STs” are less likely to participate, indicating a degree of jati-level variation in participation in these programs. In panel (c), which presents estimates for non-SC/ST jatis relative to excluded SC groups, we see that participation is much lower for the Shershabedi. This group has a 70 percentage point lower probability of participating than SC respondents. Brahmins are 19 percentage points less likely to participate than SCs, and Rajputs are 40 percentage points less likely. There is even heterogeneity among Muslims: Ansaris are 38 percentage points less likely to participate in these programs, but other Muslims are only 16 percentage points less likely than their SC counterparts.

The key finding here is that even though the program aimed to offer the program to the entire groups, the actual take-up shows considerable variation by jati. There are many possible drivers of this outcome. Geographic clustering, unequal demand for the program due to occupational patterns or variations in the status of women, the bias of program implementation teams, etc. can all make a difference to program participation rates. We do not examine those possible drivers here – we simply highlight that a program that was intended to be for all vulnerable women within a group was in fact more likely to be utilized by women from specific jatis.

# 4.2 Program 2: Participation in MGNREGS

Next, we examine the caste and jati-level variations in participation in the MGNREGS. Our surveys asked households about their possession of a “job card” – a basic pre-requisite to access guaranteed employment under this program.<sup>xviii</sup> As before, we use a linear probability model to regress a dummy variable for possession of a job-card using the same set of baseline controls as in the previous specifications. We use both broad caste categories, and then jati-level regressions that first exclude non-SC/ST jatis and then exclude SC/ST jatis.

Results are presented in Table 5.2 and Figure 2.2. When we use broad caste categories, we see the expected pattern of lower participation in non-SC/ST groups. However, when we treat these groups as the omitted category and examine participation within the SC/ST group, we see considerable heterogeneity. We see in panel (b) for example, that Musahars show the strongest participation, followed by Chamars and Dushads, when compared to non-SC/ST jatis. They are four times more likely to possess a job-card than Dobha households and almost twice as likely to possess a job-card as Sardar households. In figure 2.2(c), we observe heterogeneity in take-up among OBCs who are less likely to participate in MGNREGS, presumably because of their higher socio-economic status. Shershabedias are significantly less likely to participate even in comparison to other OBC jatis.

In summary, the results from household participation in both these anti-poverty programs suggest that beneficiaries seem to be concentrated in specific jatis. The contrast between programmatic targeting and self-targeting is also interesting. The two leading sets of beneficiaries are quite different, suggesting that self-targeting has different effects by jati than programmatic targeting. Moreover, inequality within jatis seems to matter less for self-targeting than programmatic targeting. We emphasize that the differences in the jati-level variations in take-up 8