households from nine districts surveyed in Tamil Nadu in the first half of 2013 (see Table 2). The surveys were designed to be representative of the target population of stateimplemented livelihoods projects. The survey populations are concentrated in the poorer regions of the three states, and we oversampled SC and ST households because they were the intended targets of the project.<sup>14</sup> For the purpose of this study, we restrict the sample to those households for which we have both household and woman-specific information.<sup>15</sup> This yields a sample of 8,969, 2,470, and 3,384 households from Bihar, Odisha and Tamil Nadu respectively.

Table 2, panel (a) summarizes the caste distribution for our data in the three states. Due to the oversampling of Scheduled Castes, almost 70 percent of the sample in Bihar, 27 percent in Odisha and 32 percent in Tamil Nadu are comprised of SCs. The BCs comprise the largest caste group in Tamil Nadu followed by SCs and Most Backward Castes (MBCs). Odisha is the only state with a significant sample of households from “general” or “forward” castes, which form the third largest caste category after OBCs and SCs. Odisha also has the highest share of ST households in our sample.

Table 2 panel (a) also contains the jati distributions considered for our analysis, arranged by state. In order to avoid unduly small cells, we focus on the major jati groups in the state and gather the smaller jatis into an ‘Others’ category for each broad caste group. Musahar (26 percent), Chamar (20 percent), Dusadh (17 percent) and Yadavs (7 percent) form the major jatis in our sample for Bihar. All belong to the SC caste group<sup>16</sup> . Khandayat 14 For clarity, we detail the design of the sampling strategy below: (i) In Bihar, 180 panchayats were randomly picked in each of the 16 blocks chosen from the seven project districts where the scale-up of JEEViKA was planned. Within each of the study villages, hamlets ( _tolas_ ) in which the majority of the population belonged to SC or ST castes were identified. Households were then randomly selected from these hamlets.

(ii) In Odisha, our sample is drawn from matched treatment-control pairs of blocks, which were obtained from a sample of 10 backward districts of the state for the purpose of the rollout of the TRIPTI plan. These were selected based on a ranking of the state’s districts using a backwardness index. The sample, therefore, includes a project block with the lowest backwardness score (treatment block) and a non-project block with the backwardness score closest to the last project block that was selected into TRIPTI (control block). Since TRIPTI explicitly targets the poor who are overwhelmingly drawn from SC and ST groups, SC and ST households are systematically oversampled in every village.

(iii) In Tamil Nadu, as in Odisha, selection of blocks within the ten districts was based on a backwardness score. This score was composed of five equally weighted indicators: percentage unirrigated area to the total cultivable land, infant mortality rate, industrial backwardness score, rural female literacy rate, and percentage of SC/ST population. The 3 to 5 most backward blocks were chosen for inclusion into the program. In every district, a pair of blocks—a treatment block with the last backward block chosen into the program and a control block that had the closest score to the treatment block with the lowest score (i.e., the last treatment block that was selected)—were selected for the sample. The oversampling of SC and ST households is proportionate to their population in the village.

> 15 Those households for which we could not match the women between the two modules have been dropped. 16 This is due to oversampling of SCs in the baseline data.

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