The table shows interesting results. Children of displaced households are better-off economically and more educated than households that were not displaced. They are also less likely to be farmers. On the other hand, households that report having their house destroyed by violent attacks are less educated and more likely to be farmers. These key features hold when we look at the relevant characteristics by gender. Significantly, we find also that children (aged 10-12<sup>14</sup> ) affected by displacement are more likely to work than children affected by house destruction. The difference is not however statistically significant. We find statistically significant differences in labor market outcomes by gender. Notably, we notice that displaced boys are more likely to work and for longer hours than boys that were not affected by displacement. The opposite is true for girls.

The interaction between displacement and house destruction provides further insights into how the characteristics of children and their families differ relative to the type of violence they have been exposed to. Households affected by both shocks are more likely to be farmers, less educated and the poorest among the considered categories. This suggests that displaced households are likely to be urban households belonging or in some way related to the Timorese intelligentsia, who would have fled their areas of residence for fearing of being easily targeted by the Indonesian troops (see section 3). Households that report house destruction only or both displacement and house destruction are likely to be indiscriminate victims of ̳scorch-earth‘ tactics employed by the Indonesian troops while moving back to West Timor (section 3).

The discussion above leads us to conclude that the likelihood of an individual having been affected by the 1999 violence was not a totally random phenomenon, and there are observable characteristics of the households related to the likelihood of having been affected by the violence. There may also be unobserved household and individual characteristics which are correlated both with the conflict and the outcome variables.<sup>15</sup> This may potentially lead to biases in the analysis, which are typically corrected through instrumental variable estimation techniques.

The economics literature on violent conflict usually employs geographical correlates of violence at a suitable level of analysis (village or district) as instruments for self-reported conflict information. Unfortunately, the codes for sampled villages and districts in Timor Leste were not disclosed in the 2001 TLSS, and we are unable to employ this strategy in the analysis. We only have suitable information at the area level. As Timor Leste is divided into only five areas, the IV estimator is not reliable at that level. However, we are able to make use of the DID estimation

> 14 Employment characteristics are collected only on individuals of 10 years or older.

> 15 One of the most common omitted variables in empirical research on the impact of violent conflict is the level of support of households for armed groups (see Wood 2003, Petersen 2001). Another common omitted variable is the level of control of different armed factions (Kalyvas 2006). In the case of Timor Leste, the level of control of FRETILIN and the Indonesian troops is likely to vary with the geographical characteristics of each area, as well as their proximity to West Timor.

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