they are mostly unskilled workers so the results are less likely to be confounded by skill level. The results in column 1 and 2 are as predicted. That is, for firms with positive foreign employment, the share of foreign employees is decreasing with the conflict, after controlling for the relative wage of foreigners over Ivorians. To control for the possibility that labor adjustment cost might affect how quickly firms can change the share of foreign workers, we add lagged employment size and its squared terms and interactions with time. The results are reported in column 2. The negative coefficient on the interaction between size and conflict dummy indicates that bigger firms might be slower to adjust but the effect is imprecisely estimated. Coefficient estimates of the wage and conflict variables are qualitatively unchanged, suggesting our prediction holds up after (partially) accounting for adjustment cost. Another important caveat is we assume firms to be maximizing profits in the model and thus have not taken into account the firm’s owner’s taste for employing Ivorian versus foreign workers.<sup>34</sup> To the extent that larger firms might be more likely to behave as profit maximizers, the results that larger firms are slower to adjust might also be driven by a taste-based We have found suggestive evidence of firms adjusting the shares of foreign employment downward to mitigate the conflict impact. Tables 13 and 14 report results from the production function estimations where such adjustment is taken into account. Effectively, the share of foreign workers is modeled as an additional (potentially negative) input in the production function and its effect on productivity is estimated directly in one step. As before, we define the start of the conflict as _t ≥_ 2000 and allow percentage foreign employees to have a different before and after effect on production. Since the production function estimations are at the industry level, the effect of foreign employment interacted with the conflict dummy is also allowed to be industry specific. We find negative and significant effects for the interaction term in five industries<sup>35</sup> and no significant impact on other industries. The results for these industries where we find a significant effect are reported in table 13. Using these coefficient estimates, the aggregate cost of having foreign workers during the conflict is estimated to be 5.4% of total output.

Next, we run the same production function estimations on sub samples of industries stratified by size to allow technology to be different for small and large firms and to make the percentage foreign employees more comparable across firms of similar size. Because of data limitations, this exercise can be done only for industries with sufficiently numerous observations. The results are reported in table 14. Here, we only find evidence of negative impact of foreign employment and conflict for firms in the Transport and communications and Commerce sectors and for larger firms in the Chemical, rubber products and building materials sector. Lack of statistical power might be responsible for the absence of impact in some industries but in general, these results confirm the findings in the earlier sections that foreign firms were impacted more by the conflict.

> 34Taste could also be changing with the conflict. If it does not change over time then fixed effects can control for such concern.

> 35Mechanical and electrical products, Construction and maintenance, Transport and communications, Rental and management of buildings, and Commerce)

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