Table 4: Effect on Enrollment Rates and Years of Education

||Enrollment in<br>grade 1-9|Enrollment in<br>High School two|Attending<br>Any College|Yea<br>Educ|rs of<br>ation|
|---|---|---|---|---|---|
||(6-14 yr old)|(15-18 yr old)|(HSG, _≤_24 yr old)|(15-24 yr old)|(6-24 yr old)|
|A. No diferences across gender||||||
|Treat _×_ Post2007|0.001|-0.001|-0.048<sup>_∗∗_</sup>|-0.262<sup>_∗∗∗_</sup>|-0.117<sup>_∗∗∗_</sup>|
||(0.005)|(0.005)|(0.024)|(0.077)|(0.047)|
|R-squared|0.013|0.014|0.143|0.948|0.708|
|B. Allowing diferences across ge|nder|||||
|Female _×_ Treat _×_ Post2007|0.001|-0.014<sup>_∗_</sup>|0.007|0.127|-0.063|
||(0.006)|(0.008)|(0.054)|(0.238)|(0.155)|
|Female _×_ Treat|-0.003|0.010<sup>_∗_</sup>|-0.009|-0.458<sup>_∗∗∗_</sup>|-0.062|
||(0.004)|(0.006)|(0.028)|(0.071)|(0.041)|
|Female|0.001|-0.002|-0.026<sup>_∗_</sup>|0.358<sup>_∗∗∗_</sup>|0.059<sup>_∗∗_</sup>|
||(0.002)|(0.002)|(0.016)|(0.044)|(0.026)|
|R-squared|0.010|0.012|0.145|0.956|0.739|
|Mean|98.95%|81.76%|59.59%|10.49|7.70|
|Observations|22,560|8,231|6,217|20,450|43,011|

_Source_ : Iranian Households Income and Expenditures Surveys (HIES). Note: The table presents estimated coefficients of _T reat × P ost_ 2007 ( _γ_ in equation (1)) in panel A, and estimated coefficients of _F emale × T reat × P ost_ 2007 ( _γ_ 1 in equation (2))) in panel B for enrollment rates and years of schooling. The sample for this analysis is children of the age group that officially corresponds to each level. In panel B, I examine gender differences by estimating equation (2). For college enrollment, I limit the sample to high school graduates (HSG) who aged below 24. The time period is 1995â2013. I control for age, age-squared, and parentsâ education effects, as well as time, province, and industry fixed effects (model 2). Heteroskedasticityconsistent standard errors accounting for clustering at the province and industry level in parentheses. p-values are calculated using wild bootstrap randomization inference (WBRI). Treated: oil and gas, energy supply industries. Synthetic control: information (0.148), education (0.169), and health (0.683) industries.<sup>_∗_</sup> Significant at 10% level;<sup>_∗∗_</sup> significant at 5% level;<sup>_∗∗∗_</sup> significant at 1% level.

As, the third column of Table 4 shows, the probability of attending college significantly decreased by 4.8 percentage points after the sanctions. Also, years of schooling significantly decreased by 0.1 years for the whole sample (column 5), and decreased by 0.3 years for children aged 15-24 years who completed grade 9 (column 4).<sup>45</sup> In Iran, education is compulsory until the end of high school one (grade 9). Therefore, nonsignificant effect on enrollment in these grades (column 1) can interpret as the falsification test, because this group of children attends school anyway. Also, the sanctions had no significant effect on enrollment in high school two (column 2). If there were more dropouts before entering college and thus reduction in the proportion of high school graduates, it was hard to separate the effects on college attendance from those on high school or earlier education. Panel B of Table 4 shows that the effects are not different across gender.

I compare my results to current literature and the overall effects on the current generation to find how big these negative effects on children’s education are. My finding is consistent with the literature documenting a connection between family income and children’s education(Acemoglu and Pischke (2001); Akee et al. (2010); Bastian and

> 45The overall effect is to reduce schooling by 0.1 and 0.3 years among children age 6-24 and children age 15-24, respectively. Thus, it likely implies a positive effect for children age 6-14. It is correct that the effect for those age 6-14 is positive (0.005, but not significantly different from zero) . Since children 6-14 form 53% of total sample of children 6-24, the small positive effect on the subsample of children age 6-14, would increase the schooling by only 0.003 for total sample of children age 6-24 (0 _._ 53 _×_ 0 _._ 005 = 0 _._ 003). Similarly, since children 15-24 form 47% of total sample of children 6-24, the negative effect on the subsample of children age 15-24, would decrease the schooling by 0.123 for total sample of children age 6-24 (0 _._ 47 _×−_ 0 _._ 262 = _−_ 0 _._ 123). A simple calculation (Average Years of Schooling 22 = � ( _PiSi_ ) where _Si_ is years of schooling and _Pi_ is the percentage of children age 6-24 at different levels of education) confirms that _Si_ =0

at the prior rates of college attendance and enrollment at different education levels, years of education on average decreased by about 0.1 years after the sanctions. Also. the same calculations confirm a 0.3 reduction in years of education for children age 15-24, and a 0.005 increase in years of education for children age 6-14 (which is consistent with the estimated coefficients). Thus, the overall effect on years of schooling equals to (0 _._ 53 _×_ 0 _._ 005 + 0 _._ 47 _× −_ 0 _._ 262 = _−_ 0 _._ 1) 21