The larger effect on migration of 15-17 year olds than 6-14 year olds is also consistent with our result that there was an effect on the number of upper secondary school and not on the number of basic school students, while there was a zero effect on enrollment rates in both groups.

# **Effects on the Labor Market**

Previous studies on the effects of violence on labor market outcomes for Mexico found negative effects on employment and labor force participation, particularly of women (Arias and Esquivel, 2013; Robles et al, 2013; Velásquez, 2014; Dell, 2014; and Enamorado et al, 2014). Thus, a potential channel that could act in the opposite direction of lower enrollment rates due to higher levels of violence is the re-enrollment into school of discouraged workers. Under the assumption that this hypothesis is valid, then the small/null effect on enrollment/enrollment rates could be a result of two counteracting forces (less willingness to go to school on the one hand, but a larger out of work population who could potentially enroll). This would downward bias our previous results and would thus suggest that there is in fact a negative effect of homicides on enrollment rates.

An important point to notice is that previous studies that found negative effects of violence on employment and labor force participation only estimated such an effect at the mean and by gender. They find that both employment and labor force participation declined for women while it did not change significantly for men. However, they do not study potential differentiated effects of violence on labor outcomes by age group, and thus the effect they find may not be driven by school aged population. Next, using the ENOE data, we test the hypothesis that violence affected the employment or idleness decisions of school-aged population. To do so, we divide the population between 12 and 24 into four groups that may correspond to students in lower-secondary and upper secondary education (12-14, 15-17, 18-20 and 21-24). We also divide the sample by gender to test whether there are differentiated results for women.

Table 7 Panel A estimates the regression of homicide rates on employment rates of men using the ENOE. The coefficients are all small, and most are not statistically significant, similar to what other studies have predicted. The exception is the outcome for drug-related homicides and employment rate for men between 18 and 20 years old, which correspond to the age range in the last year of upper secondary school. Table 7 Panel B presents the results of the model of the effects of violence on employment rates of women. Differently to Arias and Esquivel (2013), our estimates show no statistically significant effects of both homicides and drug-related homicides on employment rates of school-aged women.

Moreover, to test if the results we observe on enrollment rates are explained by idleness caused by violence, we present a model that regresses homicide rates on the share of young individuals that are out of both school and work. More precisely, we test whether there is an effect on the NEET rate (“Not in Education, Employment or Training”, NEET) for those in the 15 to 24 age range. Table 8 Panel A and Panel B present the estimates of the effects of violence on the rates of idle-youth divide by gender and by four groups that may correspond to students in lower-secondary and upper 28