I follow the approach of Abadie and Gardeazabal (2003) and Abadie et al. (2010), weighting industries to construct a synthetic counterfactual that replicates the characteristic of treatment group before exposure to the sanctions.

# **4.1 Synthetic Control Group Strategy.**

The SCM is based on the idea that when an intervention affects a small number of units, a combination of unaffected unites provides a better comparison group, especially when no single unit alone is comparable to the affected units (Abadie (2021)).

In the ideal case, sanctions would be an independent random event for targeted industries that had no spillover effect to other industries. Although the 2006 sanctions targeted specific firms and individuals mostly in the oil and gas industry, the present analysis is not such an ideal case because Iran’s economy is dependent on oil exports. Thus, sanctions indirectly impacted some other industries through the government budget and exchange rates.

I define households in which the head works for either oil and gas industry or energy supply (electricity, gas, steam and air conditioning supply) as the treated group.<sup>31</sup> Although the sanctions affected many sections of Iran’s economy, the severity is different across industries: (1) based on detailed policy documents on the 2006 sanctions, people who work in the oil and gas industry were directly affected by the sanctions. Also, some firms in other industries (including some firms in rubber, plastic, and mineral products industry, financial sector, motor vehicles industry, and basic metals industry) that owned or control by IRGC or Setad were directly affected by the sanctions (Source: the sanctions documents and Draca et al. (2019)).<sup>32</sup> Since the name of these firms are not observable in the main data used in this paper, I discard the entire financial sector and those subcategories of industries that include one of these targeted firms; (2) the industries that need to import raw materials and industries that are dependent on oil exports suffered from trade restrictions and the increase in the exchange rate, for example the energy supply industry was hit hard. After the oil and gas industry, the energy supply industry experienced the largest negative growth rate of value-added during the sanctions. Although this effect is indirect, since it is large and immediate, I include households in which the head works for the energy supply industry in the treated group. Other industries that were indirectly affected experience relatively small changes with a lag.<sup>33</sup> (3) there are some industries that are regulated by the government and/or are not dependent on trade, thus these industries were hardly affected by the sanctions (e.g., information industry); (4) the export-oriented industries and the industries that have foreign rivals benefited from the increase in the exchange rate as a result of sanctions (e.g., agriculture and food industries).<sup>34</sup> The definition of the comparison group is crucial, as it should capture the counterfactual outcomes trend in the absence of the sanctions. One potential comparison group would be households in which the head works for nonoil/energy industries. This group is not a good comparison group because these households differ from households

> 31I define the household head as the person earning the highest monetary income, mostly the same as the person reported as the head of the household. Some families reported the eldest person (e.g., a grandparent) as the head.

> 32United Nations Security Council Resolutions 1696, 1737, 1747, 1803 and 1929

> 33The growth rate of the real estate and administrative and support services are also largely decreased after the sanctions. However, I do not consider households whose head works in these industries in the treated group for two reasons: first, these households have a large difference in their characteristics relative to other treated households in the oil and gas industry and energy supply; second, the negative effect of the sanctions in these industries happened with a lag.

> 34Overall, 10% of household heads work in these industries that benefited.

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