outlined above to correct for potential endogeneity problems. To this purpose, we take advantage of the panel nature of the data in order to employ a fixed effect estimator methodology (FE, hereafter).<sup>16</sup> In this way, the effect of a variation of the specified covariates is the same for all individuals and over all periods of time, but the average effect for each individual _i_ can be different from individual _j_ . The FE estimator allows us to wipe out all time-invariant unobserved characteristics, which may be correlated with the conflict measure and with our dependent variable. Therefore, we take advantage of the longitudinal design of our ̳ _ad hoc’_ panel data in order to eliminate individual unobserved heterogeneity. The FE model does not account for time-variant omitted variables. Our specification includes thus year dummies that allow us to control for this unobserved time-variant heterogeneity.

In addition to potential sample biases, the results may also contain identification biases. One potential threat to our identification strategy is that trends in education before the 1999 violence were not ̳ _parallel’_ between affected and not affected group. The violation of this assumption would lead to wrong conclusions because pre-existing trends could then be driving post-conflict education outcomes. We have examined the average educational grade achieved before the 1999 violence of affected and not affected groups of individuals. Figures 6a and 6b show that trends in education levels of affected and not affected groups were parallel for cohorts which were not exposed to the 1999 conflict during primary school years and were old enough in 1999 to have completed at least their primary school level.<sup>17</sup> The graphs are done by estimating separate kernel-weighted local polynomial regressions of attained grade of education against age using an Epanechnikov kernel. Given the in figures 6a and 6b, it is unlikely that pre-existing trends may be driving our postconflict outcomes.

# **4.2. Identification strategy: The impact of violence on primary school completion in 2007**

The second aim of this paper is to analyze the longer term effect of the conflict on primary school attainment in 2007. In this section, we focus on the analysis of the impact of the 1999 violence on educational attainment in 2007, and compare this with the impact of peaks of violence during the earlier stages of the conflict on education attainment outcomes among boys and girls living in areas

> 16 We think that a FE model is more appropriate in our case than a random effect model as we would have to assume that the unobserved component of the individual fixed effects and the other covariates specified in the equation are uncorrelated. This assumption is likely to be violated in our specific case and RE estimates would be biased. We have performed the Hausman test (1978) that verifies whether the RE estimator is statistically different to FE estimator, and cannot reject the null hypothesis of the test that these effects are correlated with the other variables in the model and that ultimately the FE model is preferable.

> 17 We do not include cohorts born after 1986 as these individuals (our treated cohort) were still in primary school age in 1999. Therefore their education attainment would be censored.

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