on the number of students at the basic-school level, and a small effect on the number of upper secondary school students.

Furthermore, we estimate our preferred model which includes municipality and year fixed effects to identify if there are any lagged effects of homicide rates on the number of students enrolled in school (these results are included in the Table A.3 in the Appendix). As in the case of contemporaneous homicide rates, the estimation with homicide rates that correspond to the previous school year has no effect on primary and lower-secondary school, and it has a negative but small effect on upper secondary school of about 0.47%. An interesting case is the model that includes as independent variable the two-period lagged homicide rates. The results of this estimation find a statistically significant negative effect of homicide rates on the number or students enrolled in all school levels, however these are very small, specifically, 0.1% for basic education, and 0.3% for uppersecondary school. Notably, the small negative effect for upper-secondary school persists over time.

# **Impact of Violence on Enrollment Rates**

Albeit small, the effect on the number of students (weakly found at the upper secondary school level) may be a consequence of would-be students in the municipality moving to a different area. To the extent that families with school-aged children flee the areas that are more aggravated, we would expect to see an increase in the number of enrolled students in relatively safer areas and a small reduction in the number of enrolled students in areas getting more violence. This does not necessarily imply, however, that there is an effect on student decisions but rather that there is migration of students.

In order to test this, we use household-survey data where we can analyze, not what is the impact of violence on the number of students enrolled, but on what share of children of a certain age group is enrolled.

We ran separate regressions for different age groups so that they match the schooling levels tested in the previous tables. For each set of regressions, we present results for 6-11 year olds (roughly the age of primary school children), 12-14 year olds (secondary school age) and 15-17 year olds (upper secondary school age). In addition, using data from the household level allows us to look at the decisions of individuals of ages higher than typical high school students. Therefore, we can test whether increasing violence reduces the likelihood of a college-age youth of being enrolled. For this purpose, we include two regressions, one for 18-20 year olds, and 21-24 year olds; both groups fall within common age-range of college-level students.

Because these regressions are using Census (and Conteo) data, we can only use data for 2000, 2005 and 2010. Panel A shows the regressions that include data from 2000, 2005 and 2010, while Panel B shows 2005-2010 (which is the closest we can get to the 2007-2010 comparisons made in analysis form previous tables). From Column 11 onwards, we use the “drug-related homicide rate” variable. However, this variable only starts in 2007. Thus, regressions in columns 11-15 assign the 20