Table 3: Effect on Education Expenditure of Households

|Dependent Variable<br>Share (2006)|log|share|per child|
|---|---|---|---|
|A. Total Expenditure|-0.111<sup>_∗∗∗_</sup>|-|-|
||(0.016)|||
|B. Categories||||
|Education<br>2.14%|-0.575<sup>_∗∗∗_</sup>|-0.051<sup>_∗∗_</sup>|-0.565<sup>_∗∗∗_</sup>|
||(0.137)|(0.021)|(0.134)|
|School Tuition<br>21.02%|-0.393<sup>_∗∗∗_</sup>|-0.033<sup>_∗∗∗_</sup>|-0.384<sup>_∗∗∗_</sup>|
||(0.139)|(0.009)|(0.131)|
|University Tuition<br>51.02%|-0.713<sup>_∗∗∗_</sup>|-0.010|-0.739<sup>_∗∗∗_</sup>|
||(0.381)|(0.026)|(0.378)|
|Books<br>39.54%|-0.344<sup>_∗∗∗_</sup>|0.001|-0.337<sup>_∗∗∗_</sup>|
||(0.082)|(0.008)|(0.078)|
|Private Tutoring<br>6.21%|-0.537<sup>_∗∗∗_</sup>|-0.020<sup>_∗∗_</sup>|-0.337<sup>_∗∗∗_</sup>|
||(0.186)|(0.008)|(0.078)|
|non-Education<br>97.86%|-0.111<sup>_∗∗∗_</sup>|0.002<sup>_∗∗_</sup>|-|
||(0.022)|(0.001)||
|Observations|20,731|||

_Source_ : Iranian Households Income and Expenditures Surveys (HIES). Note: Table presents estimated coefficients of Treat _×_ Post2007 ( _γ_ in Eq (1)). Dependent variables are total family expenditure, spending on education (by item), and spending on non-education goods and services according to COICOP classification. Dependent variables are log transformed and deflated by CPI which equals 100 in year 2011 (education spending is deflated by the Education Price Index (EPI)). The sample includes households with children aged 6-24. For school, tuition the sample consists of all households with children aged 6-24 who have not graduated from high school. For university tuition, the sample consists of households with children aged 6-24 who have graduated from high school. For spending on books and private tutoring, I consider all households with children aged 6-24. The time period is 1995-2013. I control for covariates, as well as time, province, and industry fixed effects (model 2). Heteroskedasticity-consistent 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.

# **5.2 Effect on Children’s Education**

In consequence of a reduction in the family income (-15%), affected households reduced their total expenditure by 11% (Table 3). Although spending decreased for most components, it did not decrease by the same rate. As Table 3 shows, households cut spending on education by 58% (the share decreased by 5%). The reduction in education spending reflects the combination of young children not attending school and parents cutting back on school expenditures. For instance, parents may choose free public schools instead of private schools for their children. In this section, I evaluate the effects of the sanction on quantity of children’s education (enrollment rates and completed years of education) and household spending on education.

## **5.2.1 Effect on Enrollment and Years of Schooling**

First, I find the impact of the sanctions on the educational attainment measured by enrollment rates and years of schooling. Table 4 presents the effects on school enrollment, college attendance (any post-secondary programs), and years of schooling.<sup>44</sup>

> 44The sample for grades 1-9 and high school two are children of the age group who are officially eligible for enrollment in these grades (6-14 and 15-18 years old for grades 1-9 and high school two, respectively). The sample for college attendance is high school graduates who are under the typical college graduation age ( _≤_ 24 years old).

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