12 datasets found
  1. H

    International Sanctions Termination Dataset

    • dataverse.harvard.edu
    • search.dataone.org
    Updated Aug 29, 2022
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    Hana Attia; Julia Grauvogel (2022). International Sanctions Termination Dataset [Dataset]. http://doi.org/10.7910/DVN/SVR5W7
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 29, 2022
    Dataset provided by
    Harvard Dataverse
    Authors
    Hana Attia; Julia Grauvogel
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    The International Sanctions Termination (IST) dataset is composed of the entire universe of sanctions imposed by the EU, UN, US and regional organizations in the period from 1990 to 2018, including those that were already in place by 1990 and those still ongoing. The dataset covers 399 cases, its data structure is dyadic, and the core unit of analysis is a sanctions case. If several senders impose restrictions on the same target, the dataset contains a separate case for each sender to provide sender-specific information on variables such as sanctions costs, goals or outcomes. It contains information on the design of sanctions – including expiry dates, review provisions and termination requirements – and captures the gradual process of adapting and ending sanctions. The main sources of information for coding are (inter)governmental documents that stipulate the implementation, extension, adaptation and removal of sanctions. The IST dataset is currently being updated to include the years 2019, 2020 and 2021. When using the data, please cite: Attia, Hana and Julia Grauvogel. Forthcoming. International Sanctions Termination, 1990–2018: Introducing the IST Dataset. Journal of Peace Research.

  2. d

    Replication Data for: \"The Unintended Consequences of UN sanctions: A...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 8, 2023
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    Mello, Patrick A. (2023). Replication Data for: \"The Unintended Consequences of UN sanctions: A Qualitative Comparative Analysis\", Contemporary Security Policy, 2022 [Dataset]. http://doi.org/10.7910/DVN/9BGOYQ
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    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Mello, Patrick A.
    Description

    Sanctions are widely used foreign policy tools in reaction to crises in world politics. Accordingly, literature on sanction effectiveness—their intended consequences—is abundant. Yet, fewer studies address the unintended consequences of restrictive measures. This is remarkable given that negative externalities are well documented. Our article explores this phenomenon by asking under which conditions sanctions yield negative externalities. We develop a theoretical conceptualization and explanatory framework for studying the unintended consequences of UN sanctions. Empirically, we draw on data from the rich, but scarcely used Targeted Sanctions Consortium and apply qualitative comparative analysis (QCA) to examine negative externalities of UN sanctions, complemented by illustrations from the cases Haiti and North Korea. The results document the existence of multiple pathways toward unintended consequences, highlighting the negative impact of comprehensive and long-lasting sanctions, as well as the ability of autocratic targets with economic means to persist unscathed from sanctions.

  3. Sanctions imposed on Russia 2022-2024, by target

    • statista.com
    Updated May 26, 2025
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    Statista (2025). Sanctions imposed on Russia 2022-2024, by target [Dataset]. https://www.statista.com/statistics/1293531/western-sanctions-imposed-on-russia-by-target/
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    Dataset updated
    May 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 22, 2022 - Jan 11, 2024
    Area covered
    Russia
    Description

    Between February 22, 2022, and January 11, 2024, territories and organizations worldwide imposed over 16,000 restrictions on individuals from Russia. Furthermore, roughly 9,300 list-based sanctions were placed on entities over that period. The sanctions were first placed due to the country's recognition of the separatist Donetsk and Luhansk People's Republics (DPR and LPR) and then due to its military attack on Ukraine. Restrictions targeting individuals typically include asset freezes and travel bans. Sanctions on Russia prior to the war in Ukraine Over the past decade, Western countries have placed restrictions on Russia for various reasons. In 2014, when Russia annexed Crimea and Sevastopol, the EU restricted entry to several individuals and froze assets of companies allegedly responsible for undermining and threatening Ukraine's territorial integrity. Furthermore, the EU and the U.S. sanctioned several persons and companies in relation to human rights violations and the use of chemical weapons, referring to the poisonings of Sergei and Yulia Skripal and Alexei Navalny. In addition, the United States imposed measures on Russia over its malicious cyber activities and evading United Nations (UN) sanctions restricting trade and financial transactions with North Korea, Syria, and Venezuela.

  4. g

    GIGA Sanctions Dataset

    • search.gesis.org
    Updated Jun 18, 2012
    + more versions
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    Portela, Clara; von Soest, Christian (2012). GIGA Sanctions Dataset [Dataset]. https://search.gesis.org/research_data/SDN-10.7802-1346
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    Dataset updated
    Jun 18, 2012
    Dataset provided by
    GESIS search
    German Institute for Global and Area Studies (GIGA)
    Authors
    Portela, Clara; von Soest, Christian
    License

    https://www.gesis.org/en/institute/data-usage-termshttps://www.gesis.org/en/institute/data-usage-terms

    Description

    The dataset is composed of the entire universe of sanctions regimes imposed by the UN, US and EU in the period from 1990 to 2010, including those sanctions regimes that were in place by 1990, targeting a country, its leadership and entities associated with it. Episodes which are still on-going are also recorded. Included are all sanctioned countries which have been coded – at least – at the start of sanction episodes as “autocratic regimes” by the Hadenius/Teorell/Wahman dataset on authoritarian regimes (2012).

  5. Singapore Targeted Financial Sanctions

    • opensanctions.org
    Updated Jul 18, 2025
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    Monetary Authority of Singapore (2025). Singapore Targeted Financial Sanctions [Dataset]. https://www.opensanctions.org/datasets/sg_terrorists/
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    csv, application/json+senzing, html, application/json+ftm, txt, jsonAvailable download formats
    Dataset updated
    Jul 18, 2025
    Dataset authored and provided by
    Monetary Authority of Singaporehttp://www.mas.gov.sg/
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Area covered
    Singapore
    Description

    Terrorists and terrorist entities designated by the Singapore government on top of the UN security council set of sanctions.

  6. d

    Data from: Sanctions, Aid, and Voting Patterns in the United Nations General...

    • search.dataone.org
    Updated Nov 8, 2023
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    Lektzian, David (2023). Sanctions, Aid, and Voting Patterns in the United Nations General Assembly [Dataset]. http://doi.org/10.7910/DVN/BOVDTA
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    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Lektzian, David
    Description

    This paper investigates the effects of U.S. economic sanctions on UN General Assembly voting patterns. Using panel data for 123 developing countries from 1990–2014, and employing an instrumental variables approach to account for potential endogeneity, we find that U.S.- imposed sanctions generally lead to a decline in voting coincidence between the U.S. and target countries when the sanctioned country receives low U.S. aid. However, in instances where the U.S. sanctions countries dependent on U.S. foreign aid, we find targets are increasingly more likely to vote with the U.S. This is because sanctions send a credible signal of the U.S.’s willingness to carry out punishment and cancel future aid to countries that publicly oppose it. Our research shows how sanctions alone tend to pull countries apart while, together with aid dependence, have the potential to bring countries in line with the U.S.’s position on issues, adding nuance to the sanctions literature.

  7. O

    South Africa Targeted Financial Sanctions

    • opensanctions.org
    Updated Jul 11, 2025
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    Financial Intelligence Centre (2025). South Africa Targeted Financial Sanctions [Dataset]. https://www.opensanctions.org/datasets/za_fic_sanctions/
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    application/json+ftm, csv, txt, json, xml, application/json+senzingAvailable download formats
    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Financial Intelligence Centre
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Area covered
    South Africa
    Description

    The South African FIC sanctions list, largely based on UN Security Council sanctions.

  8. m

    Data for: International Sanctions' Impact on Energy Efficiency in Target...

    • data.mendeley.com
    Updated Jul 31, 2019
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    Qiang Fu (2019). Data for: International Sanctions' Impact on Energy Efficiency in Target States [Dataset]. http://doi.org/10.17632/m8r8nx8fft.1
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    Dataset updated
    Jul 31, 2019
    Authors
    Qiang Fu
    License

    Attribution-NonCommercial 3.0 (CC BY-NC 3.0)https://creativecommons.org/licenses/by-nc/3.0/
    License information was derived automatically

    Area covered
    United States
    Description

    We use Efficiency to represent GDP divided by energy use, Unilateral to represent sanctions imposed by either the U.S. or the EU only, Plurilateral to represent the sanctions imposed by the U.S. and the EU jointly, Multilateral (or UN) to represent the international sanctions imposed by the United Nations, US, EU, and UN to stand for the sanction senders, Eco to represent that the sanctions affect the economy, Non-eco to represent that the sanctions do not affect the economy, Intensity to represent the formal intensity of sanctions, GDP to stand for per capita GDP of the target state, FDI to represent the net inflows of foreign direct investment, Investment to stand for the gross fixed capital formation as a percent of GDP, Industry to represent percentage of energy industry value added to GDP, Ideology to stand for the ideological orientation of the respective government, Urbanization to represent the proportion of urban population, and Openness to stand for exports plus imports as a percentage of GDP.

  9. O

    Qatar Unified Record of Persons and Entities on Sanction List

    • opensanctions.org
    Updated Jun 17, 2025
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    National Counter Terrorism Committee (2025). Qatar Unified Record of Persons and Entities on Sanction List [Dataset]. https://www.opensanctions.org/datasets/qa_nctc_sanctions/
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    json, application/json+senzing, application/json+ftm, txt, csvAvailable download formats
    Dataset updated
    Jun 17, 2025
    Dataset authored and provided by
    National Counter Terrorism Committee
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Area covered
    Qatar
    Description

    This dataset contains both UN-mandated and the national sanctions designations for Qatar (Targeted Financial Sanctions).

  10. Operation Crude Deception

    • catalog.data.gov
    Updated Jan 21, 2024
    + more versions
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    ICE (2024). Operation Crude Deception [Dataset]. https://catalog.data.gov/dataset/operation-crude-deception
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    Dataset updated
    Jan 21, 2024
    Dataset provided by
    United States Immigration and Customs Enforcementhttp://www.ice.gov/
    Description

    This dataset focused on focused on the illicit sale of Iranian-origin petroleum products in violation of U.S. and U.N. sanctions. Including FY 2022 enforcement activity, this initiative has acted on six tankers, disrupting over 4.98 million barrels of Iranian petroleum worth an estimated $162 million.

  11. O

    Nigeria Sanctions List

    • opensanctions.org
    Updated Mar 20, 2025
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    Nigeria Sanctions Committe (2025). Nigeria Sanctions List [Dataset]. https://www.opensanctions.org/datasets/ng_nigsac_sanctions/
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    html, csv, json, application/json+senzing, application/json+ftm, txtAvailable download formats
    Dataset updated
    Mar 20, 2025
    Dataset authored and provided by
    Nigeria Sanctions Committe
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Area covered
    Nigeria
    Description

    Nigeria enforces the UN Security Council list but also has an independent list of designations.

  12. Digest of United States Practice in International Law 2011

    • catalog.data.gov
    • cloud.csiss.gmu.edu
    • +1more
    Updated Mar 30, 2021
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    U.S. Department of State (2021). Digest of United States Practice in International Law 2011 [Dataset]. https://catalog.data.gov/dataset/digest-of-united-states-practice-in-international-law-2011
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    Dataset updated
    Mar 30, 2021
    Dataset provided by
    United States Department of Statehttp://state.gov/
    Area covered
    United States
    Description

    This volume provides a historical record of developments occurring during calendar year 2011, when the State Department's Office of the Legal Adviser marked its 80th birthday since its creation as a statutory entity.1 For the first time, the State Department is publishing the official version of the Digest exclusively on-line. By publishing the Digest on-line, we seek to make U.S. views on international law more quickly and readily accessible to our counterparts in other governments and international organizations, scholars, students, and other users, both within the United States and around the world. The Arab Awakening presented a variety of challenges for the practice of international law in 2011. In addressing events in Tunisia, Egypt, Libya, Bahrain, and elsewhere, the United States government carefully applied what Secretary of State Hillary Rodham Clinton has called "smart power," utilizing a wide array of foreign policy tools to fit the needs of the particular circumstance. In Libya, the U.S. took a multilateral approach, acting quickly at the UN Security Council to pass historic resolutions that established an arms embargo and sanctions regime and made the first ever unanimous referral to the International Criminal Court. Based on Security Council Resolution 1973's authorization for "all necessary measures" to enforce a no-fly zone, and consistent with the War Powers Resolution, the United States was part of a limited, NATO-led military mission in Libya. Various additional legal issues arose during the U.S. response to the situation in Libya, including those related to securing a protecting power, addressing the situation at the United Nations Human Rights Council, recognizing the new Libyan government, and arranging for funds to be made available to the new government using assets of the former regime that had been frozen pursuant to Security Council resolutions.

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    Learn how you can add new datasets to our index.

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Hana Attia; Julia Grauvogel (2022). International Sanctions Termination Dataset [Dataset]. http://doi.org/10.7910/DVN/SVR5W7

International Sanctions Termination Dataset

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37 scholarly articles cite this dataset (View in Google Scholar)
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Aug 29, 2022
Dataset provided by
Harvard Dataverse
Authors
Hana Attia; Julia Grauvogel
License

CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically

Description

The International Sanctions Termination (IST) dataset is composed of the entire universe of sanctions imposed by the EU, UN, US and regional organizations in the period from 1990 to 2018, including those that were already in place by 1990 and those still ongoing. The dataset covers 399 cases, its data structure is dyadic, and the core unit of analysis is a sanctions case. If several senders impose restrictions on the same target, the dataset contains a separate case for each sender to provide sender-specific information on variables such as sanctions costs, goals or outcomes. It contains information on the design of sanctions – including expiry dates, review provisions and termination requirements – and captures the gradual process of adapting and ending sanctions. The main sources of information for coding are (inter)governmental documents that stipulate the implementation, extension, adaptation and removal of sanctions. The IST dataset is currently being updated to include the years 2019, 2020 and 2021. When using the data, please cite: Attia, Hana and Julia Grauvogel. Forthcoming. International Sanctions Termination, 1990–2018: Introducing the IST Dataset. Journal of Peace Research.

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