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Cross-Efficiency of International Sanctions: Application of Data Envelopment Analysis and Network Methodology

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Analysis of Images, Social Networks and Texts (AIST 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1086))

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Abstract

In this paper we provide the methodology for evaluating effectiveness of international sanctions using Data Envelopment Analysis (DEA), which we use for generating the network matrix for further analysis. DEA is a non-parametric technique used to compare performance of similar units, such as departments or organizations. DEA has wide applications in all industries, and has been successfully used to compare performance of hospitals, banks, universities, etc. The most important advantage of this technique is that it can handle multiple input and output variables, even those not generally comparable to each other. We use the “Threat and Imposition of Sanctions (TIES)” Data 4.0 for analysis. This database contains the largest number of cases of international sanctions (1412 from the years 1945–2005) imposed by some countries on others, takes into account simultaneous sanction imposition, and also estimates the cost of all sanctions - both for those who receive and those who impose them. As input variables for DEA model we use the impact of sender commitment, anticipated target and sender economic costs, and actual target and sender economic costs. As the output variable, we use the outcome of sanctions for senders. We describe how to use DEA cross-efficiency outputs to build the network of sanction episodes. Our proposed combination of DEA and network methodology allows us to cluster sanction episodes depending on their outcomes, and provides explanations of higher efficiency of one group of sanction episodes over the others.

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Acknowledgment

The article was prepared within the framework of the Basic Research Program at the National Research University Higher School of Economics (HSE) and supported within the framework of a subsidy by the Russian Academic Excellence Project ‘5–100.’

Author information

Authors and Affiliations

  1. International Laboratory for Applied Network Research, National Research University Higher School of Economics, Moscow, Russia

    Dmitry Zaytsev, Valentina Kuskova, Polina Lushnikova & Gregory Khvatsky

Authors
  1. Dmitry Zaytsev
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  2. Valentina Kuskova
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  3. Polina Lushnikova
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  4. Gregory Khvatsky
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Corresponding author

Correspondence to Dmitry Zaytsev .

Editor information

Editors and Affiliations

  1. RWTH Aachen University, Aachen, Germany

    Wil M. P. van der Aalst

  2. University of Ljubljana, Ljubljana, Slovenia

    Vladimir Batagelj

  3. National Research University Higher School of Economics, Moscow, Russia

    Dmitry I. Ignatov

  4. Institute of Mathematics and Mechanics Yekaterinburg, Yekaterinburg, Russia

    Michael Khachay

  5. National Research University Higher School of Economics, Moscow, Russia

    Valentina Kuskova

  6. University of Oslo, Oslo, Norway

    Andrey Kutuzov

  7. National Research University Higher School of Economics, Moscow, Russia

    Sergei O. Kuznetsov

  8. National Research University Higher School of Economics, Moscow, Russia

    Irina A. Lomazova

  9. Moscow State University, Moscow, Russia

    Natalia Loukachevitch

  10. Loria, Vandoeuvre lès Nancy, France

    Amedeo Napoli

  11. University of Florida, Gainesville, USA

    Panos M. Pardalos

  12. Ca' Foscari University of Venice, Venezia Mestre, Italy

    Marcello Pelillo

  13. National Research University Higher School of Economics, Nizhny Novgorod, Russia

    Andrey V. Savchenko

  14. Kazan Federal University, Kazan, Russia

    Elena Tutubalina

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Zaytsev, D., Kuskova, V., Lushnikova, P., Khvatsky, G. (2020). Cross-Efficiency of International Sanctions: Application of Data Envelopment Analysis and Network Methodology. In: van der Aalst, W., et al. Analysis of Images, Social Networks and Texts. AIST 2019. Communications in Computer and Information Science, vol 1086. Springer, Cham. https://doi.org/10.1007/978-3-030-39575-9_8

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  • DOI: https://doi.org/10.1007/978-3-030-39575-9_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-39574-2

  • Online ISBN: 978-3-030-39575-9

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