Floods and children’s learning outcomes in rural India: Do resilient communities offer protection?

• In Event: Highlighted Session: Climate-induced disadvantage: The effect of extreme weather events and natural disasters on children’s educational outcomes in climate vulnerable countries

Proposal

Background. India is a highly flood-prone and home to the world’s largest number of school-aged children, the majority of whom live in rural areas. In such areas, exposure to frequent and severe floods can lead to difficulties in school access for students and teachers, school closures, and infrastructure damage. The result may be reduced enrolment, reduced attendance, and, ultimately, reduced learning. Moreover, children from marginalized populations and communities might be particularly vulnerable to experiencing floods.

Research questions. Using a nationally representative longitudinal survey, our study examines for children age 8-11 years (i) whether resilient communities, conceptualized in terms of their economic, social, and educational resources, buffer the impact of flood disasters on children’s learning, (ii) whether protection extends to the most marginalized households within communities, and (iii) whether protective effects are mediated by reducing the household economic impact of floods.

Data. Our sample includes children in rural households in the India Human Development Survey (IHDS). The IHDS is a nationally representative multi-topic survey of over 41,000 households in 971 urban blocks and 1503 villages. It is a panel survey with interviews conducted in 2004-5 and 2011-12.

Methods. We consider three educational outcomes-- foundational reading skills, basic math skills and school progression. Our first empirical model investigates whether resilient communities protect children’s learning when floods strike. We perform a community-level analysis of effects of flooding on (a) mean, (b) standard deviation and (c) the bottom 20th percentile of the distribution for each educational outcome. These estimates go beyond the usual focus on average effects to also examine a measure of inequality and the bottom part of the distribution. We allow for the possibility that indicators of community resilience modify the flood impacts. In effect, we estimate multivariate relations of the following form for the community estimates:

E_(c,t)= μE_(c,t-1)+F_(c,t) (β+ C_(c,t)*γ)+X_(c,t) α+ε_(c,t)

where E_(c,t) is is a vector for educational outcomes in community c and year t; F_(c,t) is a vector for the community flood experience including the intensity; C_(c,t) is a vector with community characteristics including those related to resiliancy; X_(c,t) is a vector of community controls (including C_(c,t) ). β is the vector of estimated impacts of dimensions of floods on a particular educational outcome and γ is a vector of estimated heterogeneities of these impacts for the same educational outcome due to community characteristics including resiliency. Note that a significantly positive μ would indicate both immediate and persistent (though fading) effects on education through lagged outcome variables.

Our second model modifies the above equation by replacing C_(c,t) with interactions between indicators of community resilience and of the extent of membership in marginalized groups at the community and individual levels. This allows us to examine whether community features confer different degrees of protection on children from marginalized groups. Finally, to explore whether protective effects in resilient communities are mediated in part via reduced household economic impacts of floods, we replace C_(c,t) in the equation with interactions between indicators of community resilience and indicators for household economy at the individual level.

Authors

• Nazar Khalid, University of Pennsylvania

• Emily Hannum, University of Pennsylvania

• JERE RICHARD BEHRMAN, University of Pennsylvania

• Amrit Thapa, University of Pennsylvania