sanctions did not affect full/part-time employment. This reduction in income is independent of worker’s abilities since it is due to a shock in the economy whose effects do not depend on skills and abilities.

Table 2: Effect on Family Income

|Panel A: Real Family Income||Total Income|||Labor Incom|e|
|---|---|---|---|---|---|---|
||(1)|(2)|(3)|(1)|(2)|(3)|
|Treat _×_ Post2007|-0.154<sup>_∗∗∗_</sup>|-0.149<sup>_∗∗∗_</sup>|-0.144<sup>_∗∗∗_</sup>|-0.160<sup>_∗∗∗_</sup>|-0.155<sup>_∗∗∗_</sup>|-0.154<sup>_∗∗∗_</sup>|
||(0.036)|(0.026)|(0.020)|(0.035)|(0.025)|(0.022)|
|R-squared|0.197|0.429|0.460|0.173|0.348|0.372|
|Observations|20,731|20,731|20,731|20,731|20,731|20,731|
|Panel B:|R|eal Wage Ra|te|Week|ly Working|Hours|
||(1)|(2)|(3)|(1)|(2)|(3)|
|Treat _×_ Post2007|-0.111<sup>_∗∗∗_</sup>|-0.115<sup>_∗∗∗_</sup>|-0.097<sup>_∗∗∗_</sup>|-0.731|-0.654|-0.734|
||(0.037)|(0.032)|(0.030)|(0.782)|(0.804)|(0.745)|
|R-squared|0.204|0.403|0.429|0.218|0.230|0.271|
|Observations|9,951|9,951|9,951|9,951|9,951|9,951|
|Demographic controls|No|Yes|Yes|No|Yes|Yes|
|Year FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Province & Industry FE|Yes|Yes|Yes|Yes|Yes|Yes|
|Province _×_ Year|No|No|Yes|No|No|Yes|

_Source_ : Iranian Households Income and Expenditures Surveys (HIES). Note: The table presents estimated coefficients of _T reat × P ost_ 2007 ( _γ_ in equation (1)) for household income, wage rates, and weekly working hours for the respective model specification. Dependent variables (total income, labor income, and wage rates) are log transformed and deflated by consumer price index (CPI) which equals 100 in year 2011. The time period for household income (total and labor income) is 1995â2013. The time period for wage rates and weekly working hours is 2006â2013 because weekly working hours are not observable for years before 2006. 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. _∗_ Significant at 10% level; _∗∗_ significant at 5% level; _∗∗∗_ significant at 1% level.

# **5.1.1 Placebo Studies**

To assess the credibility of my results, following Abadie et al. (2015), I examine in-space placebos. To do so, I apply the synthetic control method to every 11 industries in the donor pool, assuming it was treated in the year 2007. If the placebo effects are as large as the main estimate, then it is likely that the estimated effect on family income was observed by chance. Figure 2 panel (c) shows the distribution of the post/pre-treatment ratios of root mean squared prediction errors (RMSPE) for the actual treated group (the black one) and all the industries in the donor pool.<sup>43</sup> The actual treated unit (oil & gas and energy supply) clearly stands out with the highest RMSPE ratio. Also, Figure 2 panel (d) displays the average family income gap between the actual treated unit and its synthetic (bold line) as well as the respective gaps for placebo industries. Whereas there is no significant difference in the family income between the actual treated households and the synthetic control in the pre-sanction period, it experienced large negative effects over the years of sanctions. No other placebo industry experiences a similar change. Thus, the placebo tests suggest that these results are not due to chance. Section 6 provides further robustness checks by considering in-time placebos, different periods, and different model specifications (Table **??** ).

> 43RMSPE measures the magnitude of the difference between each industry and its synthetic control in the outcome variable. A small preintervention RMSPE and a large postintervention RMSPE can be indicative of a large effect of the intervention (Abadie et al. (2015)).

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