 2007). However, at the present time data on community-level health and educational service availability is not available for NFHS-3. In NFHS-1 and 2, this information is collected only in villages, and not in urban areas. We are able therefore to replicate our previous analysis on child health and service availability using only data from the rural sector of NFHS-1 and 2. We construct three broad categories that are approximately equivalent across the two waves<sup>14</sup> : health centers (government facilities that are smaller than hospitals), clinics / dispensaries, and hospitals (private or government) and add them to our regression analysis. The results in Tables 13, 14 and 15 demonstrate that our overall findings remain substantially the same and are robust to the inclusion of these new measures of facility availability<sup>15</sup> .

# **5.6 Potentially Confounding Programs/Schemes**

> 13 We also do not find significant impacts on takeup of birth in health facilities (general or private) or antenatal care for the eligible group as a whole (although the sign of the coefficients is small but positive). 14 Ideally, we would most like to see the impact of an anganwadi, the main representative of local health services that conducts the ABAD scheme. However, NFHS-2 did not collect this data. This is a major drawback.

> 15 Note also that the presence of any health facility is not uniformly positively associated with better outcomes, possibly because certain types of facilities, such as the health centers, are indicative of the remoteness of the individual village.

16