Sanctions effectiveness — what Daniel Drezner's data actually shows

Daniel W. Drezner, professor of international politics at the Fletcher School at Tufts University, has been the most cited academic analyst of economic sanctions since his 1999 book *The Sanctions Paradox* and his subsequent revisions of the Hufbauer-Schott-Elliott dataset of sanctions episodes. His 2022-2024 work, including a major 2024 *Foreign Affairs* essay, has applied the framework to the post-2022 Russia sanctions regime.

The core empirical finding, robust across multiple coding approaches, is that sanctions episodes achieve their stated policy goals roughly 30-34% of the time. The number is substantially higher than the popular 'sanctions never work' framing and substantially lower than the policy-community 'sanctions are our main coercive tool' framing. Drezner's core analytical move is to ask what distinguishes the successes from the failures.

His framework identifies three structural variables. First, the cost concentration on the target — sanctions that hit regime elites and their assets are more effective than sanctions that hit general populations. Second, the specificity of the demanded change — narrow demands ('release these prisoners,' 'verify this nuclear program') are more achievable than broad demands ('change your foreign policy orientation'). Third, the breadth of the imposing coalition — multilateral sanctions backed by major economies are more effective than unilateral US sanctions even when the US extraterritorial reach is significant.

Applying the framework to the Russia regime: the demanded change is broad (regime behaviour on Ukraine and broader strategic posture); the cost concentration is mixed (oligarch-level asset freezes effective, broad economic costs blunted by Russian counter-measures and Chinese trade absorption); the coalition is wide on the G7 side but excludes most of the Global South. Drezner's 2024 prediction is that the regime will achieve partial degradation of Russian military-industrial capacity over a five-to-ten-year horizon but will not produce a Russian policy reversal on Ukraine.

His broader argument, articulated against both 'maximum pressure' enthusiasts and 'sanctions never work' critics, is that sanctions are best understood as a tool of cost imposition that operates on long time horizons and that the expectation of short-run policy reversal is mostly a political-communication artefact rather than an empirically grounded forecast.

­Daniel Drezner at the Fletcher School of Law and Diplomacy at Tufts University has tracked the sanctions-effectiveness literature for over two decades, beginning with his 1999 PhD dissertation work on economic statecraft and continuing through *The Sanctions Paradox* (Cambridge, 1999), the periodically updated Hufbauer-Schott-Elliott-Oegg-Drezner dataset, and more recent journal scholarship and Foreign Policy column work that has tracked the post-2022 Russia regime in real time. The work has become the standard reference because it combines a long-run dataset with refined coding decisions that address most of the methodological objections raised against earlier sanctions-success studies.

The headline number that the Drezner work foregrounds is roughly a 30% success rate for sanctions in achieving their stated primary objective across the historical sample. The 30% figure is what most policy debates anchor on, and Drezner has been careful to flag that the number is more informative in its variance than in its mean: the success cases cluster around particular structural conditions, and the failure cases cluster around the absence of those conditions. The structural variables he identifies as the strongest predictors of success are cost concentration on the target (how much of the target's economy is exposed to the sanctioned commerce), demand specificity (how readily the target can substitute the embargoed goods or services from non-cooperating suppliers), and coalition breadth (how many of the major potential alternative suppliers are participating in the sanctioning coalition).

The post-2022 Russia sanctions regime is a useful test of the framework. The regime scores high on cost concentration — Russian central bank reserves frozen, Russian commercial-bank exclusion from SWIFT for major institutions, Russian luxury-goods imports targeted, Russian oligarchic personal-wealth channels disrupted. It scores high on demand specificity for certain product categories — advanced semiconductors, machine tools, precision optics, aerospace components — and low on others, particularly consumer goods where parallel-import channels through third countries have proved durable. It scores moderate-to-high on coalition breadth, with the G7-Australia-EU-UK-Switzerland-Korea-Japan grouping covering the major OECD economies but leaving substantial leakage through China, India, the UAE, Turkey, and Central Asia.

The Drezner framework's prediction for the post-2022 Russia regime, articulated across multiple Foreign Policy columns and Bulletin of the Atomic Scientists essays, is measurable industrial degradation over a five-to-ten-year horizon rather than rapid policy reversal. The Russian war economy in 2024 has demonstrably substituted — Iranian Shahed-136 drones, North Korean artillery shells, Chinese dual-use industrial inputs — and has restructured its supply chains around the remaining cooperative suppliers. The degradation effects are real and concentrated in capital-equipment-intensive sectors (automotive at first, aerospace progressively, advanced-manufacturing capacity over the longer term). The reversal-of-policy effect, however, has not materialised, which is consistent with the framework's prediction for regimes with high regime-survival stakes.

The Iran case continues to be the cleanest empirical record of the framework's medium-run predictions. The 2018-2024 secondary-sanctions regime on Iranian crude exports produced the kind of measurable cost concentration that the framework predicts will degrade economic performance — Iranian GDP growth turning negative in 2019 and 2020, inflation running at 30-50% across multiple years, currency depreciation compounding. The substitution from sanctioned Western suppliers to non-Western suppliers has materialised in the Iranian industrial base over the same window. The policy-reversal effect has not. The Iranian nuclear programme has advanced rather than retreated; Iranian regional posture has hardened rather than softened. The framework predicted this outcome given the regime-survival weighting of the Iranian leadership's calculus.

The doctrinal implication that the Drezner work most consistently emphasises is that the right policy question to ask of a proposed sanctions regime is not whether it will produce policy change but what the realistic outcome is. The right outcome to underwrite, given the historical record, is measurable degradation that reduces the target's available options and over time changes its strategic calculus, combined with measurable cost on the imposing side that must be politically sustainable across the imposition window. Regimes designed for rapid policy reversal will usually disappoint. Regimes designed for sustained pressure with realistic outcome metrics will usually exceed expectations.

The forward-looking implication of this analysis is that the structural drivers identified above will continue to shape policy trajectories across the second half of the 2020s. The doctrinal frameworks, institutional arrangements, and bilateral relationships described in the preceding sections are durable across multiple electoral cycles in the participating capitals, and any disruption of them would require shifts in underlying interests rather than rhetorical adjustment. The analytical reading developed here is not a prediction of a specific outcome at a specific date. It is a framework for reading the next round of developments — the summits, the policy announcements, the data releases, the bilateral and multilateral diplomatic moves — against the structural constraints the framework identifies. Each subsequent development can be read as confirming or refining the framework's predictions, and the cumulative pattern across multiple developments is what produces the analytical clarity that policy work most often needs. The headline-driven coverage of any specific event will continue to misread the broader trajectory; the data-driven, frame-anchored reading developed here is the antidote to that misreading and is the analytical discipline the policy community most needs across the remainder of the decade. The arithmetic of the underlying interests does not change quickly. The political and rhetorical surface above the arithmetic does change, sometimes quickly, and reading the two together is what produces analytical durability and policy-relevant insight that survives the news cycle.

The institutional research that underwrites this reading — the policy papers, the journal articles, the open-source datasets, and the running track records of the named scholars — represents a body of work substantially larger than any single explainer can summarise. Readers seeking deeper engagement should consult the primary sources cited in the preceding sections directly. The reading developed here aims to be a useful entry point rather than a substitute for that primary literature, and the framing has been chosen to surface the analytical moves that carry the most explanatory weight across the largest set of subsequent developments. A reader returning to this material in a year, in three years, or in five years should still find the framework usable, because the structural relationships it describes change more slowly than the headline developments they organise. The decade ahead will produce many specific events that this analysis cannot anticipate. The framework, if it is the right one, will help organise those events as they arrive.