Tag: Russia
TRACER Index Offers New Benchmark for Global Sanctions Compliance
A new analytical tool is providing policymakers with a more comprehensive way to evaluate sanctions enforcement. The TRACER Index, published by the Sanctions on Russia initiative, measures how effectively countries implement export restrictions while accounting for the structural factors that influence sanctions evasion risks.
Unlike traditional rankings that focus solely on trade outcomes, the TRACER Index separates a country’s institutional capacity from the external conditions that may affect sanctions compliance. As a result, it offers a more nuanced assessment of where enforcement systems perform well and where vulnerabilities remain.
How the TRACER Index Measures Sanctions Compliance
The TRACER Index evaluates 38 countries using 85 indicators organized into four complementary pillars. Together, these indicators measure both enforcement capacity and structural exposure to sanctions evasion.
The four pillars include:
- Legal Frameworks: assessing the strength and enforceability of sanctions legislation, judicial effectiveness, and legal penalties.
- Government Enforcement: measuring customs controls, financial oversight, anti-corruption systems, and regulatory enforcement.
- Corporate Compliance: evaluating the tools available to businesses and financial institutions for sanctions screening, due diligence, and reporting.
- Structural Constraints: capturing geographic, logistical, and economic factors that may increase the risk of sanctions circumvention regardless of institutional quality.
According to the project, separating these dimensions allows policymakers to distinguish between countries with weak enforcement institutions and those facing inherently higher risks because of their geographic location or trade structure.
A Diagnostic Tool for Better Policy
The developers describe TRACER as more than a country ranking. Instead, it serves as a diagnostic framework that helps governments identify specific strengths and weaknesses within their sanctions enforcement systems.
The index recognizes that observed trade outcomes alone cannot explain sanctions’ effectiveness. Trade diversion may occur because of institutional shortcomings, but it can also result from structural factors outside the immediate control of national authorities. By accounting for both, TRACER aims to provide a fairer comparison across countries.
Moreover, the framework helps policymakers prioritize reforms by identifying areas where improvements in legislation, enforcement capacity, corporate compliance, or institutional coordination could strengthen sanctions implementation.
Why It Matters
Since Russia’s full-scale invasion of Ukraine, sanctions enforcement has become increasingly important for limiting access to restricted goods and technologies. However, implementation varies across jurisdictions, and countries face different levels of exposure to sanctions evasion.
The TRACER Index provides an evidence-based approach for understanding these differences. By combining institutional indicators with structural risk factors, it offers governments, researchers, and compliance professionals a practical tool for evaluating sanctions effectiveness and identifying where additional policy attention may be needed.
As sanctions regimes continue to evolve, analytical frameworks such as TRACER may play an increasingly important role in supporting international coordination and improving enforcement outcomes.
Further Reading
- Evidence Base on Sanctions Against Russia
- FREE Network Policy Briefs on Sanctions
- International Trade and Sanctions Research by the KSE Institute
- Ukraine Support Tracker by the Kiel Institute
Towards a Russian Internet?
The internet enables information and opinions to flow rapidly and at low cost, including across national borders. It allows individuals to coordinate collective action on an unprecedented scale. Many authoritarian governments, therefore, seek to control the online information environment. This policy brief examines the evolution of internet control in Russia and documents how censorship and network disruptions have intensified since the full-scale invasion of Ukraine.
Drawing on three complementary datasets—Access Now’s Shutdown Tracker Optimization Project (STOP), the Internet Outage Detection and Analysis (IODA) initiative, and the Open Observatory of Network Interference (OONI)—we document a sharp increase in internet disruptions, platform blocking, and website censorship in Russia since 2022. We argue that this expansion of censorship was enabled by a longer-term shift from a relatively decentralized system of internet regulation towards a centralised infrastructure capable of monitoring, filtering, and controlling internet traffic at scale.
The Online War
The Russian government has been fighting its war against Ukraine on multiple fronts: aside from the battlefield in Ukraine, there is also an online front at home. Since the start of the full-scale invasion in February 2022, the Kremlin has sought to control how the war is presented to the Russian public. Within weeks of the invasion, Russia blocked Facebook, Instagram, and Twitter, and restricted access to numerous foreign and independent media outlets. In the years that followed, restrictions expanded to include VPN services and specific features of messaging platforms such as WhatsApp and Telegram.
These measures are not isolated events. Rather, they represent the latest stage in a broader effort to control the Russian internet. Over the past decade, Russia has gradually built the legal and technical infrastructure needed to monitor, filter, and disrupt online communications. The war in Ukraine has revealed the extent of these capabilities and accelerated their deployment.
This brief examines how internet control in Russia has evolved in recent years. We discuss the challenges of measuring internet censorship and analyse evidence from three complementary datasets. Together, these measures show a sharp increase in internet disruptions, platform restrictions, and censorship since the full-scale invasion of Ukraine.
Why Control the Internet?
The internet has transformed the way information is produced, shared, and consumed. It allows information and opinions to spread rapidly at low cost, including across national borders, and enables individuals to coordinate collective action on an unprecedented scale. For an authoritarian government, the internet allows the spread of information that contradicts official narratives and can facilitate political opposition. The role of social media in mobilising protests during the Arab Spring highlighted the power of the internet.
In response, many authoritarian governments have sought to exert greater control over the internet. China is the most advanced example of state control over the online information environment. Through its “Great Firewall”, the Chinese government controls access to foreign information and platforms, while influencing and monitoring domestic online activity through censorship, regulation, and the cooperation of domestic technology companies.
Russia has historically taken a different approach. Until recently, Russians retained access to many Western platforms, and internet censorship was implemented in a relatively decentralized manner by internet service providers. Rather than constructing a separate internet from the outset, Russia sought to control information flows while remaining integrated with the global internet.
Authoritarian Trade-offs
Why might the Russian government have followed this light-touch approach, and why change course now? The literature in economics and political science describes two trade-offs an authoritarian government faces when deciding how much control to exert over the internet.
The first is economic. Describing the ‘dictator’s dilemma,’ Kedzie (1997) writes, “it may now be virtually impossible for any country to maintain an open economy for expansion while remaining closed to democratic ideas“. Estimates of the economic cost of internet shutdowns support this argument. One estimate suggests that government-imposed outages cost the global economy $19.7 billion in the year 2025 (Migliano 2026).
The second is informational. Egorov et al. (2009) argue that an authoritarian government that constrains free media and communication flows too aggressively cuts itself off from information required to govern effectively. Local bureaucrats have no incentive to perform in the absence of reliable independent monitoring. King et al. (2013) provide empirical evidence for this in the context of Chinese social media censorship. They find that censors allow (potentially informative) criticism of the government but specifically target posts that could give rise to collective action.
Controlling the narrative around a prolonged, costly war necessitates a greater level of intervention. The censorship strategies discussed below can be viewed through the lens of a government seeking new ways to navigate both trade-offs.
Tracking Internet Shutdowns
Identifying government-imposed internet shutdowns is challenging. Affected users will typically have no way of verifying the extent or true cause of an outage, and their ability to report it in real-time may itself be curtailed. As a result, organizations that monitor internet shutdowns use very different methodologies. In our brief, we will describe three of the most prominent publicly available datasets that attempt to track disruptions to internet services worldwide.
Access Now, a member of the #KeepItOn coalition, provides a publicly available dataset of internet shutdowns through its Shutdown Tracker Optimization Project (STOP). The distinguishing feature of STOP is that it establishes intent. It combines technical data on internet connectivity with either official government statements or information provided by informed insiders. STOP records various types of technical disruption: from full blackouts to throttling and partial service restrictions. However, a measured disruption of internet services is only recorded as a shutdown event if it can be traced back to deliberate government intervention with a high degree of confidence. The advantage of this approach is that one can be confident that each instance in the data reflects a deliberate government-induced shutdown. The limitation is that the dataset likely undercounts shutdowns in data-scarce or highly repressive environments where establishing intent is not always possible.
Figure 1 plots internet shutdowns in Russia, and for comparison, the FREE network member countries from 2016 to 2025. The chart is dominated by the sharp upward trend in Russia, starting in 2021, and accelerating after the full-scale invasion of Ukraine. There is also an increase in Ukraine after the invasion; which includes both Russian actions that disrupted connectivity and Ukrainian measures to block specific Russian platforms. Similarly, Latvia imposed nationwide blocks of two Russian platforms after the start of the invasion. The chart also shows the internet blackouts in Belarus amid widespread protests following the 2020 election.
Figure 1. Internet shutdown events in FREE Network countries (2016-2025)

Source: Access Now, KeepItOn STOP (2016-2025) and authors’ calculations.
Note: This chart shows the number of distinct intentional internet shutdown events active during each quarter in countries of the SIDA Free Network. (Sweden, Georgia, Moldova, and Poland are excluded from the graph because no shutdown events were recorded for them over this period.) An internet shutdown is defined as an intentional disruption of internet or electronic communications, rendering them inaccessible or effectively unusable, for a specific population or within a location, often to exert control over the flow of information (Access Now, KIO). A shutdown event can result from third-party interventions rather than be intended by the country’s government.
Figure 2 uses the same dataset to illustrate which social media and online messaging platforms were most affected by the increase in government control of the internet in Russia. Relative to China, Russia used to exert only ‘light-touch’ control over the internet, as seen in the first panel of the figure. From 2016 to 2021, the social media and online messaging platforms in the chart were largely unaffected by shutdown events. The second panel shows that since early 2022, all of these platforms have experienced shutdown events, and in the case of Facebook, Twitter/X, and Instagram, there have been active blocks throughout the entire period.
Figure 2. Platform service disruptions in Russia (2016 – 2025)


Source: Access Now, KeepItOn STOP Dataset (2016-2025) and authors’ calculations. Note: This graph details the platforms affected by internet shutdowns in Russia (See Figure 1). Each bar shows the percentage of days in the period when at least one shutdown event affected the platform in Russia.
As discussed, the STOP dataset likely undercounts internet shutdowns. We therefore evaluate whether alternative measures show the same upward trend for Russia.
Our second dataset comes from the Internet Outage Detection and Analysis (IODA) initiative at Georgia Tech, which monitors global internet connectivity using three complementary technical signals to detect when networks go offline. IODA identifies outages at the country, regional, or network level and records their duration and severity. Importantly, unlike STOP, IODA detects outages but not their cause. An outage may reflect deliberate government action or infrastructure failure.
Panel (a) of Figure 3 compares the IODA measure of outages with the STOP measure of internet shutdowns for Russia. The IODA measure (right axis) is roughly 100 times as high as the STOP measure in any given period, as IODA records all detected disruptions regardless of intentionality. That said, the IODA data corroborate the finding that internet disruptions have become ever more frequent in Russia, with significant increases in 2024 and 2025.
Our third dataset comes from the Open Observatory of Network Interference (OONI), which focuses on censorship rather than outages. OONI relies on volunteers running tests through an open-source app, generating measurements of whether specific websites, messaging platforms, and circumvention tools are accessible or blocked.
Figure 3. Trend in internet disruption and online censorship in Russia (2022-2025)
a. Count of internet disruptions

b. Rate of websites and apps censorship

Source: Access Now KeepItOn STOP (KIO), Internet Outage Detection and Analysis (IODA), Open Observatory of Network Interference (OONI), and authors’ calculations.
Note: Panel (a) shows STOP internet shutdown events in the blue line, which records intentional disruptions of internet or electronic communication (KIO, see Figure 1), and IODA internet outages in the orange line, which are abnormal simultaneous drops in 2 or more signals measuring internet connectivity, intentional or accidental. IODA outages are filtered to only include events lasting more than 2 hours to match the KIO restriction. The red line shows a twelve-month moving average of IODA outages. Panel (b) shows online censorship rates for websites and messaging apps, measured by the monthly rate of anomalies recorded by OONI. An anomaly is detected when a measurement presents signs of potential network interference (such as the blocking of a website or app). Messaging apps data derive from OONI messaging platform availability tests (WhatsApp, Telegram, Signal, Facebook Messenger), and website data from OONI Web Connectivity tests on individual websites’ availability. Days and platforms or websites with fewer than 5 measurements are excluded for reliability.
It does so by comparing results over the user’s network against a control server, with divergences flagged as potential interference. The main limitation is uneven coverage over time, a consequence of the volunteer-based approach, though the total number of daily measurements is always known.
Panel (b) of Figure 3 plots anomaly rates for websites and messaging apps as experienced by Russian users since the start of 2022. Both lines show a clear upward trend, indicating that Russian users are increasingly encountering websites and apps that are blocked in Russia but available elsewhere.
The Centralisation of Russian Internet Control
While Russia has always exerted some degree of control over the internet, it has historically relied on what Ramesh et al. (2020) call a decentralised model. Since 2012, Russia’s internet regulator, Roskomnadzor, has maintained a national blocklist of websites and required Internet Service Providers (ISPs) to restrict their users’ access to these websites. As ISPs were granted full discretion over how to comply, the blocking mechanisms and their effectiveness reportedly varied significantly across websites and providers. The attempted blocking of Telegram in 2018 exposed the limitations of Russia’s decentralized approach to internet censorship. To enforce the ban, Roskomnadzor blocked millions of IP addresses associated with Amazon and Google cloud services, leading to widespread disruption of unrelated online services, while failing to prevent Russian users from accessing Telegram.
Since then, Russia has moved towards a more centralised model of internet governance, aimed at increasing state control over its domestic internet and reducing dependence on the global network. In 2019, the “Sovereign Internet Law” (or “Law on Sustainable Runet”) came into force, which provided the Russian state the legal and technical tools to centrally monitor, filter and reroute internet traffic. The law requires ISPs to install TSPU (Tekhnicheskie Sredstva Protivodeystviya Ugrozam, or “technical means of countering threats”) devices on their networks, or face fines. These devices allow the government to track and manage internet traffic across private networks in a centralised manner (Human Rights Watch 2025).
TSPUs first attracted attention in 2021 when access to Twitter was throttled, but their impact has since become more widespread (Xue et al., 2021). In February 2023, OONI and the Russian digital rights organisation Roskomsvoboda reported that numerous media outlets and websites with critical coverage of the Russian war in Ukraine had been blocked in 2022. In a striking contrast to previous decentralised censorship practices, these restrictions were implemented simultaneously across internet providers. Figure 4, originally published by OONI, illustrates the simultaneous blocking of the Human Rights Watch website after it was added to Roskomnadzor’s blocklist on April 17, 2022. The figure shows that users across multiple networks lost access at the same time. The OONI report also highlights that providers are now using the same technical methods to enforce central directives, illustrating the widespread effective use of TSPUs.
Figure 4: Network interference in Russia

Source: Open Observatory of Network Interference (OONI), Roskomsvoboda, How Internet censorship changed in Russia during the 1st year of military conflict in Ukraine.
Autonomous System Numbers (ASNs) which presented the largest volume of anomalies (more than 1,200 anomalies) in the testing of www.hrw.org in Russia between 1st January 2022 to 20th February 2023. An anomaly is detected when a measurement presents signs of potential network interference (such as the blocking of a website or app).
Recent restrictions on Telegram provide further evidence of their efficacy. In contrast to the failed block in 2018, most Russian users are now unable to access the app without VPNs or other workarounds.
The capabilities of TSPUs extend far beyond individual website blocking. Recent reports suggest that instead of just targeting specific parts of the internet, they are now used to impose temporary, near-total internet blackouts. These cut users off from much of the global internet, while preserving access to a whitelist of Russian government websites and fully cooperative platforms (Human Rights Watch, 2026). In doing so, TSPU moves Russia closer to the Chinese model of internet control, increasing the state’s ability to manage internet traffic centrally.
Conclusion
In recent years, Russia’s strategy towards internet censorship has changed profoundly. The decentralised, relatively light-touch approach, with unrestricted access to many Western platforms, has been abandoned. The government has acquired the legal and technical capability to exert tight, centralised control over service providers, and every indicator we have analysed in this brief makes clear that it is using these powers ever more aggressively.
The incremental nature of these changes and their technical sophistication mean that Russia’s internet control cannot be equated with the blunt tool of country- or region-wide shutdowns as used by authoritarian governments in other parts of the world. These types of internet shutdowns are highly visible to domestic and international users and spark outrage. Russia’s strategy is more insidious. Its citizens’ access to the global internet has been shutting down, year by year and month by month. Individual users’ experience of these changes is fragmented, making a collective response difficult. Russia is on its way to creating and controlling its very own version of the internet.
References
- Access Now. 2026. “#KeepItOn Shutdown Tracker Optimization Project (STOP) Dataset.” Accessed 15 Apr. 2026.
- Access Now. 2026. “Shutdown Tracker Optimization Project (STOP): Tracking Internet Shutdowns — Our STOP Methodology.“
- Bischof, Zachary S., Kennedy Pitcher, Esteban Carisimo, Amanda Meng, Rafael Bezerra Nunes, Ramakrishna Padmanabhan, Margaret E. Roberts, Alex C. Snoeren, and Alberto Dainotti. 2023. “Destination Unreachable: Characterizing Internet Outages and Shutdowns.” Proceedings of the ACM SIGCOMM 2023 Conference, 608–621.
- Egorov, Georgy, Sergei Guriev, and Konstantin Sonin 2009. “Why resource-poor dictators allow freer media: A theory and evidence from panel data.” American political science Review 103, no. 4: 645-668.
- Human Rights Watch. 2026. “Russia: Internet Shutdowns Escalate.” March 31.
- Internet Outage Detection and Analysis (IODA). 2026. “IODA website.“
- Kedzie, Christopher R. 1997 “Communication and Democracy: Coincident Revolutions and the Emergent Dictator’s Dilemma.” RAND Document No: RGSD-127.
- King, Gary, Jennifer Pan, and Margaret E. Roberts 2013. “How censorship in China allows government criticism but silences collective expression.” American political science Review 107, no. 2: 326-343.
- Kruope, Anastasiia. 2025. “Disrupted, Throttled, and Blocked.” Human Rights Watch, July 30.
- Migliano, Simon 2026. “Cost of Internet Shutdowns in 2025” TOP10VPN Annual Internet Shutdown Report.
- Open Observatory of Network Interference (OONI). 2026. “OONI Web Connectivity test.“
- Open Observatory of Network Interference (OONI). 2026. “OONI Website.“
- Ramesh, Reethika, Ram Sundara Raman, Apurva Virkud, Alexandra Dirksen, Armin Huremagic, David Fifield, Dirk Rodenburg, Rod Hynes, Doug Madory, and Roya Ensafi. 2023. “Network Responses to Russia’s Invasion of Ukraine in 2022: A Cautionary Tale for Internet Freedom.” 32nd USENIX Security Symposium (USENIX Security 23), August 2581–2598
- Roskomsvoboda and OONI. 2023. “How Internet Censorship Changed in Russia during the 1st Year of Military Conflict in Ukraine.” February 24.
- Xue, Diwen, Benjamin Mixon-Baca, ValdikSS, et al. 2022. “TSPU: Russia’s Decentralized Censorship System.” Proceedings of the 22nd ACM Internet Measurement Conference, October 25, 179–94.
- Xue, Diwen, Reethika Ramesh, Valdik S. S., et al. 2021. “Throttling Twitter: An Emerging Censorship Technique in Russia.” Proceedings of the 21st ACM Internet Measurement Conference, November 2, 435–43.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
The Hormuz Blockade: Winners, Losers, and Vulnerabilities
This policy paper presents calculations and modeling of how oil producers and consumers in selected countries may be affected by the de facto blockade of the Strait of Hormuz. We study two scenarios: one where strategic inventories cushion the effects, and one where inventories have run out. Russia profits substantially, equivalent to 6-11% of GDP, driven by higher global oil prices and a potential reduction in the sanctions-induced discount on Russian oil. Net oil importers lose – most substantially India, to some extent China, and to a lesser extent Europe. Within Europe, most countries lose, with the exception of Norway and possibly Estonia. Gulf countries generally lose since they cannot export their oil. Surprisingly, Saudi Arabia can make a net profit by earning high prices for oil redirected to its western ports.
We also analyze oil inventories to measure importers’ vulnerability. India is by far the most vulnerable among larger economies, due to limited storage, high net imports, and an oil-intensive economy. China is less vulnerable, and Europe is the least. Finally, we discuss how the crisis may trigger a macroeconomic recession, reshape long-run oil demand, destabilize OPEC, and create domestic tensions between those who gain and those who lose from an oil-price shock.
Introduction
Since the end of February, the Strait of Hormuz has been almost fully closed for oil transports. Under normal circumstances, around 20% of the global supply passes through the Strait. In this policy paper, we present rough calculations and modeling of how producers and consumers of oil in selected countries may be affected by the de facto blockade of the Strait of Hormuz. We then briefly discuss some potential implications and uncertainties on the longer-run effects of the current crisis. A caveat throughout the analysis is that both the conflict and the oil market are evolving rapidly. The assessments and choices are based on our best judgment at the time of writing.
Disruption Scenarios – Short and Medium Term
The model we use to assess the changes in consumer surplus and producer profits is a simple supply and demand model of oil. It is akin to Gars et al. (2025), which studies how different countries would be impacted by a Russian oil-export restriction, i.e, a supply shock. In this policy paper, the restriction of supply comes instead from a reduction of the exports of countries inside the Strait of Hormuz. In the appendix, we describe the data and methods we use and briefly discuss their limitations.
Table 1 shows the key parameters for the situation before the disruption and for our two disruption scenarios. Before the war, the affected Gulf countries exported 21 mb/d, of which 18 mb/d is seaborne through the Strait of Hormuz. In our blockade scenarios, exports from Bahrain, Iran, Iraq, Kuwait, and Qatar are zero, since they have no alternative routes. Saudi Arabia has a pipeline to the Red Sea that normally runs at 2 mb/d; we assume this can be increased to 5 mb/d in our analysis. The UAE has a pipeline bypassing the strait that normally runs at 1.1 mb/d; we assume this flow can be increased to 1.8 mb/d.[1] Consequently, the supply disruption from the Gulf is the seaborne oil that cannot be redirected via pipelines, and this is a flow of 14.2 mb/d in both our short and medium-term scenarios. Since we assume that the domestic consumption in the Gulf states is unaffected (see Appendix), we do not include it in our analysis.
Our short-term scenario reflects the period in which non-Gulf countries have inventories to draw from, while our medium-term scenario reflects the situation in which all inventories are depleted. In the short-term scenario, we assume inventory draws of 5 mb/d.[2] Furthermore, a minor part of the disruption is compensated for by increased production in non-Gulf countries.[3] The final global supply disruption is 8.5 mb/d in the short-term scenario and 13.1 mb/d in the medium term. The model then yields a global oil price of 120 $/b in the short term and 158 $/b in the medium term.
Finally, in the pre-war scenario, we assume a total Russian sales discount of 20 $/b on Russian oil to China and India due to sanctions, while Russian exports to other countries have no discount. The total discount has two components, the buyer’s discount and transport cost premium. China and India receive the buyer’s discount of 10 $/b, while intermediaries receive the transport cost component of 10 $/b. In the disruption scenarios, we assume that the discount disappears due to relaxed sanctions. This is a key uncertainty in our analysis.[5]
Table 1: Quantities and prices (data and model) in different scenarios

[4]. Gulf domestic production/consumption is 8.31 mb/d in all scenarios.
Results: Winners and Losers of a Blockade in the Short Run
Figures 1-3 show the results of a blockade scenario in the short run, that is, with inventory draws. Figure 1 depicts producer profit increase (dark) and consumer loss (light), both relative to GDP, for selected countries and groups of countries. The total of these (production minus consumption) constitutes the country’s change in net gains and is marked by the black bar. As can be seen, Russia profits considerably from the blockade. This is mainly due to the general price effect and to a lesser degree due to the assumed disappearance of the discount on its oil. The US profits marginally since it is a slight net exporter. EU+ (EU, Norway, Iceland, Switzerland, and UK) and OECD- in total lose marginally.[6] China loses more and India loses substantially. The reason for this pattern is that both China and India have a higher oil intensity than EU+ and that they lose both due to the world oil price increasing and due to the assumed elimination of the discount on Russian oil.
Figure 1: Producer profit and consumer loss, relative to GDP, induced by a blockade when inventory draws add 5 mb/d to the global market.
Figure 2 shows the equivalent producer profits and consumer losses broken down for the EU+ group. Notably, nearly all countries make net losses, with the major exception of Norway and the minor exception of Estonia.
Figure 2: Producer profit and consumer loss, relative to GDP, induced by a blockade when inventory draws add 5 mb/d to the global market.
Figure 3 shows the producer loss in the Gulf countries subject to the blockade. Most of them lose considerably from the blockade. The exception is Saudi Arabia, which enjoys a profit increase on the oil it does manage to export through its Western ports. This attenuates the loss it makes when not being able to export through its Eastern ports in the Gulf.
Figure 3: Lost export revenues for the Gulf states, relative to GDP, induced by a blockade, with inventory draws of 5 mb/d to the market.
Results: Winners and losers of the blockade after inventories have run out
Figures 4-6 show the results of a blockade scenario in the medium run. We here use the same parameters and quantities as in the short run, with the difference that we set inventory draws to zero. This is meant to capture the effects after the inventories have run out. This may happen should the blockade last for, say, 12 months. Here the price increases to 158 $/b. The transition between the previous short-run scenarios and the medium-run scenario will likely come gradually as the inventories are emptied.
Figure 4 shows the producer-profit increase (dark) and consumer loss (light), again relative to GDP, for selected countries. The results are similar to those in the short run, just more pronounced, so producers make larger profits and consumers make larger losses. Most pronounced is that Russia makes a net profit increase of around 11% of GDP while India’s consumers bear a cost equivalent to roughly 4% of GDP.
Figure 4: Producer profit and consumer loss, relative to GDP, induced by a blockade when there are no inventory draws.

Figure 5 shows the breakdown for the countries in EU+. The results are akin to those in the short run, but again more pronounced.
Figure 5: Producer profit and consumer loss, relative to GDP, induced by a blockade when there are no inventory draws.

Figure 6 shows the profit losses in the countries subject to the blockade. The difference to the short run is that now Saudi Arabia enjoys an even higher price effect on its western oil, so in total makes a substantial profit. Furthermore, the price effect is strong enough to make the United Arab Emirates increase its profits.
Figure 6: Lost export revenues for the Gulf states, relative to GDP, induced by a blockade, when there are no inventory draws.
Results: Inventories and Oil Reliance
In total, global oil inventories (crude and products) are estimated at 8210 mb as of January 2026, according to the IEA March 2026 Oil Market Report and other sources. Around half, 4088 mb, is held by OECD countries. OECD Europe holds 1285 mb, and the United States holds 1700 mb. China holds 1200 mb, India 250 mb, and other non-OECD countries hold 693 mb. Some of these consist of governments’ strategic reserves, while others consist of commercial stocks. Oil on water is estimated at 2000 mb. This is oil on tankers, either for storage or on the way to a buyer. Ignoring oil on water, the inventories could in theory cover 60 days of world consumption or around 400 days of disrupted supply due to the blockade.
On 11 March, the IEA and its 32 member countries decided to release 400 mb from their emergency stocks of 1200 mb and 600 mb of industry stocks held under government obligations. 400 mb is equivalent to 28 days of lost exports due to the blockade. In our short-term scenario, we assumed a draw of 5 mb/d. 1200 mb of emergency inventories would last for 240 days with such a draw. Under a slower release, of say 2 mb/d, the release will last for longer, but will then, of course, replace less of the blocked oil.
The oil released through this IEA decision will be released to the global market. It should thus have the same effects as increased production, benefiting any consumers of oil, wherever they reside. Should the blockade outlast this time span, and under the uncooperative nature of the current geopolitical landscape, it is, however, conceivable that some countries will choose to prioritize supplies for their own markets. In such a scenario, each country or geopolitical block may treat itself as an isolated market.
We briefly look here at how vulnerable different groups of countries would be to such a development. Figure 7 shows for select countries and groups of countries how much storage they have relative to their net imports. The values imply how many days of imports their storage can cover.[7] India could cover the shortest period of a disruption, followed by China.
Figure 7: Oil inventories divided by daily net imports.
Figure 8 shows oil consumption expenditures as a share of GDP in the pre-blockade scenario. This captures how reliant different economies are on oil. India has the most oil-intensive economy, while EU+ has the lowest oil intensity among these economies.
Figure 8: Oil intensity defined as oil expenditures divided by GDP pre-blockade.
Figure 9 shows an index of vulnerability that takes into account both how oil-intensive and how import-dependent the economies are. More precisely, it calculates as (net imports/storage)*(oil consumption expenditures/GDP). Here we clearly see that India is by far the most vulnerable: it has very high imports, low storage, and has an oil-intensive industry structure. EU+ is less vulnerable thanks to its economy having low oil intensity.
Figure 9: Vulnerability index defined as oil intensity multiplied by net imports relative to inventories.

Discussion of Further Considerations and Effects
Model Scenario Outcomes Vs Current Market Expectations:
Since the war started, global oil prices have been extremely volatile and have increased significantly. At the time of writing, Brent stands above $100/b.[8] A likely key driver of market movements is shifting assessments of how long the war and the de facto blockade will last. The current, relatively low price compared to our short- and medium-term scenarios (which assume prolonged disruptions), as well as sharply falling futures prices, indicates that the market expects a relatively short disruption. Our results thus show that if the disruption proves more persistent than currently priced by the market, oil prices could increase substantially from current levels, with significant implications for both energy markets and the broader macroeconomy.
Macroeconomic Effects and Inflation:
Our analysis is confined to the direct impact of the blockade on consumers and producers in various countries. The oil market is, however, large and fundamental in the sense that it constitutes a large share of GDP, and oil is an essential input to many production processes and economic activities. This means that a price shock can (and most likely will) spread throughout the macroeconomy in the form of inflation, reduced demand, and macroeconomic implications. Historically, such events have had profound effects (e.g., the oil shocks of the 1970s). While today’s economy is relatively less reliant on oil than it was then, the current disruption is larger. These contagious effects can happen both within a country (domestic buyers of oil-intensive products raise prices) or between countries (imports become expensive). This is not captured by our analysis but may ultimately become more serious and long-lasting than the initial direct effects.
Tensions Within Countries:
It is important to note that a country that on net gains from the blockade may still experience serious internal tensions since parts of its society gain (oil producers) while other parts lose (oil consumers). The net effects are informative to the extent that a country can reconcile these tensions, either by redistribution (such as in Norway), a high government take (such as in Russia and Norway), or by simply having a political system which can ignore the losers.
A Possible Excessive Rebound Effect:
Another factor not captured by the analysis is that the blocked countries have relatively flexible production allowing them to scale it up or down. This means that some of the oil they do not sell today because of the blockade can be sold tomorrow. Hence, over time they may recover some losses. Importantly, when the blockade disappears or easens, their exports of oil may be larger than Business as usual, implying excess supply and a substantial price drop. This may destabilize the world economy in the opposite direction of what we see now. Countering this, countries may start replenishing their storage.
Long-run Structuring of Oil Demand and Supply:
Following the oil-supply shocks in the 70s, importers of oil and more generally energy-intensive industries made substantial investments into alternative energy sources and into energy efficiency. We may, rationally, expect a similar change following this blockade should it last. But there are also forces pulling in the opposite direction. After the energy disruptions and price surges following Russia’s full-scale invasion of Ukraine, some countries (not least in the EU) decided to roll back fuel taxes (Gars et al., 2022). The motive for that was to mitigate the increased price facing consumers. Notably, many of these tax reductions remained even after the global oil price fell back. Basic economic theory would suggest an importer should keep fuel taxes when facing a supply disruption and use the proceeds to make transfers to the population. In particular, realizing oil supply shocks do occur, especially in a rivalrous geopolitical world, an oil importer should make efforts to reduce long-run reliance on oil. In the longer run this may benefit China who has a large market share in green technologies and associated materials.
Another pathway, not mutually exclusive with reducing demand, is that countries would increase domestic oil production where possible. Even though it is difficult to fully insulate an economy from global price shocks, the effects could be mitigated.
The Effect on Opec Cooperation:
The blockade and, in particular, Iran’s attacks on its neighbors’ oil production is a stress test for OPEC. How cooperation will evolve is difficult to predict. One possibility is that Iran is formally or informally left out of OPEC. Another is that Russia breaks out of OPEC+ or that the whole organization collapses. True, key members of OPEC (e.g., Iran and Saudi Arabia) have been regional adversaries for many years. But the escalation during this war is a substantial step into an open conflict.
Conclusion
This policy paper has – based on simple modeling of the oil market, – analyzed the immediate economic effects of the blockade of the Strait of Hormuz across countries and producers and consumers of oil. The effects are substantial, in particular for Russia (which profits significantly, 6-11% of GDP) and India (which incurs costs of around 2-4% of GDP). Europe is less affected compared to other countries and regions (0.5-2% of GDP), despite being a net importer of oil. This is thanks to its economy having low oil intensity. The US gains on net, since it is a net exporter of oil, but its consumers are subject to costs of around 1-2% of GDP due to its economy being oil-intensive. Perhaps surprisingly, even some of the Gulf countries can profit from the blockade if they manage to redirect their exports to ports outside the Strait of Hormuz.
The analysis shows that the existence and usage of oil inventories are of great importance. The inventories can only cover the supply disruption for about a year, or, if they are to last longer, replace only a small part of the shortage from the Gulf. If and when these inventories run out, the economic effects will be substantially larger. The inventories are not spread evenly: India is very vulnerable to a shortage, while the EU is much less vulnerable.
The blockade puts the oil market under substantial stress. The paper attempts to gauge the direct effects, which are by themselves very uncertain. The indirect and longer-run effects are naturally even more uncertain and may be even more severe, as discussed in the report.
References
- Gars, J., Spiro, D. and Wachtmeister, H., 2022. The effect of European fuel-tax cuts on the oil income of Russia. Nature Energy, 7(10), pp.989-997.
- Gars, J., Spiro, D. and Wachtmeister, H., 2025. Winners and losers of a Russian oil-export restriction. Public Choice, pp.1-31.
- Kilian, L., Rapson, D. and Schipper, B., 2024. The impact of the 2022 oil embargo and price cap on russian oil prices. The Energy Journal, p.01956574251414076.
- Spiro, D., Wachtmeister, H. and Gars, J., 2025. Assessing the impacts of oil sanctions on Russia. Energy Policy, 206, p.114739.
Appendix: Data, Method, and Its Limitations
We use data on oil production and consumption of different countries (from US EIA for 2024, the most recent year for which the full data set is available) to parameterize a model and compare how they fare without and with a blockade. For GDP, we use World Bank data for 2024.
The model used to assess the changes in consumer surplus and producer profits is a simple supply and demand model of oil. It is akin to Gars et al. (2025) , but with the restriction of supply coming from a reduction of the exports of countries inside the Strait of Hormuz rather than sanctions on Russia. We assume demand elasticity is the same in all countries at -0.2 and a supply elasticity of 0.02.[9] For the short-run analysis, we assume an inventory draw of 5 mb/d. We abstract from the profits made when selling these. These assumptions are crude and naturally do not capture all the effects and nuances, some of which we discuss at the end of the brief.
The model implicitly assumes that oil on the market can be traded and rotated freely. In other words, even if the blocked oil was originally bound to, say, China, supplies from elsewhere will be redirected to China until prices equalize across destinations. Consequently, our analysis focuses on the price effects of the blockade, and this price effect is assumed to apply equally across countries (though see the discussion below about the discount on Russian oil).
To analyze the impact on the Gulf countries directly affected by the blockade, we need to take a stance on what happens in their domestic oil markets. When these countries cannot export their oil, their domestic market will face excess supply. The producers in these countries can then either reduce production or flood their domestic market with oil. Since these countries are overwhelmingly net-exporters of oil, their domestic market cannot absorb all the excess supply that is stuck behind the blockade. Furthermore, these countries have historically had low domestic oil prices, making it unlikely that prices could fall much further and increase consumption significantly. We therefore assume that domestic consumption remains unchanged and that producers instead reduce excess production. Based on this assumption, we measure the effects on these countries as lost export revenues. Note that these countries’ production costs are rather low, so lost export revenues are nearly equivalent to profit losses. In analyzing profit gains in other producing countries, we base the costs implicitly on a constant-elasticity supply function. Hence, we do not take into account possible country differences with respect to this cost change, or if their costs would imply a non-constant elasticity. This is a simplification, but without greater loss of precision, since the main source of increasing profits is that the oil price goes up rather than from increased production (this follows from the supply elasticity being very low).
Footnotes
- [1] We deem the assumed redirected volumes as optimistic, as such flows have not been seen historically, and that both routes could be targeted in a prolonged conflict. ”.
- [2] On 11 March, IEA members decided to release 400 mb of their inventories. At a release speed of 5 mb/d that will last for 80 days.
- [3] This increase is endogenously generated by the model. The increase is 0.7 mb/d and 1.1 mb/d in the short- and the medium-run scenario respectively.
- [4] Gulf domestic production/consumption is 8.31 mb/d in all scenarios.
- [5] In January 2026 the total discount on Russian oil was around 30 $/b. This discount consisted of a transport cost premium and a buyer’s discount at the importer’s port. Both of these were driven by sanctions and bargaining power (see Spiro et al., 2025; Kilian et al., 2025) which we assume have disappeared under the blockade. This is a key uncertainty. Should the discount not disappear, our results overstate Russian gains, and the losses for China and India.
- [6] OECD- consists of OECD except EU+ and US: Canada, Chile, Mexico, Australia, Japan, South Korea, New Zealand and Turkiye.
- [7] Russia and US are net exporters so they do not, in theory, rely on storage should the market become fragmented. Hence we omit them from the figure. In practice, the US and Russia may still be vulnerable as they, especially the US, rely on both imports and exports of various kinds of crude and products to optimize refineries and production, etc.
- [8]Many physical crude benchmark prices are even higher, as well as certain refined products, indicating a stressed oil market under volatile reconfiguration.
- [9]We view these parameter assumptions as conservative in the sense that it implies assuming the oil market is more adaptable than it may be in practice. Estimates of demand elasticity in the literature are typically -0.125, though there are reasons to believe elasticity is higher for larger price shocks and due to new technologies making a switch between energy sources easier.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Antagonistic Information Threats: Lessons from Ukraine
Russia’s full-scale invasion of Ukraine highlights how modern conflict increasingly relies on antagonistic information threats alongside military force. This policy brief examines how such threats operate and what lessons they offer for European resilience. First, it outlines a framework through which hostile actors gradually weaken societies’ capacity to interpret events and trust institutions. Second, the brief analyzes Ukrainian cyber operations, highlighting that sustained defensive investment can reduce destructive impact even as attack activity intensifies. The brief further examines the economic implications, showing that antagonistic threats create continuous fiscal pressure as monitoring, detection, and incident response become permanent public expenditures rather than temporary crisis measures. Finally, the brief draws policy implications for Europe, stressing the need to treat cyber and information resilience as macro-critical infrastructure and to strengthen coordination across policy domains.
Introduction
Ukraine’s experience since the full-scale invasion of 2022 illustrates how antagonistic threats operate in contemporary conflict. The war demonstrates that modern confrontation extends far beyond conventional military force. Instead, it functions as a hybrid system in which military, informational, economic, and political instruments are combined into a coordinated architecture of pressure. While this dynamic is most visible in active war, its underlying mechanisms are not confined to the battlefield. Similar forms of antagonistic pressure are increasingly directed at European societies despite the absence of open military confrontation.
Within this broader system, information threats have become particularly significant, largely due to technological change and the digitalization of communication. Networked information environments allow hostile actors to combine cyber operations, disinformation campaigns, and other forms of manipulation at low cost and large scale, amplifying the effects of other forms of pressure. Information operations can shape how events are interpreted, undermine institutional trust, and influence political behavior, often reinforcing technical disruption or economic coercion.
This brief focuses on antagonistic information threats — hostile activities that include disinformation campaigns, cyber operations, and other forms of manipulation targeting the information environment. We first outline a structural framework for understanding the targets and effects of such threats. We then examine how cyber operations have been used in Ukraine and assess their associated costs. The brief concludes with policy lessons relevant for strengthening resilience in European societies.
Layers of Antagonistic Information Influence
Understanding antagonistic information threats requires moving beyond viewing disinformation or cyber incidents as isolated events. Instead, these activities form a structured and multi-layered architecture of pressure aimed at gradually degrading democratic governance. Rather than aiming for immediate institutional breakdown, these operations gradually weaken a society’s capacity to interpret events, trust institutions, and act collectively across four interconnected layers: cognitive, institutional, informational, and behavioral. This four-layer framing synthesizes Ukraine’s wartime practice with established research on cognitive warfare and decision-making manipulation, hybrid warfare, and institutional effectiveness (NATO STO, n.d.; Havlík & Horáček, 2026; Tsybulska, 2023; World Bank, 2017).
At the cognitive layer, hostile actors target how individuals interpret reality, shaping threat perception, responsibility attribution, and identity boundaries. This dynamic is well documented in research on cognitive warfare and reflexive control, which demonstrates that perception manipulation can redirect strategic decision-making without direct confrontation (Havlík & Horáček, 2026; Thomas, 2004). By exploiting uncertainty, fear, and emotional triggers, adversaries influence how citizens understand crises before institutional responses even occur. Cognitive distortion thus lays the foundation for broader destabilization.
At the institutional layer, hostile actors target trust in government, elections, and public authority. Evidence from hybrid warfare analysis demonstrates that weakening institutional legitimacy degrades both crisis response and democratic resilience (OECD, 2022; World Bank, 2017). As Tsybulska (2023) argues, delegitimization, rather than outright destruction, is often the central objective of a hybrid strategy. When public trust erodes, policy implementation fragments, and crisis communication loses authority.
The informational layer addresses narrative dominance and agenda-setting. Hostile actors use saturation, repetition, and cross-platform amplification to ensure that adversarial frames define the terms of public debate (McCombs & Shaw, 1972; Paul & Matthews, 2016). The goal is not simply to spread falsehoods but to normalize certain interpretations over time, embedding them into how societies process political reality (Tsybulska, 2024).
Finally, the behavioral layer translates perception and narrative control into observable outcomes, from voting behavior and protest mobilization to compliance with policy measures and support for defense decisions. Research on misinformation and political behavior demonstrates that even marginal shifts in turnout, polarization, or policy support can generate significant strategic consequences (Allcott & Gentzkow, 2017). Behavioral influence does not require majority conversion; small distortions at scale can reshape political outcomes.
Ukraine’s post-2022 experience shows that antagonistic information threats function as a long-term governance pressure system, designed for erosion. This is why recognizing the layered architecture of these threats is essential for building durable resilience.
Threats at the Operational Level: Lessons from Ukraine
Ukraine’s wartime experience illustrates how antagonistic information threats operate in practice, particularly through cyber operations. Unlike kinetic warfare, cyber operations continue even during ceasefires: they are relatively low-cost, scalable, and persistent, generating both technical disruption and information that can later be exploited in influence campaigns.
The Computer Emergency Response Team of Ukraine (CERT-UA) recorded 4,315 cyber incidents in 2024, nearly a 70% increase over 2023 and more than triple the 2021 level (SSSCIP/CERT-UA, 2025c). In the first half of 2025 alone, incidents increased by a further 17% (SSSCIP/CERT-UA, 2025b). These figures reflect strategic structural pressure, as shown in Table 1.
Table 1. Registered cyber incidents in Ukraine, 2021–2024

Source: CERT-UA / State Service of Special Communications and Information Protection of Ukraine (SSSCIP), Russian Cyber Operations: Analytics for the Second Half of 2024.At the same time, a parallel trend deserves attention: while overall incident volume rose sharply, critical and high-severity incidents declined by 94% between 2022 and 2024 (SSSCIP/CERT-UA, 2025a). Ukrainian authorities attribute this to strengthened monitoring networks, early detection mechanisms, and international cooperation. The policy conclusion is clear: sustained defensive investment reduces destructive impact even as attack frequency increases.
The operational model has also evolved. Rather than prioritizing spectacular disruption, campaigns increasingly emphasize persistent access, credential theft, and selective data exfiltration, so-called ‘steal and go’ tactics (SSSCIP/CERT-UA, 2025b). The objective is chronic degradation rather than dramatic collapse. Data theft supports later narrative exploitation; minor disruption normalizes instability; repeated low-grade incidents strain administrative capacity.
This shift aligns with the broader strategic goal identified in Ukrainian cybersecurity reporting: producing distrust, paralysis, delayed response, societal fatigue, and long-term strategic advantage. The sectoral and methodological breakdown confirms this pattern (Table 2).
Table 2. Target sectors and attack methods in Ukraine in 2024

Source: CERT-UA/SSSCIP, Russian Cyber Operations: Analytics for the Second Half of 2024. Sector figures are incident counts; method figures reflect malware-specific incidents.
Artificial intelligence (AI) further accelerates this dynamic. Large-scale content saturation campaigns, such as the Pravda/Portal Kombat network, have been documented flooding digital ecosystems and targeting AI retrieval environments (American Sunlight Project, 2025; Sadeghi & Blachez, 2025). While academic debate continues over the scale of LLM manipulation (Alyukov et al., 2025), the strategic investment in content flooding is well documented.
Generative AI reduces the marginal cost of producing multilingual disinformation. CERT-UA has also identified indications of AI-assisted scripting in phishing and malware deployment (SSSCIP/CERT-UA, 2025b). As Havlík and Horáček (2026) warn, AI increasingly enables the precision targeting of cognitive vulnerabilities, thereby compressing defenders’ response time.
These dynamics illustrate how cyber operations generate effects across the four layers of antagonistic information influence identified earlier. Repeated incidents and data leaks shape the informational environment; narrative exploitation of stolen or manipulated data affects how events are cognitively interpreted; persistent disruptions undermine institutional credibility and crisis response; and accumulated uncertainty ultimately influences political and societal behavior.
Crucially, antagonistic information threats do not operate alone. They are part of a synchronized system of persistent pressure. Cyber operations, Foreign Information Manipulation and Interference, economic coercion, electronic warfare, and kinetic activity are integrated into a unified strategy. Ukrainian authorities report temporal synchronization between cyber intrusions, energy-sector targeting, and missile strikes (SSSCIP/CERT-UA, 2025a). Narrative campaigns frame events before and after disruption; cyber operations generate exploitable material; economic pressure increases uncertainty; kinetic or electronic actions amplify fear. The compound effect exceeds what any single domain could achieve on its own.
Ukrainian experience highlights vulnerabilities relevant for Europe more broadly. Hybrid pressure operates as a synchronized, multi-domain system in which military, informational, economic, and political instruments reinforce one another. European governance, however, addresses these domains through separate institutional channels. Energy security, cyber defence, strategic communications, and democratic resilience are managed in distinct policy silos with different authorities and threat perceptions. This fragmentation creates exploitable gaps: an adversary operating through tightly coordinated cross-domain pressure can exploit exactly the delays and blind spots that institutional separation produces.
The lesson from Ukraine is therefore not limited to wartime resilience. Even without open conflict, antagonistic actors can pursue gradual systemic pressure by targeting infrastructure, information, economic vulnerabilities, and institutional trust simultaneously. Effective resilience, therefore, requires moving beyond sectoral responses toward integrated governance capable of anticipating and responding to coordinated cross-domain pressure.
Economic Costs of Antagonistic Information Threats
Antagonistic information threats are persistent and structurally embedded, which means their economic implications extend beyond isolated incidents. Ukraine’s experience provides a rare empirical case showing how these costs accumulate and how sustained investment can mitigate them. Hybrid pressure does not produce only one-off destruction; it generates continuous fiscal demand. Monitoring, detection, and incident response systems have therefore become permanent budget items rather than crisis expenditures.
In 2024 alone, national monitoring systems processed hundreds of billions of telemetry events, identified around 3 million security events, and confirmed 1,042 cyber incidents requiring formal response (SSSCIP, 2024). These figures illustrate that antagonistic threats impose a constant administrative and financial burden, underscoring the fiscal consequences of inaction.
Ukraine’s cybersecurity market reached approximately 138 million USD in 2024, having quadrupled over eight years (SSSCIP, 2024). This growth reflects systemic adaptation under sustained pressure rather than discretionary digital modernization. The statistics in Table 1 show that investment did not eliminate the threat, but it fundamentally reduced its destructive impact. The burden falls disproportionately on public administration. With 76% of recorded incidents targeting government, local authorities, and the defense-industrial sector, the fiscal weight of cybersecurity concentrates where the budgets are most constrained. In this way, the institutions most essential to democratic governance bear the highest cost of defence.
Beyond direct-response spending, antagonistic threats impose systemic economic costs. Insurance premiums rise while cyber coverage narrows; compliance costs increase under frameworks such as NIS2, and procurement and crisis coordination become slower and more complex. As public administration becomes a primary target, trust and institutional credibility weaken, raising coordination costs across markets and public systems. As a result, governance efficiency itself becomes economically vulnerable.
At the same time, the costs of inaction are substantial. At the European level, ENISA estimates total cyber-related losses over five years at approximately €300 billion, with Germany alone reporting €205.9 billion in losses in 2023 (Nagy, 2023). While these figures do not isolate state-linked hybrid operations, they indicate the fiscal environment in which antagonistic threats operate and suggest a scale of what unmitigated exposure would cost.
The EU’s persistent security workforce deficit of 260,000 to 500,000 specialists (ENISA, 2024) further constrains the capacity for the type of sustained defensive investment that Ukraine’s experience shows to be effective.
Table 3 highlights a central policy lesson. In Ukraine, both the number of detected threats and the capacity to identify them increased sharply, while the share of destructive incidents declined significantly. This demonstrates that rising incident volume does not necessarily translate into rising damage. It thus indicates that the economic trade-off is not between security spending and fiscal savings, but between investing in preventive resilience and absorbing escalating systemic costs.
Table 3. The Returns on Sustained Investment, Ukraine

Sources: CERT-UA/SSSCIP (2025a, 2025b, 2025c); SSSCIP (2024); ENISA (2024); Howden (2025).
In economic terms, resilience reduces the probability of high-impact shocks, whereas delayed investment merely defers their costs. For European policymakers, cyber and information resilience must be treated as macro-critical infrastructure, with financial consequences extending well beyond IT systems into fiscal stability, labour markets, and long-term growth.
Conclusions
Ukraine’s experience since 2022 demonstrates that antagonistic information threats must be treated as a systemic governance challenge, not just a communication problem. Operating simultaneously across cognitive, institutional, informational, and behavioral layers, these threats aim to erode decision-making capacity rather than trigger immediate collapse. The strategic objective is gradual fragmentation of perception, trust, narrative coherence, and ultimately political action. For policymakers, the implication is straightforward: resilience must be built across all four layers.
Moreover, Ukraine’s operational data demonstrates that antagonistic information threats are persistent, adaptive, AI-accelerated, and strategically synchronized. Resilience must therefore be systemic, coordinated, and anticipatory, not reactive and sector-bound.
Ukrainian experience shows that sustained investment did not eliminate cyber pressure, but it dramatically reduced high-severity impact while expanding detection capacity. At the same time, the burden of defense falls disproportionately on public administration. Treating resilience spending as macro-critical infrastructure investment could be part of the solution.
References
- Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of Economic Perspectives, 31(2), 211–236.
- Alyukov, M., Makhortykh, M., Voronovici, A., & Sydorova, M. (2025). LLMs grooming or data voids? Harvard Kennedy School Misinformation Review, 6(5).
- American Sunlight Project. (2025, February 26). Russian propaganda may be flooding AI models: The Pravda network and risks to AI information integrity.
- European Union Agency for Cybersecurity (ENISA). (2024). 2024 report on the state of cybersecurity in the Union.
- Havlík, M., & Horáček, J. (2026). War is a mind game: Countering weaponized information. NATO Defense College.
- Howden (2025). Rebooting growth. Howden’s 2025 cyber insurance report.
- McCombs, M., & Shaw, D. (1972). The agenda-setting function of mass media. Public Opinion Quarterly, 36(2), 176–187.
- Nagy, C. (2023, December 11). 2024 cybersecurity predictions and emerging threats in Germany. SecurityBridge.
- NATO Science and Technology Organization (NATO STO). (n.d.). Cognitive warfare: NATO chief scientist research report.
- OECD. (2022). Building Trust to Reinforce Democracy: Main Findings from the 2021 OECD Survey on Drivers of Trust in Public Institutions, Building Trust in Public Institutions. OECD Publishing.
- Paul, C., & Matthews, M. (2016). The Russian “firehose of falsehood” propaganda model. RAND Corporation.
- Sadeghi, M., & Blachez, I. (2025, March 6). A well-funded Moscow-based global ‘news’ network has infected Western artificial intelligence tools worldwide with Russian propaganda. NewsGuard.
- State Service of Special Communications and Information Protection of Ukraine (SSSCIP) / CERT-UA. (2025a). Russian Cyber Operations: Analytics for H2 2024.
- State Service of Special Communications and Information Protection of Ukraine (SSSCIP) / CERT-UA. (2025b). Russian Cyber Operations: Analytics for H1 2025.
- State Service of Special Communications and Information Protection of Ukraine (SSSCIP) / CERT-UA. (2025c). CERT-UA recorded 4,315 cyber incidents in 2024.
- Thomas, T. (2004). Russia’s reflexive control theory and the military. Journal of Slavic Military Studies, 17(2), 237–256.
- Tsybulska, L. (2023). Hybrid warfare in Ukraine. Carnegie Council for Ethics in International Affairs.
- Tsybulska, L. (2024). Russian culture is a shining Trojan horse with tanks, bombs, and missiles inside. Detector Media.
- World Bank. (2017). World development report 2017: Governance and the law.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Do Election Results Shape Legitimacy Perceptions in Autocracy?
Elections remain a central feature of many authoritarian regimes despite widespread manipulation and limited political competition. Using a survey experiment with a nationally representative sample of Russian voters, this study examines whether improving perceptions of legitimacy can help explain why autocrats hold elections. The results show that information about high turnout increases trust in government, while information about low turnout reduces it, with effects driven by government supporters and individuals who believe in election integrity. This suggests that authoritarian leaders may use elections and reported electoral outcomes strategically to reinforce legitimacy among their support base and manage public perceptions over time.
Puzzle of Autocratic Elections
In recent decades, many authoritarian regimes have increasingly adopted institutions resembling those of democracies, particularly elections (Guriev and Treisman, 2019). Autocrats often organize multiparty elections and invite international observers, even as they manipulate outcomes through widespread fraud. This combination raises an important puzzle: if elections do not truly determine political power, why do authoritarian leaders hold them?
A large body of research has examined how authoritarian elections are organized (Gandhi and Lust-Okar, 2009; Gehlbach et al., 2016; Egorov and Sonin, 2020), including strategies such as limiting competition (Gandhi and Przeworski, 2007; Egorov and Sonin, 2021), managing media and information (Egorov et al., 2009; Edmond, 2013), and using elections to signal regime strength or monitor elites (Gehlbach and Simpser, 2015). However, less is known about whether these elections actually shape voters’ perceptions of government legitimacy (Dukalskis and Gerschewski, 2017).
One seemingly straightforward way to approach this question is to look at the relationship between electoral participation and trust in government, a key measure of political legitimacy. For example, across OECD countries, higher turnout is strongly correlated with greater trust in national governments (Figure 1). However, this descriptive pattern does not establish causality. Economic conditions may simultaneously shape both trust and electoral outcomes, creating omitted variable bias, while legitimacy itself may influence participation, leading to reverse causality.
These limitations point to the need for causal evidence on whether election results influence perceptions of legitimacy, particularly in non-democratic settings. The importance of such evidence is underscored by recent policy interest, including a commissioned report for the European Parliament on authoritarian legitimation through elections (Demmelhuber and Youngs, 2023). This policy brief presents findings from a recent study that addresses this issue, using a Russian election as a case study.
Figure 1. Trust in government and voter turnout in parliamentary elections in OECD countries (2017-2020)

Note: Trust is measured as a percentage of the population over 15 years old who answered ”Yes” to the following question in a nationally representative survey: “In this country, do you have confidence in the national government?” (Source: OECD). Turnout is the percentage of the registered voting population who voted in the last parliamentary election (Source: IDEA). Countries with compulsory voting are excluded.
Survey Experiment
To causally assess whether reported election outcomes influence perceptions of government legitimacy, the study implemented a survey experiment using a nationally representative sample of 1,603 Russian voters. The central feature of the design was a randomized information treatment that generated exogenous variation in respondents’ exposure to election results.
After completing the initial socio-demographic questions, respondents reported their prior political participation as well as their recollections of how past elections were conducted and their outcomes. Respondents were then randomly assigned to one of five treatment arms and asked to evaluate a hypothetical government formed after an upcoming election, with information about the election outcome randomly varied across treatment arms.
A control group received no information about hypothetical election results. Two groups were informed only about hypothetical voter turnout, which was presented as either low (38%) or high (66%). Two additional groups received information about turnout, either low or high, combined with a high vote share for the leading party (72%).
Following the information treatment, respondents reported their levels of trust in government, perceptions of whether the government represented national and personal interests, and their approval of and willingness to comply with hypothetical laws. These outcomes served as proxies for different dimensions of political legitimacy.
Election Outcomes Shape Trust in Government – but Only for Incumbent Supporters
By comparing responses across treatment groups, the experiment isolated the causal impact of election outcomes on legitimacy perceptions while holding constant respondents’ other characteristics. Respondents exposed to information about low turnout express significantly lower trust in government compared to those who received no information. On average, low turnout reduces trust by approximately 0.77 points on a ten-point scale, equivalent to about 0.25 standard deviations. In contrast, exposure to high turnout increases trust by around 0.68 points, or 0.22 standard deviations.
Providing additional information about the ruling party’s vote share does not significantly alter these effects. When high vote share information was combined with low turnout, trust increased slightly by 0.07 points, while adding vote share information to high turnout reduced trust by about 0.40 points; neither difference is statistically significant.
The impact of turnout information is highly heterogeneous. The observed effects are driven by individuals who expressed support for the ruling party, United Russia. Among these respondents, low turnout substantially lowers trust, while high turnout leads to a significant increase in trust. In contrast, opposition supporters do not update their perceptions in response to any of the information treatments: their trust levels remain statistically indistinguishable from those of the control group.
Moreover, the study examines heterogeneity based on baseline perceptions of electoral fraud. Before administering the information treatments, respondents were asked how frequently they believed irregularities in vote counting occur in Russian elections. Individuals who reported frequent violations are likely to view election outcomes as non-transparent and therefore to distrust official results, suggesting that information about turnout and vote share should have limited impact on their perceptions. Consistent with this expectation, no significant effect of turnout information on trust in government is observed among respondents who report a higher frequency of such violations.
Figure 2. Effect of information on trust relative to the control group

Note: This plot shows the effects of information treatments on trust in government relative to receiving no information (control group). Black circles are coefficient estimates for each group, with horizontal lines showing 95% confidence intervals.
Mechanisms: Expectation Shock and Anchoring
To examine how election information affects perceived legitimacy, the study relies on respondents’ reported recollections of past election results, including turnout and leading party performance. These prior beliefs provide a baseline against which new information is interpreted, as respondents tend to anchor their expectations about future elections to what they remember from previous ones.
When information about hypothetical election outcomes is presented, it generates exogenous shocks to these expectations. The magnitude and direction of each shock is defined as the difference between a respondent’s prior belief and the reported hypothetical outcome. By varying turnout between low and high values and combining turnout with high ruling party results, the experiment produced both positive and negative expectation shocks.
The results indicate that positive shocks, when the reported turnout exceeds prior beliefs, increase legitimacy across treatment groups, while negative shocks, when reported turnout is below the expected one, decrease legitimacy regardless of the treatment arm.
These findings suggest that election outcomes shape legitimacy by generating expectation shocks, and that respondents anchor beliefs about future elections to their perceptions of past results; in the absence of such anchoring, deviations between reported outcomes and respondents’ priors would have had little effect.
However, in the case of the leading party’s vote share, the resulting shock was rather small: an average respondent reported recalling the past vote share as 65%, while the value used in the information treatments was 72%. If respondents indeed anchor expectations about future election outcomes to past results, this may explain the absence of an additional effect of the vote share information, as the treatment did not generate a sufficiently strong expectation shock.
Conclusion
Do election results affect an autocrat’s perceived legitimacy? Using a survey experiment with a nationally representative sample of Russian voters, this study provides evidence that information about election outcomes can shape trust in government in an authoritarian setting. The results show that exposure to high (low) voter turnout increases (decreases) trust in government, with these effects concentrated among government supporters and individuals who believe elections are generally fair. This pattern suggests that autocrats may have limited ability to influence opposition supporters and instead rely on reinforcing legitimacy within their existing support base.
In addition, because voters anchor their expectations to past results, autocrats may be incentivized to generate higher outcomes while exercising caution in revealing lower ones in future elections. This underscores the role of autocratic elections as a tool to manage public perceptions over time.
The results of this study show that information about election outcomes holds strategic significance in non-democracies, as it can shape perceptions of government legitimacy. Policymakers should therefore prioritize support for independent media that provide credible information about election outcomes, even when results in authoritarian contexts appear predictable.
References
- Demmelhuber, T. and R. Youngs (2023). Strengthening the right to participate: legitimacy and resilience of electoral processes in illiberal political systems and authoritarian regimes. Technical Report PE702.581, European Parliament.
- Dukalskis, A. and J. Gerschewski (2017). What autocracies say (and what citizens hear): proposing four mechanisms of autocratic legitimation. Contemporary Politics 23(3), 251–268.
- Edmond, C. (2013, October). Information Manipulation, Coordination, and Regime Change. Review of Economic Studies 80(4), 1422–1458.
- Egorov, G., S. Guriev, and K. Sonin (2009). Why Resource-poor Dictators Allow Freer Media: A Theory and Evidence from Panel Data. American Political Science Review 103(4), 645–668.
- Egorov, G. and K. Sonin (2021). Elections in Non-Democracies. The Economic Journal 131(636), 1682–1716.
- Gandhi, J. and E. Lust-Okar (2009). Elections Under Authoritarianism. Annual Review of Political Science 12(1), 403–422.
- Gandhi, J. and A. Przeworski (2007). Authoritarian Institutions and the Survival of Autocrats. Comparative Political Studies 40(11), 1279–1301.
- Gehlbach, S. and A. Simpser (2015). Electoral Manipulation as Bureaucratic Control. American Journal of Political Science 59(1), 212–224.
- Gehlbach, S., K. Sonin, and M. W. Svolik (2016). Formal Models of Nondemocratic Politics. Annual Review of Political Science 19(1), 565–584.
- Guriev, S. and D. Treisman (2019). Informational Autocrats. Journal of Economic Perspectives 33(4), 100–127.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Russia’s New Strategy in Africa: Big Ambitions, Limited Gains
Russia’s renewed engagement with Africa has expanded rapidly since 2022, as Moscow seeks to counterbalance its growing international isolation. Drawing on trade, diplomatic, and UN voting data, this brief finds that while Russia has intensified relations with a handful of African states, the overall involvement remains limited in scope and depth. Economic ties are concentrated in fragile and politically isolated countries, while indicators of political alignment, such as UN General Assembly voting, suggest declining rather than increasing support. Russia’s new strategy may yield short-term geopolitical leverage but shows little sign of delivering durable economic or political gains.
Since the introduction of Western sanctions in 2014, and especially following its full-scale invasion of Ukraine in 2022, Russia has intensified its geopolitical and economic engagement across Africa. A previous brief (Berlin, 2024) outlined the main areas of Russian activity and the strategic objectives behind this renewed focus. As discussed there, Russia’s approach stands in sharp contrast to the longer-term strategies of both traditional Western partners and newer actors such as China. Rather than pursuing sustained investment or development-oriented cooperation, Moscow has adopted a realist and opportunistic stance, prioritizing short-term gains while paying little attention to potential side effects such as heightened instability and conflict. This brief examines whether this strategy is yielding tangible results for Russia; specifically, whether it has succeeded in strengthening ties with valuable new partners on the African continent and securing broader diplomatic legitimacy.
Uneven Economic Footprint
Trade statistics show a modest expansion of Russia–Africa trade since 2022, with growth concentrated among a few countries. Egypt shows the strongest increase in its share of Russia’s exports, while other countries with noticeable gains include Ethiopia, Tanzania, Uganda, and Madagascar. Many of these states are resource-rich, supplying Russia with minerals and agricultural goods, ranging from citrus, olives, and cocoa to gold, diamonds, and uranium. Some are former French colonies that harbor various degrees of anti-French or anti-colonial sentiment and, except for Egypt, maintain a degree of distance from Western trade and aid networks. This pattern suggests that Russia’s growing import links are concentrated among commodity-exporting and geopolitically flexible countries, reflecting a pragmatic effort to diversify supply sources rather than the emergence of deep economic partnerships.
Figure 1. Average change in export share to Russia, 2022-2024 vs 2019-2021.

Source: Mirrored trade data from CORISK.The countries showing the strongest increases in imports from Russia since 2022 include Libya in the north; Côte d’Ivoire, Ghana, and the Republic of the Congo in the west; and Tanzania, Uganda, Kenya, and Zimbabwe in the east and south. Most of these economies are net-importers of fuel, fertiliser, and grain. In the immediate aftermath of the full-scale invasion, Russia appears to have sought to gain market advantage over Ukrainian exports (and did so in part by capitalising on the Ukrainian port blockade). Several countries have also entered into cooperation in nuclear technology. These are all sectors in which Russia has for a while actively sought to expand its market presence. Arms sales had also been among Russia’s most profitable exports to the continent, until the escalation of the war in Ukraine tied up most of its capacity. Nevertheless, the overall volume of trade with Russia remains modest compared with Africa’s exchanges with other major partners.
Figure 2. Average change in import share from Russia, 2022-2024 vs 2019-2021.

Source: Mirrored trade data from CORISK.
Few of Africa’s most dynamic economies, those experiencing sustained growth and deeper integration into global markets, feature prominently in this trend. Only Ethiopia, Tanzania, and, to some extent, Kenya stand out as moderately growing economies with notable trade expansion toward Russia. This pattern could indicate that Russia’s engagement is driven more by short-term political expediency than by prospects for durable economic cooperation. At the same time, it may also reflect a reactive strategy, with Russia focusing on partners that remain accessible, while wealthier and more stable countries have limited need or willingness to risk established ties with Western markets.
Politics Over Partnership
Diplomatic data reveal a similar pattern. Between 2022 and 2023, Moscow’s state visits to Africa focused heavily on slower-growing or politically isolated countries, including Mali and Sudan. Only Egypt and Ethiopia, both larger economies with diversified external relations, received higher-profile visits and strategic agreements. Participation in the 2023 Russia–Africa Summit in St Petersburg, although broad, with 49 of 54 African countries represented, was lower than at the inaugural summit in Sochi in 2019, with only 17 heads of state compared to 43 in Sochi. Further, these came predominantly from slower-growing or politically isolated countries, including Mali, Burkina Faso, the Central African Republic, the Republic of the Congo, Eritrea, Libya, and Zimbabwe. While larger economies such as Egypt, South Africa, and Senegal also participated at a high level, the overall pattern suggests once more that Russia’s recent outreach has concentrated on politically receptive or less globally integrated states, reflecting both the reluctance of more dynamic economies to risk established ties with Western partners and Moscow’s limited room for maneuver.
In turn, Russia’s military cooperation agreements with African states have increased markedly in recent years. Documented cases include, again, many of the countries already mentioned above, such as the Central African Republic, Mali, Libya, Sudan, Burkina Faso, and Niger.
The combination of arms deals, Wagner-linked security arrangements, and elite-level political support reflects a transactional approach, where immediate influence outweighs sustainable cooperation.
UNGA voting patterns
If Russia’s growing presence were translating into stronger political alignment, one way this would be visible would be in international voting patterns. Yet UN General Assembly data indicate the opposite trend. While several African countries abstained, rather than siding against Russia on the three major resolutions on Ukraine, which has concerned many observers, in general, the average agreement rate of African countries with Russia, historically around 75–80 percent, has fallen to its lowest level since the 1970s.
Figure 3. Average agreement with Russia/USSR in UN resolutions over time

Source: Bailey et al., 2017
Figure 4. Distribution of agreement with Russia/USSR in UN resolutions over time

Source: Bailey et al., 2017. Lighter shades from blue to red to yellow represent more recent voting distributions.
The distribution of votes has become increasingly polarized, with more countries distancing themselves or adopting neutral positions. These patterns suggest that Russia’s efforts to leverage security and diplomatic engagement into broader political loyalty have met limited success. Despite increased activity, Russia’s influence appears confined to a narrow set of partners rather than expanding across the continent.
The Battle Over Hearts and Minds
Foreign presence, whether in the form of military, economic, or diplomatic engagement, can shape public attitudes in complex ways. During the Cold War, for example, development cooperation to Africa was widely used as a tool to project ideological influence and promote alternative institutional models, values, and norms. As the foreign aid paradigm came under critical scrutiny from the 1980s onward, the question of how aid affects attitudes toward donors and development models has become increasingly salient (Andrabi and Das, 2005).
The impact of foreign actors on local perceptions has been explored across various settings. A substantial literature has examined the United States and, to some extent, the USSR as two of the most prominent power actors in the international arena, spanning foreign aid, economic and diplomatic relations, and military involvement (Allen et al., 2020; Vine, 2015). Similarly, Chinese investment and lending have gained popularity in many countries but have also been linked to increased corruption and weakened governance in some contexts (Isaksson & Kotsadam, 2018a, 2018b).
In fragile or politically unstable regions, especially those marked by weak state control, violent conflict, or active competition for power among domestic or international actors, public opinion is particularly vulnerable to external influence. In such contexts, and particularly where Russia is present, disinformation campaigns, anti-Western narratives, and appeals to historical grievances can play a significant role in shaping attitudes and perceptions. Russian propaganda efforts are often focused on delegitimizing Western actors by invoking anti-colonial rhetoric and promoting authoritarian, revisionist alternatives (Lindén, 2023; Akinola & Ogunnubi, 2021). Indeed, information influence remains one of the domains where Russia can achieve the greatest impact at minimal cost. While resource constraints are beginning to limit Moscow’s ability to “buy” influence through trade incentives, arms deals, and other forms of economic cooperation, manipulating audiences on platforms such as X or Facebook through coordinated networks of bots remains inexpensive and effective. A recent study by Cedar reports that RT France (formerly Russia Today) has expanded its following on X by 80 percent and on Facebook by 35 percent since 2022. Ukraine’s military intelligence (HUR) notes that in 2025 RT also began translating content into Portuguese to reach audiences in Mozambique and Angola, and plans to launch programming in Amharic to target viewers in Ethiopia by the end of the year.
Western organizations must do a better job at communicating the benefits of their engagement and the values behind it. In regions saturated with Russian media messaging, proactively engaging local narratives by highlighting successful projects, promoting transparency, and countering misinformation is key to maintaining public goodwill.
Figure 5. Share of African audiences increased as RT’s access in Europe was restricted

Source: Cedar.
Conclusion
Russia’s engagement in Africa is driven less by economic partnership and more by opportunistic, short-term goals: access to strategic resources, military presence, and symbolic legitimacy. While these ties may help Moscow navigate temporary diplomatic isolation, they do not appear to generate lasting political or economic gains for Russia, for the time being.
A pressing question is whether they impact development outcomes for African counterparts, and in what direction. Ongoing work within the FREE NETWORK is now using geolocated data to identify how Russian and Wagner-linked activity shapes donor engagement, local development, and public sentiment across affected regions (see preliminary results in Berlin and Lvovskyi, 2025). The analysis is expected to provide a clearer assessment of whether Russia’s outreach in Africa delivers tangible influence or remains largely symbolic.
References
- Akinola, Akinlolu E., och Olusola Ogunnubi. ”Russo-African Relations and Electoral Democracy: Assessing the Implications of Russia’s Renewed Interest for Africa”. African Security Review, 03 juli 2021. https://www.tandfonline.com/doi/full/10.1080/10246029.2021.1956982
- Allen, Michael A., Michael E. Flynn, Carla Martinez Machain, och Andrew Stravers. ”Outside the Wire: U.S. Military Deployments and Public Opinion in Host States”. American Political Science Review 114, nr 2 (may 2020): 326–41. https://doi.org/10.1017/S0003055419000868.
- Andrabi, Tahir, Jishnu Das. “In aid we trust: Hearts and minds and the Pakistan earthquake of 2005″. Review of Economics and Statistics, 99 (3), (2017) pp. 371 – 386
- Bailey, Michael A., Anton Strezhnev, and Erik Voeten. “Estimating dynamic state preferences from United Nations voting data.”Journal of Conflict Resolution 61.2 (2017): 430-456.
- Berlin, Maria P., 2024. “Russia in Africa: What the Literature Reveals and Why It Matters”, FREE Policy Brief.
- Berlin, Maria P., and Lev Lvovskyi 2025. “Russia’s Involvement on the African Continent and its Consequences for Development: The Aid Channel”, SITE Working Paper No 64.
- Isaksson, Ann-Sofie, och Andreas Kotsadam. ”Chinese aid and local corruption”. Journal of Public Economics 159 (2018a): 146–59. https://doi.org/10.1016/j.jpubeco.2018.01.002.
- Lindén, Karolina. ”Russia’s Relations with Africa: Small, Military-Oriented and with Destabilising Effects”, 2023.
- Vine, David. 2015. Base Nation: How U.S. Military Bases Abroad Harm America and the World. New York: Metropolitan Books/ Henry Holt.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
The Case for a Transport Ban on Russian Oil
In this policy brief we discuss the effects that would arise if the EU imposed a full transport ban on Russian oil. The transport ban would imply that any oil tanker transporting Russian oil would be prohibited from any oil trade involving the EU and from entering EU ports. We argue that such a transport ban would achieve the intended objectives of the EU’s oil sanctions: to reduce Russia’s oil income without risking surging oil prices.
Background
In its ambition to protect Ukraine and itself from Russia, the EU has two toolboxes at its disposal: military defense and economic warfare. The purpose of economic warfare is to “reduce the economic strength, hence the war potential, of the enemy relative to [one’s] own“ (Wu, 1952, p.1). It essentially boils down to the dual goal of harming your opponent without harming yourself too much (Snidal, 1991; Spiro, 2023).
Following the full-scale invasion in 2022, the EU and other countries significantly ramped up the oil sanctions against Russia as part of this economic warfare. Among them, the import embargo on Russian oil has been the most consequential; the G7 price cap on Russian oil, while being more politically salient, quickly lost much of its initial efficacy (Kilian et al., 2024; Spiro et al., 2025). Sanctions are like a cat-and-mouse game where Russia has now managed to circumvent the price cap to a high degree. The question for the EU, therefore, is how to revise the price cap sanction or what to replace it with. This policy brief analyzes one option: a full transport ban on Russian oil. To understand why and how such a sanction would work, it is, however, important to understand why the price cap does not.
The Price Cap: In Theory and Practice
Theoretically, the price cap sets a maximum price for Russian oil exports. Initially, the G7 cap was set at $60/bbl, while the EU later lowered it to $47.60/bbl. The practical implementation of the price cap was through the tanker and insurance markets. Any tanker transporting Russian oil at a price above the cap would not be able to get access to Western insurance or services. Since a very large part of the tanker fleet was, at the time of implementation, insured in the UK, this was consequential. Eventually, an additional constraint was added: tankers not following the price cap would not be allowed to access European ports.
The rationale for the price cap, at the time of its implementation, was that the G7 wanted to achieve the dual goal of economic warfare: it wanted to harm Russia by limiting its oil income while minimizing the harm to the global economy by ensuring Russia would not reduce oil exports. It was believed that a price cap set at 60 $/bbl would achieve that dual goal. With a world oil price at $80-100/bbl, the cap would severely reduce Russia’s oil profits; but since Russia’s cost of production is $5-15/bbl, it would have economic incentives to continue exporting oil (Gars et al., 2025; Johnson et al., 2023; Wachtmeister et al., 2022).
The price cap initially worked as intended: combined with the EU import embargo, it drove significant discounts on Russian oil while export volumes remained steady (Babina et al., 2023; Spiro et al., 2025; Turner & Sappington, 2024). Over time, however, the price cap’s efficacy eroded (Cardoso et al., 2024; Kilian et al., 2024; Spiro et al., 2025). This was for two main reasons: 1) the expansion of the “shadow fleet” of tankers willing to transport Russian oil without Western insurance or services; 2) fraudulent paperwork, allowing some tankers to appear compliant while actually transporting Russian oil at a price above the cap (Hilgenstock et al., 2023).
By early January 2025, only 15% of crude-oil tankers departing Russia used Western insurance (CREA, 2025), with the remainder being part of the shadow fleet. After the implementation of large-scale vessel sanctions later that month by the US Treasury’s Office of Foreign Assets Control (OFAC), the share of tankers using Western insurance increased. This indicates the shadow fleet can be affected by countermeasures. Yet, despite the strengthened sanctions, by October 2025, around 65% of shipments still used the shadow fleet, even as a large portion of that fleet now consisted of sanctioned vessels. A large part of the remaining 35%, while officially compliant, likely circumvented the price cap by use of fraudulent paperwork.
Extensive additional monitoring and enforcement capacity would be required to eliminate such fraud. To restore the full intended function of the price cap, or make a lowering of the cap meaningful, the shadow fleet would also need to be substantially reduced. But given recent estimates putting the shadow fleet at around 18% of global tanker tonnage (The Maritime Executive, 2025) this seems hard to achieve.
Given the challenges involved in re-establishing this system, an alternative approach is to replace the price cap altogether. So, what could serve as an effective replacement?
A Full Transport Ban
We here consider a transport ban on Russian oil. In practice, under such a transport ban, a European coalition of countries would ban any tanker carrying Russian crude oil or refined products from entering European ports and using European services, either permanently or at least for as long as the ban is in place. Consequently, such tankers would be banned from any European oil trade, including, for instance, oil sold by OPEC countries to the EU, as well as any European maritime services in the future. This restriction would apply regardless of the sale price or whether the shipment formally complied with the G7 price cap.
Notably, in 2022, one of the sanctions planned by the EU and discussed within the G7 was a “service ban” that would be akin to the transport ban proposed here. The EU and G7 eventually decided not to implement it and to introduce the price cap instead, due to fears that such a sanction would come at a great cost to the world economy. Since Russia at the time only had access to a small tanker fleet of its own, a service ban would have resulted in an export reduction and an oil-price spike (Gars et al., 2025). This fear may have been well-founded there and then. However, as argued below, it is not a major concern today.
How a Transport Ban Would Work Today
The economic harm to Russia from a transport ban would come through the tightening of the tanker market that Russia can access. A tanker owner would essentially need to decide whether they want to transport Russian oil (around 10% of all seaborne oil trade) or have access to trade involving the EU countries (around 23% of seaborne oil trade). This, in essence, constitutes a trade-off between the short-run gains from transporting Russian oil and the longer-term consequences of the tanker being permanently sanctioned. Since the transport ban would be aimed at the tanker, it would also reduce the tanker’s value if sold. Plausibly, tanker owners would then only agree to transport Russian oil if they receive a sufficiently large premium compared to the income from transporting other oil. This would translate into higher transport costs for Russia, squeezing its profit margins (Spiro et al., 2025). How much Russian transport costs would increase is hard to say, but it should be noted that even an increase of $5 per barrel in these costs for crude implies Russian losses equal to 0.5% of GDP (Spiro et al., 2025).
Since Russian profit margins are very large, they would likely be willing to pay that premium. Furthermore, given that export reductions would inflict losses on Russia itself and on its key partners (China and India, see Gars et al., 2025), it is unlikely that Russia would reduce its exports as a sort of retaliation. The risk of a Russian supply disruption and an oil-price spike is thus low under a transport ban. In other words, a transport ban would inflict costs on Russia without risking major costs to the EU.
Other Advantages
Importantly, under the described transport ban, paper fraud would become a non-issue. The sanctioning coalition would only need to monitor whether a tanker has entered a Russian port. Any such vessel would be placed on the banned list, regardless of whether it belongs to the shadow fleet, is Western-owned, or claims compliance with the price-cap regime. Given that a large share of Russian oil exports goes through European waters and chokepoints (e.g., the Danish Straits), it should be possible for the EU to identify such tankers, in particular those transporting Russian oil through the Baltic Sea (46% of all seaborne Russian crude and products).
Furthermore, this EU-led transport ban would not depend on coordination with the United States. The effectiveness of this sanction stems from geography, where a large share of Russian oil transits EU-controlled waters, and from the EU’s position as a large oil importer (13.7 mb/d). That said, if more countries joined the sanctioning coalition, the cost of ending up on the sanctioned list would be higher. Similarly, the premium required by the tanker owners would be higher. Hence, the sanction would be more effective if other major importers, such as Japan and South Korea, or major exporters, such as Canada and Norway, joined the coalition. US participation would, of course, also add weight, but would not be essential for the core mechanism to work.
Potential Problems and Interactions with Other Sanctions
One problem that a transport ban would likely not solve and could even exacerbate is the environmental risks posed by the poor condition and risky operations of the shadow fleet. The cost of being on the sanctioned list would be the loss of future earning potential of the tanker. Tankers closer to being scrapped would more likely choose the short-run premium over the future earning potential. The fleet transporting Russian oil could therefore end up consisting of even older, less safe tankers than today. Furthermore, the value of servicing the tankers would likely decrease, possibly reducing the quality and safety of the tankers further. While it is hard to ascertain the strength of these effects, by our judgment, it is likely small compared to the current situation and condition of the shadow fleet. The transport ban would not increase the amount of Russian oil shipped through European waters. The transport ban would, furthermore, provide another reason to monitor the movements and doings of tankers in European waters (on top of the current monitoring due to environmental risks and sabotage).
The EU today has a list of shadow tankers that are banned from European trade and services (EU Council, 2025). That is a good start, but the list is only partial. It has most likely missed a large share of vessels serving Russia using fraudulent paperwork. The proposed tanker ban would make the list longer and easier to administer. Prohibiting specific tankers from entering European ports and being involved in the European oil trade should be within the EU’s capacity. If secondary sanctions could be imposed consistently, that would give even larger effects, since the costs of breaking the sanction would increase further. That is where coordination with the US would be particularly impactful, as OFAC has a much better capacity for such measures. This said, given the current geopolitical situation, there are strong reasons for the EU to build up its own capacity for secondary sanctions.
While the proposed transport ban would simplify the monitoring compared to the price cap, there could still be potential for evasion. Monitoring whether a tanker has been in a western Russian port should be feasible, but following its movements all the way to the destination may not be. Potentially, Russia could then partly evade the sanctions using ship-to-ship transfers. Here, one tanker could transport the oil from Russia out of European waters, then transfer the oil to another tanker, which would transport the oil to the final destination. If the transfer is not detected, that second tanker could transport the Russian oil part of the way without facing sanctions. We cannot rule out that some such evasion could happen. But due to the risk of detection, the second tanker would also likely demand a higher premium, and Russian transport costs would still increase, albeit by somewhat less. Importantly, the EU should be able to detect and block these ship-to-ship transfers when they occur in European waters.
The US recently implemented sanctions on the two Russian oil companies Rosneft and Lukoil, by which anyone who does business with them is subject to secondary sanctions. In a sense, these US sanctions are similar to a transport ban, as they make it more difficult for Russia to export oil. In another sense, they are more of a complement to it. The US sanctions are targeted at specific firms, opening up for evasion by changing corporate structures and selling off assets, while the transport ban would be targeted at the physical tanker. It cannot be taken for granted that the US will uphold or keep its current sanctions, not least because they are intertwined with other motives (such as a trade war). It is, furthermore, not obvious that OFAC will have the capacity (or be allowed) to sanction entities within China and India. So, while the US sanction has touch points with the transport ban discussed here, the EU may need to construct its sanctioning regime independently.
In Summary
A transport ban implemented by the EU would serve the purpose of its economic warfare and has the potential to fill a gap in the current sanctions regime that has been opened by the eroding efficiency of the price cap. A transport ban would increase Russia’s oil-transport costs with low risks of oil-supply disruptions and price spikes. The requirements of monitoring for upholding a transport ban are much lower than for the price cap. The transport ban is not entirely immune to evasion, but the problems are likely small and would only partially reduce the effect of the sanction. The main concern is the environmental risks, but the sanction is unlikely to meaningfully increase the risks already posed by the current shadow fleet built up in response to the price cap. It is also feasible to implement a transport ban by the EU on its own, although the effect will increase if the sanctioning coalition is enlarged.
References
- Babina, T., Hilgenstock, B., Itskhoki, O., Mironov, M., & Ribakova, E. (2023). Assessing the Impact of International Sanctions on Russian Oil Exports (SSRN Scholarly Paper No. 4366337).
- Cardoso, D., Daubanes, J., & Salant, S. W. (2024). The dynamics of evasion: The price cap on Russian crude exports and amassing of the shadow fleet, mimeo
- CREA. (2025). Tracking the impacts of G7 & EU’s sanctions on Russian oil. Centre for Research on Energy and Clean Air.
- EU Council. (2025). Council Regulation (EU) 2025/2033 of 23 October 2025 amending Regulation (EU) No 833/2014 concerning restrictive measures in view of Russia’s actions destabilising the situation in Ukraine.
- Gars, J., Spiro, D., & Wachtmeister, H. (2025). Winners and losers of a Russian oil-export restriction. Public Choice.
- Hilgenstock, B., Ribakova, E., Shapoval, N., Babina, T., Itskhoki, O., & Mironov, M. (2023). Russian Oil Exports Under International Sanctions. SSRN Electronic Journal.
- Johnson, S., Rachel, L., & Wolfram, C. (2023). Design and implementation of the price cap on Russian oil exports. Journal of Comparative Economics, 51(4), 1244–1252.
- Kilian, L., Rapson, D., & Schipper, B. C. (2024). The Impact of the 2022 Oil Embargo and Price Cap on Russian Oil Prices (SSRN Scholarly Paper No. 4781029).
- Snidal, D. (1991). Relative Gains and the Pattern of International Cooperation. American Political Science Review, 85(3), 701–726.
- Spiro, D. (2023). Economic Warfare (SSRN Scholarly Paper No. 4445359).
- Spiro, D., Wachtmeister, H., & Gars, J. (2025). Assessing the impacts of oil sanctions on Russia. Energy Policy, 206, 114739.
- The Maritime Executive. (2025). Sanctions Have Not Slowed the Growth of the Shadow Fleet. The Maritime Executive.
- Turner, D. C., & Sappington, D. E. M. (2024). On the design of price caps as sanctions. International Journal of Industrial Organization, 97, 103099.
- Wachtmeister, H., Gars, J., & Spiro, D. (2022). Quantity restrictions and price discounts on Russian oil (No. arXiv:2212.00674). arXiv.
- Wu, Y. (1952). Economic Warfare. Prentice-Hall.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Russia Budget Deficit Surges as Oil Revenues Fall
Russia’s public finances are under strain as oil and gas revenues slide. The budget deficit of Russia has ballooned in 2025, while spending keeps rising. Buffers like the National Welfare Fund are shrinking, and growth is stalling. These findings come from the KSE Institute’s August 2025 Russia Chartbook by Benjamin Hilgenstock, Yuliia Pavytska, and Matvii Talalaievskyi.
What’s Driving the Gap: Context Behind the Numbers
Russia’s oil export earnings rose to $14.3 billion in July, supported by slightly higher global oil prices that kept Russian export prices near $60 per barrel. Still, the global oil market outlook points to lower prices for Russian exports through the rest of this year and into the first half of 2026. As a result, budgetary pressures are expected to persist. While oil and gas revenues increased in July compared to June due to quarterly tax payments, they were more than 30% lower in May–July than during the same period last year. Extraction tax receipts remain very weak and are unlikely to recover soon.
Challenging Outlook for Russian Oil and Gas Exports
Sanctions are increasingly squeezing Russia’s ability to move oil abroad. The number of sanctioned shadow tankers has climbed to 535, with 124 of them directly listed by the EU, UK, and US. This means that nearly two-thirds of the shadow fleet is now under sanctions, raising pressure on Moscow’s export routes.
Stronger enforcement will be key, as gaps still allow some shipments to move despite restrictions. In July, the shadow fleet’s share in Russian oil exports rose slightly, likely helped by higher global prices. This suggests that Russia is leaning even more on risky channels to keep its oil flowing, leaving its energy revenues vulnerable to tighter controls in the months ahead.
Russian Budget Deficit Deepens as Revenues Fall
Russia’s public finances came under heavy strain in July. The monthly budget deficit soared to 1.5 trillion rubles, driven by weak oil and gas revenues combined with surging expenditures.
This pushed the cumulative shortfall for January–July 2025 to 4.9 trillion rubles, a sharp increase from just 1.1 trillion during the same period in 2024. Alarmingly, the deficit has already reached 129% of the full-year target set after the most recent budget revision.
The rapid deterioration highlights how falling energy revenues and rising spending are creating mounting fiscal risks for Moscow.
Key Research Findings
- Oil and gas revenues fell 19% year over year, while expenditures jumped 21%, driving the Russian budget deficit wider.
- The liquid part of the National Welfare Fund is about 4.0 trillion rubles and could be used up within 6–12 months.
- Domestic debt issuance (OFZ) reached 3.0 trillion rubles in Jan–Jul, with falling yields showing strong bank demand.
- Growth slowed to 1.1% year over year in Q2, signaling a stalling economy; inflation eased to 8.8% while the policy rate stands at 18%.
What it Means: Risks and Next Steps
If oil prices drift toward $60 Brent into 2026, budget pressure will persist. The state may lean more on domestic borrowing and the National Welfare Fund, raising financial stability risks as buffers thin. With limited labor and capital, output has little room to grow, and policy goals clash: restrain prices or fund spending. Further monitoring of the Russian budget deficit and oil price trends is essential.
Meet The Researchers
- Benjamin Hilgenstock — KSE Institute.
- Yuliia Pavytska — KSE Institute.
- Matvii Talalaievskyi — KSE Institute.
Read The Full Report
Explore the full findings and detailed analysis by reading the complete report on the KSE Institute’s website. Additionally, you can view more policy briefs from the KSE Institute on the FREE Network’s website.
Explore Other Editions of KSE Institute’s Russia Chartbook
- KSE Institute’s Russia Chartbook – August 2025
- KSE Institute’s Russia Chartbook – July 2025
- KSE Institute’s Russia Chartbook – June 2025
- KSE Institute’s Russia Chartbook – May 2025
- KSE Institute’s Russia Chartbook – April 2025
- KSE Institute’s Russia Chartbook – March 2025
- KSE Institute’s Russia Chartbook – February 2025
- KSE Institute’s Russia Chartbook – January 2025
Russia’s Counter Sanctions: Forward to the Past!
Since February 2022, Russia has introduced a series of counter sanctions in response to the international sanctions introduced following the country’s full-scale invasion of Ukraine. These measures aimed to counteract external economic pressure while shielding the domestic economy from further destabilization. However, their broad implementation has led to mixed effects across various sectors while simultaneously increasing the administrative burden. This policy brief argues that Russia’s countersanctions reinforced state control over key industries, worsened market competition and fiscal sustainability, which contributed to a systematic move towards a planned economy.
Russia’s Counter Sanctions and the Expansion of State Control
Since February 2022, Russia has introduced a series of countersanctions in response to the international sanctions imposed following its invasion of Ukraine. A broad range of economic, financial, and trade restrictions have been implemented, including nationalization of foreign assets, price control, capital flow restrictions, export bans, and state-directed subsidies – all aimed at mitigating external economic pressure while reinforcing state control over key industries (Garant, 2025).
While it is widely accepted that, in times of crisis, governments may intervene in the economy to provide necessary support, such intervention should remain limited in scope and duration. Prolonged state involvement, particularly through subsidies and market controls, can distort price signals, crowd out private investment, and erode the foundations of competitive market dynamics (Friedman, 2020).
In the case of Russia, intensive government economic interventions, specifically after 2022, have led to mounting inefficiencies, increased inflationary pressures, and weakening long-term growth prospects (SITE, 2024; SITE, 2025). This policy brief discusses how the recent surge in presidential decrees, the sharp expansion of targeted subsidies across nearly all sectors, and the tightening of price regulations reflect the Kremlin’s strategic use of counter sanctions as a means of consolidating economic power and reinforcing centralized control.
An Expansion of Presidential Control
Since 2022, presidential decrees account for 25 percent of all anti-sanctions legislative measures, indicating a significant consolidation of executive control over economic policymaking. The trend of expanding presidential control through issued decrees is illustrated in Figure 1. As shown in the figure, the total number of presidential decrees has nearly doubled since 2019, amounting to 1131 in 2024. The largest share of this decree increase, however, occurred post February 2022.
Figure 1. Number of Presidential Decrees in Russia

Source: ConsultantPlus, 2025.
Beyond the expansion in the number of decrees, what is particularly noteworthy is the breadth of topics they cover. They range from significant interventions on nationalization and economic control to quite detailed low-impact orders.
Among the highly impactful presidential decrees, Decree No. 79 (February 28, 2022) should be mentioned. The decree introduced a mandate that Russian residents engaged in foreign economic activities sell 80 percent of their foreign currency earnings. Further, Decree No. 302 (April 25, 2023), allowed the Russian state to seize foreign assets from “unfriendly states” if necessary for national security or in retaliation for asset confiscations abroad. Global companies from Germany (Uniper), Finland (Fortum), France (Danone), and Denmark (Carlsberg) are among those affected by these expropriations (Garant, 2025). Seized foreign assets were transferred to state-controlled entities, which drastically reduced competition and increased inefficiencies within key Russian industries.
Similarly, Decree No. 416 (June 30, 2022) on the Nationalization of Sakhalin-2, transferred oil and gas projects from foreign operators (Shell, Mitsubishi and Mitsui) to a Russian-controlled legal entity. Moreover, foreign companies from “unfriendly” countries were required to sell their Russian assets at a minimum 50 percent discount when exiting the market. Additionally, they were obliged to pay a “voluntary contribution” to the Russian federal budget at 15 percent of asset value (Garant, 2025).
At the same time, numerous presidential decrees have been adopted to address very specific low-level administrative issues. While their economic impact has been quite limited, they have largely contributed to a growing micromanagement and regulatory complexity (for instance, Decree No. 982 (December 22, 2023) on Temporary State Control Over a Car Dealership, Decree No. 1096 (June 17, 2022) on Transport Credit Holidays etc.).
Apart from the potential negative effects of direct government intervention in the economy, there are several issues with Presidential Decrees. Most importantly, presidential decrees, unlike statutes or other forms of legislation, are not subject to parliamentary approval. Thus, they are bypassing legislative debate and accountability, which makes them less transparent and balanced. Presidential decrees serve as tools to avoid legislative resistance since the Russian judiciary rarely challenges presidential authority, meaning decrees are difficult to contest or reverse through legal means. Further, they often overlap with other legislation, thus duplicating the functions of other legislative (and executive) authorities, leading to regulatory uncertainty. This, in turn, undermines implementation and expands bureaucratic oversight, further increasing inefficiencies and costs (see for instance, Remington, 2014; Pertsev, 2025).
Altogether, the surge in presidential decrees in Russia contributes to increasing institutional instability, an increasing administrative burden and a centralization of power. However, the full impact of these measures on the macro level is yet to unfold.
Targeted Subsidies and Industry Dependence
A key tool in Russia’s counter sanctions strategy is the expansion of state subsidies. Since 2022, substantial subsidies have been directed toward the energy sector; industrial and technological development – including aviation, pharmaceuticals, electronics, and shipbuilding; agriculture and food security; transportation and infrastructure; the banking sector; housing; and consumer lending. The scale of these subsidies indicates growing imbalances and escalating fiscal risks in the Russian economy (Garant, 2025).
However, estimating the total resources going to subsidies is quite challenging. Precise subsidy figures are only explicitly stated in few legislative acts. Most legislative documents mention the form of subsidy without specifying the amount or the source of financing. Nevertheless, some estimates have been made by both Russian and Western experts.
For instance, Russia spent approximately 12 RUB trillion (126 USD billion) on fossil fuel subsidies in 2023 (Gerasimchuk et al., 2024). Subsidies to the agricultural sector were estimated at 1 trillion RUB between 2022 and 2024 (Statista, 2025). Since 2022, Russia has allocated approximately 1.09 trillion RUB (12 billion USD) in subsidies to the aviation sector to maintain operations (Stolyarov, 2023; Garant, 2025). Around 100 billion RUB were allocated to support the tourism industry during 2023–2024 (Ministry of Economic Development of the Russian Federation, 2024; Garant, 2025).
To understand the order of magnitude, it’s worth noting that, for instance, budget revenues from oil and gas amounted to 8.8 trillion RUB in 2023 and 11.1 trillion RUB in 2024 (Figure 2).
Figure 2. Budget revenues and expenditures

Source: SITE, 2025.
In addition, state subsidies for mortgages nearly doubled since 2022, with the total amount reaching 1.7 trillion RUB between 2022 and 2024 (CBR, 2024). Thus, the Russian mortgage market has become heavily dependent on state support, with subsidized mortgage programs accounting for nearly 70 percent of the growth in mortgage lending in early 2024 (CBR, 2024). Although the so-called standard preferential mortgage program was terminated on July 1, 2024, its discontinuation does not remove the substantial fiscal burden created by earlier subsidy schemes.
Moreover, the Russian government has expanded subsidized lending programs to support both businesses and individuals. For instance, preferential loans and credit holidays have been granted to small, medium and large enterprises (see for instance, Presidential Decree: No. 121, March 2022, Federal Law 08.03.2022 No. 46-FZ, and others (Garant, 2025)), further straining the government’s finances.
In many cases, subsidies allocated to state-owned enterprises double as a mechanism for off-budget military financing. For instance, defense-industrial conglomerates like Rostec not only receive targeted support but play also a pivotal role in facilitating military acquisitions and production activities outside of the formal federal budget framework (Kennedy, 2025). This not only obscures the true scale of budget expenditures but again increases the long-term fiscal burden.
As such, these measures have fostered a heavy reliance on state funding, resulting in the accelerated depletion of financial reserves and contributing to increased fiscal risks.
Price Controls, State Regulation and Planned Procurement
As mentioned earlier, the set of countermeasures recently implemented by Russia also indicates a shift toward a planned economy, with hallmark features such as price controls gradually re-emerging as policy tools. As in Belarus, where state-led economic management has long been the norm, the Russian government’s direct intervention in price-setting mechanisms, particularly for essential goods, erodes market signals.
Since 2022, a series of decrees have introduced price controls on essential goods and services to cushion households against rising costs amid inflation. These measures include caps on fare increases for public transportation, limits on tariffs for heating, water supply, and wastewater services; price limits on essential medicines, and staple agricultural products (Garant, 2025).
By limiting the price growth of necessities, these interventions aim to support households in the short term. However, prolonged price controls may entail distorted market signals, increased subsidies dependency for producers, and higher administrative costs for control enforcement.
The deviation from market mechanisms has been even more amplified in procurement, through Federal Law No. 272-FZ (July 14, 2022), which compels businesses to accept government contracts if they receive state subsidies or operate in strategic sectors. In practice, companies cannot refuse government contracts if their products or services are required for so-called counterterrorism and military operations abroad. Refusal to comply with procurement orders may result in criminal liability, as non-performance can be interpreted as economic sabotage under this law.
In addition, the Russian government provides up to 90 percent of procurement contracts in advance (Government Decree No. 505, March 29, 2022). This arrangement weakens the role of contracts, prices, and competition, while increasing the fiscal risks. In effect, it reinforces a central planning logic and undermines competitive procurement, where outcomes should be driven by performance and value rather than access to state funding.
With Russian companies cut off from foreign investment and other external financing due to sanctions, large-scale government support has become even more critical – intensifying dependence on state subsidies and, by extension, state control. The legal changes outlined above have turned procurement into a key instrument of political control over businesses. The scale of these subsidies is contributing to a damaging shift toward a centrally planned system, restricting competition and undermining long-term growth potential.
Fiscal Sustainability at Risk
The extensive use of subsidies, preferential loans, and government-backed financial interventions has placed an increasing burden on Russia’s fiscal system. While these measures were introduced to mitigate the effects of international sanctions, stabilize key industries and support households, they have led to significant structural imbalances, growing budget deficits, and rising financial risks.
State-subsidized loans have surged across multiple sectors, including construction, IT, housing, energy, infrastructure, and agriculture. The result has been a sharp increase in corporate and consumer debt, with unsecured consumer loans growing at an annual rate of 17 percent as of April 2024. Overdue debt on loans to individuals reached 1.34 trillion RUB by February 2025, signaling mounting financial distress for households despite the support measures (CBR, 2025).
The high concentration of corporate debt has further destabilized the financial system. By early 2024, the debt of the five largest companies accounted for 56 percent of the banking sector’s capital, indicating systemic vulnerabilities (CBR, 2025). In addition, the government has implemented new policies that exacerbate the risks connected to state interventions in banking operations. For instance, in March 2022, it introduced a moratorium on bankruptcy proceedings, effectively delaying the official declaration of businesses as insolvent or financially distressed. At the same time, the Central Bank required commercial banks to restructure loans rather than classify them as defaults – masking financial distress and exacerbating long-term risks to the banking sector (Garant, 2025).
Moreover, a growing share of Russia’s war-related spending now flows through off-budget channels – such as state-owned enterprises and regional programs – rather than the federal budget. According to a recent analysis, as much as one-third of military and strategic expenditures bypass formal budget reporting altogether (Kennedy, 2025).
These hidden expenditures distort the actual fiscal position, reduce transparency, and increase the long-term burden on the public sector by masking the true scale of liabilities – raising further questions about the sustainability and accountability of Russia’s fiscal policy.
Conclusions
Since February 2022, Russia’s counter-sanctions measures have markedly shifted its economic governance toward greater state control and elements reminiscent of Soviet-era central planning. Large-scale subsidies, administrative pricing, and deep state involvement in production and procurement have suppressed market competition and efficiency. These interventions have distorted incentives and curtailed the role of market signals, contributing to growing inefficiency across key sectors.
Looking ahead, the long-term economic outlook for Russia is increasingly negative. While the counter-sanctions measures may have softened the initial blow of international sanctions, they have entrenched structural vulnerabilities, reduced fiscal flexibility, and amplified systemic risks, particularly in the financial and real estate sectors. Moreover, by undermining innovation and productivity, Russia’s counter sanctions are accelerating its trajectory toward deeper economic isolation and a centrally managed model, with severe implications for sustainable growth.
References
- Central Bank of Russia (CBR). (2024). Mortgage lending market statistics. https://www.cbr.ru/statistics/bank_sector/mortgage/mortgage_lending_market/
- Central Bank of Russia (CBR). (2025). https://www.cbr.ru/statistics/
- ConsultantPlus. (2025). https://www.consultant.ru/
- Friedman, M. (2020). Capitalism and freedom (40th anniversary ed.). University of Chicago Press.
(Original work published 1962). 272 p. - Garant. (2025). Anti-sanction measures 2022-2025 (special economic measures and measures aimed at supporting businesses and citizens) (in Russian). https://base.garant.ru/57750630/
- Gerasimchuk, I., Laan, T., Do, N., Darby, M., & Jones, N. (2024). The cost of fossil fuel reliance: Governments provided USD 1.5 trillion from public coffers in 2023. International Institute for Sustainable Development (IISD). https://www.iisd.org/articles/insight/cost-fossil-fuel-reliance-governments-provided-15-trillion-2023
- Kennedy, C. (2025). Russia’s hidden war debt: Full report. Navigating Russia. Retrieved March 5, 2025 from https://navigatingrussia.substack.com/p/russias-hidden-war-debt-full-report
- McFaul, M. (2021). Russia’s road to autocracy. Journal of Democracy, 32(4), 11–26. https://www.journalofdemocracy.org/articles/russias-road-to-autocracy/
- Ministry of Economic Development of the Russian Federation. (2024). About 100 billion rubles have been allocated for the national project Tourism and Hospitality Industry in 2023–2024. https://en.economy.gov.ru/material/news/about_100_billion_rubles_have_been_allocated_for_the_national_project_tourism_and_hospitality_industry_in_2023_2024.html
- Pertsev, A. (2025). Auditing the auditors: Does Putin trust anyone now? Carnegie Endowment for International Peace. https://carnegieendowment.org/russia-eurasia/politika/2025/03/russia-putin-elites-control?lang=en
- Remington, T. F. (2014). Presidential decrees in Russia: A comparative perspective. Cambridge University Press.
- Statista. (2025). Annual value of subsidies in the agricultural industry in Russia from 2015 to 2025. https://www.statista.com/statistics/1064082/russia-agricultural-subsidies/
- Stolyarov, G. (2023, December 21). Russia splashes $12 billion to keep aviation sector in the air. Reuters. https://www.reuters.com/business/aerospace-defense/russia-splashes-12-bln-keep-aviation-sector-air-2023-12-21/
- Stockholm Institute of Transition Economics (SITE). (2024). The Russian economy in the fog of war. https://www.hhs.se/en/about-us/news/site-publications/2024/russias-economic-imbalances/
- Stockholm Institute of Transition Economics (SITE). (2025). Financing The Russian War Economy. https://www.hhs.se/contentassets/2ca16d102eed4a1c8ff24b59c9db7c25/site-russian-economy-spring-2025-update.pdf
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.
Russia’s Car Fleet Dynamics – and Why They Matter
Russia’s car imports have evolved dramatically since its full-scale invasion of Ukraine in February 2022. The invasion and subsequent sanctions have led to a shift away from mainly Western car imports to domestically produced cars, and especially Chinese cars, both of which entail quality concerns. Despite state-sponsored loan relief, the heightened inflation pressures in Russia and increased financial burden on households is catching up to the car market – in the first quarter of 2025, the sales of new cars decreased by 25 percent compared to 2024. This policy brief uses the developments in the Russian primary car market as a lens to examine the spending power of Russian households and highlight the limitations of state interventions under sanctions and inflationary pressure.
From Western Dominance to Domestic Car Sales
Prior to February 2022, imports of American, European, South Korean and Japanese (hereafter called western) cars stood for about 60 percent of all new car sales in Russia. Domestic production took up most of the remaining 40 percent market share (SITE, 2024). In 2023, the number of western car sales was almost zero as most of these automotive firms exited the Russian market following the country’s war on Ukraine. Collaborations between European and Russian automotive companies, such as between Renault and Autovaz, as well as production of western cars in Russia, were also largely abolished. The mass exodus severely impacted the production levels in the Russian automotive industry; in 2021 around 1 350 000 cars were produced in Russia, dropping to around 450 000 in 2022, and increasing to only about 750 000 cars in 2024. However, the sales of new Russian cars fell in the immediate months following the invasion and subsequent sanctions but managed to bounce back to initial levels in 2023 (Figure 1).
Figure 1. New car sales in Russia

Source: Association of European Businesses. Note: Detailed data for 2024 and 2025 is unavailable.
Russia’s Car Dynamics: The Chinese Import Surge
While the sale of Russian cars rebounded following the invasion, the key market player post-2022 is China. As illustrated in Figure 1, in 2023, the sales of newly produced Chinese cars in Russia were eight times the 2020 figures.
Although the imports of Chinese cars made up for a large part of the massive withdrawals of western cars post-invasion, new issues have arisen. Chinese cars are considered unfit for Russian weather conditions, and spare parts are also considered to be of low quality. Additionally, Chinese cars are reported to survive shorter total mileages (about half, compared to many western brands), and to have poor electronic and ergonomic systems. Still, prices for a Chinese car are generally higher than for a Russian car, mostly due to taxes and import tariffs. To dampen the recent Chinese expansion on the car market (in 2025 accounting for 63 percent of the market), Russia in March 2025, hiked the import tax on Chinese cars from nearly $6000 to $7500. Furthermore, the price of Chinese cars is expected to increase in 2025, following a depreciation of the ruble against the yuan.
High Prices, Large Loans
Not only have Chinese cars met criticism when it comes to quality and price. In summer 2022, Autovaz declared that the 22 model of the classic Lada Granta would be void of air bags, an ABS braking system, and a brake assist system, due to a scarcity of imported components. A subset of the model has since been equipped with a driver-seat air bag. Despite such major shortcomings, prices for new Russian-made cars have increased by 67 percent since the onset of the war. These price increases are mirrored on the secondary market where the price for a used foreign car have increased by 60 percent since 2022.
Another feature of the Russia automotive market concerns the large increase in automobile loans granted to businesses and entrepreneurs over the last four years (Figure 2).
Figure 2. Volume of companies’ automobile loans

Source: Rosstat.
While the near doubling in the loan value for companies’ car loans seems large, its growth is small compared to that for individuals. Since the onset of the war, the volume of private car loans has grown more than fivefold. This increase is arguably spurred by the preferential loans scheme for the purchase of new cars, introduced mid-July 2022 and granted to Russians with at least one child under 18, new car owners, people employed within health and education, military personnel and their close relatives, and disabled people. The so-called loan (projected to be in place up until 2027) applies to car purchases in Russia of a maximum 2 million ruble and discounts the price by 20 percent (25 percent for cars sold in the Far East Region). Under this scheme, car loans constituted almost 6 percent of all consumer loans in mid-2024, a sixfold increase in just a year (see Figure 3). This trend has not waned off since 2024. In December 2023, 70 percent of all cars bought in Russia were financed by borrowed funds. The size of an average car loan also grew substantially, around 20 percent, between 2022 and 2023. At the same time, the share of risky borrowers increased. In October 2024, 60 percent of the borrowers had a Debt Service-To-Income (DSTI) Ratio of over 50 percent, indicating that a large segment of car buyers will potentially be unable to repay the debt (CBR, 2024).
Figure 3. Private Automobile Loans

Source: CBR (2024). Note: Figure based on approximation from CBR figure.
Household Strains and Financial Risks
Over the last five years gasoline prices have gone up by about 17 percent (standard petrol), alongside substantial price increases for nearly all major consumption goods in Russia – driven by the rampant inflation. In fact, the price of the Russian consumer basket nearly doubled between February 2022 and August 2024. Progressive income taxes have been introduced for about 3.2 percent of the working population – increasing taxation from 13 percent up to 22 percent. Furthermore, in July 2024, the subsidized mortgages for newly built apartments were scrapped such that all buyers now face a 16-20 percent rate (SITE, 2025). While real wages did increase by 8 to 9 percent in 2023 and 2024, real pensions did not. Furthermore, reported inflation figures are likely severely understated, with actual inflation being around 20, rather than the reported 9.5 percent. If so, the actual real wage growth would be about 0 percent (SITE, 2025).
This undermines the spending power of Russian households, which is now being reflected on the primary car market. There has been a sharp drop in car sales – 25 percent in the first quarter in 2025, and car prices are also on the decline. This, combined with the growing reliance on credit, signals that many consumers are no longer able to make large purchases despite the state driven support scheme – pointing to major affordability issues. Given that the preferential loans scheme will be in place only up until 2027 and that Chinese cars will likely become more expensive, demand may dwindle even further in the years to come. In such situation, the government could be forced to expand their preferential scheme to artificially keep up demand levels, taking on greater financial risks and associated costs. They may also increasingly close off the inflow of Chinese cars, which leave consumers with no options outside of domestically produced cars.
The falling demand for cars may also be considered an indicator of household’s beliefs about the economic conditions to come. That is, the demand for cars could be a signal of consumers understanding that the economy is, or will shortly be in a recession (Attanasio, Larkin, Ravn and Padula, 2022). While the Russian war time economy is not currently displaying recession signs, its persistent issues with rampant inflation, rapidly growing household mortgages and changes in the credit to GDP ratio signals its financial stability is at risk. As discussed in the report “Financing the Russian War Economy”, these are key indicators correlated with banking crises (SITE, 2025). If declining demand for cars is a sign of consumers perceiving the economy as increasingly fragile, this perception could amplify existing vulnerabilities.
Conclusion
The automotive sector offers comparatively timely data, making it a useful window for assessing the financial situation of Russian households. In the current automotive landscape in Russia, buying a new car is becoming increasingly expensive. This has forced not only private buyers but also businesses to increasingly take up loans to cover the payment of a new car – often despite reduced quality and limited choice. The demand for new cars is partly driven by state intervention, particularly the preferential loan scheme. This not only places a growing financial burden on the state but also carries rising risks of borrowers defaulting. At the same time, the current trends in the sector illustrate the growing limitations of both import substitution and state-backed credit schemes as tools for maintaining consumer demand. The recent drop in new car sales, despite state support, may reflect a growing reluctance among households to make large purchases, exposing how Russian households’ purchasing power is eroding in the Russian wartime economy. Importantly, this drop may point not only to affordability issues but also to a broader perception that the financial system is increasingly unstable.
Overall, Russia’s car dynamics suggest that the Russian economy is not performing as well as officially claimed, adding support for the effectiveness of sanctions and company withdrawals from the Russian market.
References
- Attanasio, O., Larkin, K., Ravn, M. O., & Padula, M. (2022). “(S)Cars and the Great Recession”. Econometrica, 90(5), 2319–2356.
- The Central Bank of Russia (CBR). (2024). “Financial Stability Review No. 2. Q2-Q3, 2024”.
- Stockholm Institute of Transition Economics (SITE). (2024). “The Russian Economy in the Fog of War”.
- Stockholm Institute of Transition Economics (SITE). (2025). “Financing the Russian War Economy”.
Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.