as is the usual custom in developing countries, then intergenerational regression coefficients for older cohorts will be biased upward. Tracking the same younger age cohort [16-27] between years has the added advantage that our estimates are comparable and are not un-duly influenced by changes in coresidency pattern over the life cycle.

While we are not aware of any paper that provides direct estimates of sibling and intergenerational correlations in education for India, some indirect evidence on intergenerational persistence in education can be found in two recent studies. Our empirical approach, however, differs in some important ways from that of the existing studies. Jalan and Murgai (2008) use the NFHS 1998/99 data to estimate intergenerational regression coefficients for different age cohorts.<sup>24</sup> Hnatkovska, Lahiri and Paul (2011) examine the probability of children having a different level of education compared with their parents among the socially dis-advantaged Scheduled Caste/Tribes relative to rest of the population using different rounds of NSS data.<sup>25</sup> In contrast to Jalan and Murgai (2008), we track influences of family background and parental education directly for the same age cohort between 1992/93 (year immediately following economic liberalization) and 2006 (15 years after liberalization). For the reasons mentioned above, we restrict our sample to younger age cohort (16-27 years), whereas the sample used in Hnatkovska et al. (2011) consists of 13 to 65 year olds.

As noted before, our main sample consists of all children in the age group 16-27 who are co-resident with the mother.<sup>26</sup> Estimation was carried out for all children and separately for brothers and sisters. Since an important objective of our study is to uncover spatial differences in intergenerational mobility, we also estimate the sibling and intergenerational correlations for subsamples defined on the basis of geographical location such as rural and urban areas, and developed and less developed regions/states. The number of observations for different sub-samples is reported

> 24 The estimated regression coefficients are in general different from the intergenerational correlations that take into account the changes in the variance of the children‘s education. Trying to uncover trends in intergenerational correlations on the basis of estimates from different age cohorts is problematic when co-residency pattern of children and parents changes over life cycle. As noted above, the coefficients tend to be underestimated for younger age-cohorts in the presence of birth effect in education and tend to be over-estimated when parents co-reside with better educated children. Thus intergenerational regression coefficients may suggest a spurious decrease in intergenerational persistence across age cohorts simply due to changes in co-residency pattern over the life cycle. 25 Hnatkovska et al. (2011) do not estimate intergenerational correlations directly. Instead they regress the probability of education switching (defined as children having different education level than parents) on scheduled caste and scheduled tribe (SC/ST) dummies for various rounds of NSS data between 1983 and 2005. The magnitudes of coefficients of SC/ST dummy are then compared to find the trend in intergenerational persistence among SC/ST compared with non-SC/ST population.

> 26 For NFHS 2006, there is also a sub-sample of children who are co-resident with father, but information on their mother is not available. We repeated our estimation procedure for this extended sample. Main conclusions are similar to those from our main sample. NFHS 1992/93 did not administer the male questionnaire, and so does not have this additional sub-sample. For comparability of results, we restrict both 2006 and 1992/92 samples to those who are co-resident with mother.

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