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    <title>sanctions coalitions · Julian Hinz</title>
    <link>https://julianhinz.com/topics/sanctions-coalitions/</link>
    <description>sanctions coalitions by Julian Hinz.</description>
    <language>en</language>
    <managingEditor>mail@julianhinz.com (Julian Hinz)</managingEditor>
    <lastBuildDate>Fri, 23 Oct 2026 00:00:00 +0000</lastBuildDate>
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      <title>Trade Sanctions: Evidence From Russia</title>
      <link>https://julianhinz.com/research/trade_sanctions/</link>
      <pubDate>Fri, 23 Oct 2026 00:00:00 +0000</pubDate>
      <guid>https://julianhinz.com/research/trade_sanctions/</guid>
      <dc:creator>Julian Hinz</dc:creator>
      <dc:creator>Matthieu Crozet</dc:creator>
      <dc:creator>Patrik Šváb</dc:creator>
      <category>input-output linkages</category>
      <category>sanctions</category>
      <category>sanctions coalitions</category>
      <category>firm-level trade</category>
      <category>Russia</category>
      <description>&lt;figure&gt;&lt;img src=&#34;FigRUSanctionsProdnb.svg&#34;
         alt=&#34;Number of exported products by French firms following the imposition of sanctions against Russia in 2022.&#34;/&gt;&lt;figcaption&gt;
            &lt;p&gt;Number of exported products by French firms following the imposition of sanctions against Russia in 2022.&lt;/p&gt;
        &lt;/figcaption&gt;
&lt;/figure&gt;

&lt;p&gt;We review the economics of trade sanctions and provide new macro and micro evidence with the Russia 2014 and 2022 episodes as central case studies. On the macro side, we calibrate a multi-country, multi-sector general-equilibrium trade model with input–output linkages to quantify welfare effects under alternative coalition and intensity scenarios. Relative to 2014, the 2022 measures imposed substantially larger costs on Russia (about &amp;ndash;2.6% of real income) while the average cost for EU/UK senders remained modest (around &amp;ndash;0.1%), with larger losses in highly exposed small economies. Coalitions amplify pressure on the target at limited additional cost for most senders; hypothetical extensions bound sanctions potential (e.g., global participation or embargoes).
On the micro side, using French customs data (monthly firm–product–destination flows, 2021–2023) and a triple-difference design, we show that exports to Russia fell by roughly three quarters after February 2022. The adjustment is dominated by the extensive margin, with smaller but significant intensive-margin declines among continuing firms. Targeted products contracted far more than non-targeted ones (dual-use goods most severely), and we document diversion consistent with rerouting to nearby non-sanctioning countries.
We further discuss financial channels that propagate losses beyond listed goods, limits of ``smart&#39;&#39; sanctions when governments shield strategic firms, and political responses—including rally-around-the-flag effects.&lt;/p&gt;
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    <item>
      <title>Brothers in arms: The value of coalitions in sanctions regimes</title>
      <link>https://julianhinz.com/research/sanctions_coalitions/</link>
      <pubDate>Mon, 15 Apr 2024 00:00:00 +0000</pubDate>
      <guid>https://julianhinz.com/research/sanctions_coalitions/</guid>
      <dc:creator>Sonali Chowdhry</dc:creator>
      <dc:creator>Julian Hinz</dc:creator>
      <dc:creator>Katrin Kamin</dc:creator>
      <dc:creator>Joschka Wanner</dc:creator>
      <category>quantitative trade models</category>
      <category>input-output linkages</category>
      <category>econometrics</category>
      <category>sanctions</category>
      <category>sanctions coalitions</category>
      <category>Russia</category>
      <description>&lt;figure&gt;&lt;img src=&#34;cost_contribution_russia.png&#34;
         alt=&#34;Incurred and imposed welfare costs of the 2014 Russia sanctions.&#34;/&gt;&lt;figcaption&gt;
            &lt;p&gt;Incurred and imposed welfare costs of the 2014 Russia sanctions.&lt;/p&gt;
        &lt;/figcaption&gt;
&lt;/figure&gt;

&lt;p&gt;This paper examines the impact of coalitions on the economic costs of the 2012 Iran and 2014 Russia sanctions. By estimating and simulating a quantitative general equilibrium trade model under different coalition setups, we (i) dissect welfare losses for sanctions senders and target; (ii) compare prospective coalition partners; (iii) investigate “optimal” coalitions that maximise payoff from sanctions; (iv) provide bounds for sanctions potential, i.e. the maximum welfare change attainable when sanctions are scaled vertically up to an embargo, and horizontally up to a global regime. Relative to unilateral action, we find that coalitions magnify welfare losses imposed while their impact on domestic welfare loss incurred depends on the design and sectoral dimension of sanctions. Hypothetical cooperation of large developing economies such as China additionally raises the deterrent force of coalitions. Additionally, we quantify transfers that equalise welfare losses across coalition members to further demonstrate asymmetries in the relative economic burden of sanctions. In all scenarios, we implement a novel Bayesian bootstrap procedure that generates confidence bands for simulation outcomes.&lt;/p&gt;
</description>
    </item>
    <item>
      <title>Coalitions for Sanctions Heighten Costs for Russia but Burden of Implementation Should Be Shared among Member Countries</title>
      <link>https://julianhinz.com/research/diw_sanctions_coalitions/</link>
      <pubDate>Thu, 01 Feb 2024 00:00:00 +0000</pubDate>
      <guid>https://julianhinz.com/research/diw_sanctions_coalitions/</guid>
      <dc:creator>Sonali Chowdhry</dc:creator>
      <dc:creator>Julian Hinz</dc:creator>
      <dc:creator>Joschka Wanner</dc:creator>
      <dc:creator>Katrin Kamin</dc:creator>
      <category>quantitative trade models</category>
      <category>KITE</category>
      <category>sanctions</category>
      <category>sanctions coalitions</category>
      <category>Russia</category>
      <description>&lt;p&gt;Countries increasingly form alliances to collectively impose sanctions. However, the resulting impact of such coordination remains unclear. Analyzing the 2014 wave of sanctions against Russia over 400,000 simulations with a quantitative trade model, this report demonstrates that multilateral cooperation through coalitions simultaneously reduced domestic welfare losses incurred from sanctions and intensified welfare losses imposed on Russia. Results also reveal significant disparities within the coalition, with Russia sanctions placing relatively high economic costs on Baltic nations that can be mitigated through a burden-sharing program. Hypothetical cooperation by emerging economies like China is also shown to substantially raise the force of sanctions against Russia.&lt;/p&gt;
&lt;p&gt;The research behind this report is &lt;a href=&#34;/research/sanctions_coalitions/&#34;&gt;Brothers in Arms: The Value of Coalitions in Sanctions Regimes&lt;/a&gt;.&lt;/p&gt;
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    <item>
      <title>Sanctions coalitions: Stronger together</title>
      <link>https://julianhinz.com/research/voxeu_stronger_together/</link>
      <pubDate>Sun, 30 Oct 2022 00:00:00 +0000</pubDate>
      <guid>https://julianhinz.com/research/voxeu_stronger_together/</guid>
      <dc:creator>Sonali Chowdhry</dc:creator>
      <dc:creator>Julian Hinz</dc:creator>
      <dc:creator>Katrin Kamin</dc:creator>
      <dc:creator>Joschka Wanner</dc:creator>
      <category>sanctions</category>
      <category>sanctions coalitions</category>
      <description>/</description>
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