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How to simulate international economic sanctions: A multipurpose index modelling illustrated with EU sanctions against Russia

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  • Bali, Morad
  • Rapelanoro, Nady

Abstract

One of the main challenges economists must face while studying economic sanctions is to simulate them in their models faithfully. It seems extremely hard to achieve without a dedicated variable that precisely imitates coercive economic measures. Thence, this short paper aims to offer a framework for the construction of economic sanction indexes. Researchers can use our multipurpose index modelling to simulate economic punishment in their econometric models. If our work is framed within the Ukrainian crisis case and European economic sanctions against Russia, the method we provide can be used in any other case study. It is a great alternative to the standard use of dummy variables that witness sanctions' implementation and withdrawal. Additionally, our proposal allows calibrating the weight attributed to each sanction depending on its type, the sanction sender's ability to apply economic pressure, and the effect of time on sanctions' effectiveness. The first part of this paper details the methodology and the mathematical formalisation of our framework. It is used to build a sanction index that simulates sanctions against Russia during the Ukrainian crisis. The second part is an empirical study that compares our index to another one from the literature. Results reveal that our new sanction index witnesses the behaviour of sanctions more precisely, which leads to a stronger explanatory power. Moreover, it enhances the statistical significance of impulse-response functions generated by our SVAR models. Consequently, the framework for sanction index construction that is proposed in this paper successfully produced a reliable index that simulates the European Union's sanction against Russia in the Ukrainian crisis case.

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  • Bali, Morad & Rapelanoro, Nady, 2021. "How to simulate international economic sanctions: A multipurpose index modelling illustrated with EU sanctions against Russia," International Economics, Elsevier, vol. 168(C), pages 25-39.
    • Handle: RePEc:eee:inteco:v:168:y:2021:i:c:p:25-39
    DOI: 10.1016/j.inteco.2021.06.004
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    Cited by:

    1. Batten, Jonathan A. & Boubaker, Sabri & Kinateder, Harald & Choudhury, Tonmoy & Wagner, Niklas F., 2023. "Volatility impacts on global banks: Insights from the GFC, COVID-19, and the Russia-Ukraine war," Journal of Economic Behavior & Organization, Elsevier, vol. 215(C), pages 325-350.
    2. Morad Bali & Thanh T. Nguyen & Lincoln F. Pratson, 2024. "Impacts of EU Sanctions Levied in 2014 on Individual European Countries' Exports to Russia: Winners and Losers," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 50(2), pages 154-194, April.
    3. Chishti, Muhammad Zubair & Khalid, Ali Awais & Sana, Moniba, 2023. "Conflict vs sustainability of global energy, agricultural and metal markets: A lesson from Ukraine-Russia war," Resources Policy, Elsevier, vol. 84(C).

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    More about this item

    Keywords

    Ukrainian crisis; Economic sanctions; Sanction index; Structural vector autoregressive models; Russia; European Union;
    All these keywords.

    JEL classification:

    • F - International Economics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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