1999 (del Nino 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, which began in a smaller sample of villages in 1989, then was expanded to 15 villages in 1994. Several rounds were conducted before 1999. 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.

However, the exact timing of occurrence of the natural hazards and surveys matters in interpreting our empirical results, although we adopt the unique approach described in the previous sections. In Bangladesh, the 1998 flood was immediately followed by the initial round. Though the impact of disaster was realized gradually after the flood, the initial round would already have captured some short-term impact of flood exposure. The subsequent two rounds conducted within a year captured dynamic changes of the impacts. This issue is especially important in analyzing child anthropometry. However, we think that our measure of human capital investment, years of schooling completed is more robust to idiosyncratic shocks, particularly health and illness shocks that typically accompany floods.<sup>10</sup> For pre-flood assets, however, the data were constructed to reflect the pre-flood situation.

By contrast, the initial survey rounds in Ethiopia and Malawi were conducted before the 2001 droughts. Thus, the information on child schooling does not contain the potentially confounding influences of the droughts (except the parts explained by ex-ante actions). However, potential problems arise from the interval between the 2001 droughts and the 2004 follow-up survey. Given the actual impacts on income that are supposed to have occurred in 2001-2002, the interval between drought occurrence and the 2004 survey was rather short. This means that we may not capture the complete recovery process of human capital investment in the two-year period.

Malawi had a large flood in 2001-2002 after the 2001 drought. However, our preliminary analysis indicates that the impacts of the flood were rather small, compared to the drought. Therefore, we focus on the 2001 drought in Malawi for the empirical analysis. The above concern on the interval between natural hazards and the follow-up survey is also relevant.

Differences in the time structure of the hazards and the initial and follow-up rounds change the way in which we interpret empirical results. In Bangladesh, first, we may underestimate the initial impacts on child human capital since the first round, immediately after the flood, already contains some of the impacts. However, this survey is ideal to capture the recovery dynamics of human capital starting immediately after the flood. Second, in Ethiopia and Malawi, the setting is suitable to investigate the short-run impacts on human capital investment as the interval between the droughts and the follow-up survey was rather short.

Third, in Bangladesh, using the three rounds conducted in a year after the flood, we can reveal short-term changes of school attendance after the flood, though the initial

> 10For example, water-borne diseases are common after floods, and diarrheal disease in particular would affect weight for height measures. In the analyses, we use the height-for-age z scores in the range of -6 to 6.

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