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Understanding multi-layered sanctions: A firm-level analysis

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  • Javad Shamsi

Abstract

This paper examines which types of firms are hit by multi-layered sanctions, quantifies the extent of the economic impact on the affected firms, and identifies the channels through which these effects are propagated. To this end, I use a text-based approach from computational linguistics to gauge the exposure of publicly listed Iranian firms to sanctions, validating this measure through its anticipated fluctuation over time and across industries. The findings reveal three key insights. First, Iranian firms report significant challenges due to sanctions, exceeding COVID-19 concerns by up to 20%. Second, politically-connected and non-connected firms suffer equally from sanctions; for every $1 loss inflicted on connected firms, an externality of $5 is imposed on non-connected firms, considering their economic scale. This contradicts the idea that sanctions only inflict harm on political decision-makers. Third, sanctions are hurtful; firms with higher exposure to sanctions endure greater losses in stock market value in the wake of unanticipated sanction events. Sanctions also lead to reduced sales, investment and hiring. Furthermore, the study reveals that sanctions impact firms via several mechanisms, the primary one being the limitation of access to export destinations.

Suggested Citation

  • Javad Shamsi, 2023. "Understanding multi-layered sanctions: A firm-level analysis," CEP Discussion Papers dp1956, Centre for Economic Performance, LSE.
  • Handle: RePEc:cep:cepdps:dp1956
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    Keywords

    economic sanctions; firms; text-as-data; computational linguistics;
    All these keywords.

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