on school attendance, but rather that after 4 years of a conflict in which there is broad economic suffering in locations that are not necessarily affected by violence (e.g., Tandon and Vishwanath 2020), school attendance does not vary in response to additional changes in violence in the district of residence.

However, it is possible that other factors correlated with violence or shocks causing violence and school attendance to co-move are obscuring the relationship. Furthermore, another reason that there is potentially little correlation between school attendance and the location violence is that other conflict-related shocks are more important to school attendance in this context. Investigating these possibilities, we further investigate the impact of sudden conflict-related shocks on school attendance using the WFP mobile phone survey. In particular, we investigate the impact each of the four conflict-related shocks described above on school attendance- three of them are sudden and unexpected changes in the severity of violence, and another was caused by the conflict but was not related to any specific violent incidents.

# **Section 5. Response of Attendance to Each Type of Conflict-Related Shock**

The basic empirical strategy is illustrated in figure 4, which presents the evolution of school attendance in regions affected by each of the four shocks and indicates when the shock occurred. We estimate the change in school attendance immediately after the shock happened in the affected regions and compare this change to the change at the same time in all the districts of Yemen that were unaffected by any of the four major shocks analyzed.

The first three panels of figure 4 demonstrate that there was little change in the share of households where all school-aged children attended school following the secessionist capture of regions in the south from the IRG, the onset of the partial ceasefire,27 or the capture of Al Jawf from the IRG by DFA forces. However, the fourth panel illustrates how school attendance significantly worsened following the beginning of the teacher strike in the governorates fully controlled by the IRG.28 Formalizing this comparison between shock-affected and unaffected districts, we estimate 29 the following difference-in-difference linear probability model for each shock :

# where all variables are as above, _Post_ denotes an indicator if the household was surveyed

> ~~27There appears to be an increase in the~~ share of children not attending school following the reduction in violence from the partial ceasefire, which is the opposite sign that one might expect based on evidence from other settings. However, the timing of this shock coincides with the beginning of the school year and the increase in the share of households with children not attending school at the beginning of the school year is qualitatively identical to the change observed in districts with no conflict-related shock.

> 28Figure 4a does not report attendance for the months of January and February because all districts were significantly affected by the teacher strike, which is reported in figure 4c.

> 29Given that the dependent variable is binary, we also estimate a logit specification for each shock using only the most recent survey each household completed.

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