migration decision and migrants’ legal status are closely linked.

In Table A.11 in the Online Appendix, we check the robustness of the results to incorporating the legal status into the return migration equation. Column (3)—which models the return migration decision—therefore includes a dummy variable for illegal migration. We find a negative coefficient of illegality in the return migration equation, although it is not statistically significant. This suggests that there is no significant association between illegality and return decisions. As for the results from our structural equation, the estimates in column (4) consistently show that undocumented migration is associated with a wage penalty, while documented migrants witness a significant wage premium upon return. The magnitudes of the estimated wage penalty and premium are 17% and 27%, respectively. Our benchmark results reported in Table 6 were associated with an estimated wage penalty of 19% and a wage premium of 28%. These effects are therefore very comparable in terms of magnitude.

As presented in section 4.2, we also check the validity of the exclusion restriction of conflict occurrence. Since our instrument could only be predicting forced return migration due to armed conflicts and not planned return migration, we also control for unemployment rate in the destination country in the return migration equation. The unemployment rate is both country and year specific. For return migrants, the unemployment rate is matched with the year of return migration, while we matched the unemployment rate at the time of the survey in 2012 for current migrants.

We report our results in Table A.12 in the Online Appendix. We deal with the selection into emigration, legal status, and into return in columns (1) to (3). For the identification of the return migration equation, column (3) includes both the number of active armed conflicts and the unemployment rate in the destination. We find that both variables are positively associated with return migration. While an additional armed conflict in the destination country increases the probability of return migration by 2.8 percentage points, we find that a one percent increase in unemployment rate at destination is associated with 0.7% increase in the return probability. The results from our structural equation are reported in column (4) and are consistently robust to controlling for unemployment rates at destination in the return migration equation.

A related issue is that conflicts might have consequences on the Egyptian economy through, for instance, changes in trade flows, foreign direct investments, or remittances. In Table A.13 in the Online Appendix, we check the robustness of our results to controlling for the following variables in Egypt in the return migration equation: FDI (% of GDP), remittances (% of GDP), and the exports and imports of goods and services (% of GDP).<sup>28</sup> Our results from the structural equation in column (4) are also consistently robust to controlling for these variables.

> 28 Data comes from the World Bank Development Indicators. These variables are matched with the year of migration for return migrants and at the time of the survey in 2012 for current migrants. The results were also robust to controlling for these variables in the structural equation in column (4).

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