village of Palanpur decreased from 39 percent in 1974/75 to 29 percent in 1983/84. More recent estimates from Palanpur show that this declined even further to 17 percent by 2008/9. (Himanshu, Lanjouw, Murgai and Stern 2013).<sup>iv</sup> Beyond this literature, very little is known about inequality at the jati level. We know that most marriages occur within jatis (Desai and Dubey 2010; Banerjee, Duflo, Ghatak and Lafortune 2013), and they tend to cluster spatially, showing differing levels of political mobilization and access to basic public services (Banerjee and Somanathan 2007). Jati-based networks provide an extensive insurance network for credit, transfers and insurance during periods of vulnerability (Munshi and Rosenzweig 2006; Mazzocco 2012). Jati-based disparities in educational attainment have been remarkably persistent within states over the several decades of India’s postindependence period (Kumar and Somanathan 2017). Similarly, jati-affiliation also shapes opportunities for employment and out-migration (Munshi and Rosenzweig 2006; Munshi 2016). Jati-identity also affects women’s opportunities to work outside the household, make decisions within the household, and participate in the community (Joshi, Kochhar and Rao 2018).

Jati-level information, thus, may be key to a deeper understanding of the determinants of inequality in India. Data on jati however, are lacking in most national surveys. We know of no decomposition of inequality at the jati-level using large samples that are representative at the state level. This could have significant implications for the design and impact of poverty-alleviation programs. If some jatis can capture more benefits than others (Kumar and Somnathan 2017), jati can become an important source of “exclusion error” in the implementation of these programs. (Government of India 2017: 177).

Our data confirm the persistence of caste-based inequality, with SC and ST populations generally poorer on average than households from higher-ranked castes. Using the ELMO measure of inequality decomposition, which permits comparisons when the number of groups varies, we find that decompositions using government caste categories show that the contribution of between broad-caste inequality to total inequality stands at less than 1 percent. Decompositions using between-jati inequality are, however, nearly three times higher. We also estimate the share of between-jati inequality to total inequality _within_ a broad caste group and find that all the estimates are below 7 percent. We plot distributions of monthly per-capita expenditure to illustrate that there is substantial overlap in the distributions of the different jatis and caste-groups, but that some jatis are - to use the sociologist William Julius Wilson’s term - “truly disadvantaged” (Wilson 1987) - systematically worse off even within groups that suffer disadvantage. We also examine the role of caste in accessing large poverty alleviation programs; we examine the state-run rural livelihoods program that was the reason behind the efforts to collect these data, as well as the Mahatma Gandhi National Rural Employent Gaurantee Scheme (MNREGS). We find that some jatis, even within targetted SC and ST groups, participate more than others.

This paper is organized as follows. Section 2 provides an overview of the survey. Section 3 presents results on inequality within jatis. Section 4 illustrates how jati-based inequality affects participation in poverty alleviation programs. Section 5 concludes.

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