# this information.

Including village (area) fixed effects may underestimate the impacts of disaster if the shocks are perfectly correlated within a village. However, there is a cost of not including village fixed effects since unobserved village-specific factors often jointly affect child schooling in the village (e.g., change in school availability). Actual costs of flood and drought are not evenly distributed among villagers. In the analysis below, I estimate not only the direct impact of disaster but the indirect effects through pre-disaster child human capital and asset holdings, which mitigate the above problem.

One advantage of using village fixed effects is that we can control for possible substitution effects on child schooling through changes in the wage rate in the labor market if labor market conditions are homogeneous at least within the village (area). Therefore, with village fixed effects, we expect to observe negative effects of disaster on schooling (through income effects).

> As discussed in the previous section,  2 and  3 could be either positive or

> negative.  3  0 together with  2  0 implies that the recovery process from a disaster is faster, if the child embodies more human capital in the previous stage (before disaster). If the recovery process is faster for children with more initial human capital,

> the process will increase inequality in human capital among children.  3  0 implies that the disaster will decrease the inequality in human capital formation among children

> (or siblings). After a disaster, it is possible that  1  0 if adverse impacts of disaster are large and/or destructive forces due to the disaster can entirely subvert the dynamic formation of human capital (for example, if all schooling and health facilities are destroyed).

# **4. Data**

This section describes the data from Bangladesh, Ethiopia and Malawi that we use to test our hypotheses. The International Food Policy Research Institute has conducted panel household surveys in the three countries with corresponding local collaborators. The period covered in the panel data includes the occurrence of major natural hazards such as flood and drought.

In Bangladesh, the initial survey round was fielded in late 1998, immediately after the onset of the 1998 flood, followed by two subsequent rounds until the middle of 1999 (del Ninno et al. 2001). In 2004, a follow-up survey was conducted in April-May, coinciding with the season of the previous survey round, April-May 1999 (Quisumbing 2005a, 2005b).

In Ethiopia, the panel data set builds on the Ethiopian Rural Household Survey (cite), which began in a smaller sample of villages in 1989, then was expanded to 15 villages in 1994. Several rounds were conducted before 1999. For child anthropometry data, we use the 1997 round. A large drought occurred in 2001, followed by the 2004 survey. Similarly, in Malawi, the initial round occurred in 2000, followed by the 2001 drought and the subsequent round in 2004. Therefore, combining the panel data and the information on these natural hazards, we have an ideal setting to assess the impacts of natural hazards and disasters on human capital formation and the roles of ex-ante actions and ex-post responses.

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