Author: ln

U.S. Sanctions on Rosneft and Lukoil: Pressure on Moscow, Strains on Europe

Posted on December 8, 2025 | Policy Brief

The U.S. sanctions on two Russian oil giants, Rosneft and Lukoil, came into effect on Nov 21, 2025. These sanctions affect not only companies per se but also their counterparties worldwide under the secondary sanctions clause. For the EU, these sanctions highlight a central trade-off: how to exert real pressure on Russia without fracturing political alignment among EU Member States. This brief discusses the consequences of the sanctions, including their immediate impact on the firms and Russia’s budget, the new tensions exposed in Europe’s energy policy, and the broader lessons for the next generation of EU sanctions tools.

The Threat of Secondary Sanctions

On 22 October 2025, the United States imposed sanctions on Russia’s two largest oil companies, Rosneft and Lukoil. At the time, the measures appeared symbolically significant: they were the first sanctions package introduced by the new Trump administration and were coordinated with the EU’s 19th sanctions package, giving the impression of renewed transatlantic alignment after a long period of fragmentation and uncertainty. The announcement reportedly caught Mr Putin off guard. This reaction highlights how unexpected the measures were, given President Trump’s rhetoric and the geopolitical positioning many observers had anticipated he would adopt.

Although, in retrospect, that initial sense of alignment appears more fragile, given other political developments during November, the sanctions that formally came into effect once the wind-down period ended on 21 November are likely to be consequential, both for the target companies and for the Russian federal budget. To understand this impact, it is essential to look at how U.S. sanctions operate in practice, especially the leverage created by secondary sanctions.

When the U.S. Treasury’s Office of Foreign Assets Control (OFAC) designates an entity for sanctions, it warns that any financial institution dealing with that entity may itself become exposed to penalties. In particular, OFAC notes that foreign banks engaging in significant transactions for a sanctioned person risk the imposition of so-called secondary sanctions. In practical terms, OFAC can bar such a bank from accessing the U.S. financial system if it knowingly carries out, or helps carry out, a transaction for someone under U.S. sanctions. Losing this access means losing the ability to use U.S. dollar accounts and payment channels.

This is precisely why OFAC’s sanctions are so widely feared: almost every dollar transaction in the world ultimately passes through a U.S. correspondent bank. Even two foreign banks trading dollars in Asia or Africa must clear their payments through the United States. If OFAC cuts a bank off from that system, it is effectively locked out of the dollar economy, and in the global economy, losing access to dollars is like losing access to oxygen.

The power of secondary sanctions becomes visible in how different actors react to the risk. Swiss trader Gunvor abruptly withdrew, and later publicly denied, its bid to acquire Lukoil’s international business once the sanctions exposure became apparent. In Bulgaria, the government moved to take control of Lukoil’s Burgas refinery because, once sanctions took effect, counterparties were likely to refuse payments to a sanctioned entity, forcing the refinery to shut down. This temporary state takeover has been tacitly tolerated so far, as it was deemed necessary to maintain Bulgaria’s fuel security. The same logic drove Viktor Orbán to rush to Washington to secure guarantees for Hungary’s fuel supplies, resulting in a one-year exemption from U.S. measures. In short, the threat of secondary sanctions is real and shapes major commercial and political decisions alike.

Economic Implications for the Targets

Given the far-reaching implications of OFAC sanctions, the economic impacts are potentially significant. Following the announcement in October, financial markets reacted immediately. Lukoil’s share price fell by around 9.4 percent, while Rosneft’s declined by approximately 7 percent. This asymmetry reflects the companies’ different exposure profiles. Lukoil, as a more private and internationally exposed firm, is significantly more vulnerable than Rosneft, whose operations are more domestically anchored and politically protected.

The sanctions raise the prospect of forced divestments of Lukoil’s foreign assets, likely at significantly reduced valuations due to the limited pool of potential buyers willing to engage with sanctioned entities. Even when divestment is not formally mandated, the measures can make it effectively impossible for the companies to repatriate dividends from their overseas holdings, as financial intermediaries are unlikely to process payments involving sanctioned actors. This constitutes an immediate loss of income, besides the longer-term loss of strategic presence in Europe.

Figure 1. Map of Lukoil’s foreign assets

Source: Bloomberg. The map includes the headquarters of the international marketing and trading arm, LITASCO SA, based in Geneva.

Operationally, both firms face higher costs and greater frictions. Sanctions increase the risk for suppliers, banks, insurers, and logistics partners, who now must factor in secondary sanctions exposure when doing business with Lukoil or Rosneft. This narrows the pool of potential counterparties and scares away buyers.

These dynamics are already visible in the adjustment patterns of major international buyers of Russian oil, notably India and China. There, the adjustment is expected to be sharper for India than for China. This is because India is more dependent on the dollar, given the rupee’s status, while trade with Russia is not as diversified to allow for barter-like arrangements (as Russia reportedly resorted to with China). Several major Indian refiners reportedly began planning to halt or scale back purchases of Russian crude. However, the grace period allowed India to stock up: according to tracking firm Kpler, India’s Russian oil imports reached 1.855 million barrels per day (bpd) in November, a five-month high, reflecting a rush to secure barrels ahead of the sanctions deadline. But for December, the same sources project a drop to 600,000–650,000 bpd, a three-year low in Russian oil shipments to India.

About 40-45 percent of China’s oil imports from Russia are also affected by these sanctions, and Chinese buyers, especially the smaller independent refiners but even some state-owned ones, are being more careful.

By and large, though, export volumes are unlikely to decline significantly in the near term, given the extensive circumvention networks and practices already in place. Nevertheless, financial effects are increasingly visible, not least due to another effect of the sanctions – buyers being able to extract deeper discounts, further compressing Russia’s earnings. There are already multiple reports of Urals trading at its steepest discount in a year, sometimes several dollars per barrel below Brent. The discount widened from USD11–12/bbl (before Oct 22 sanctions) to USD19–20/bbl by early November, and reportedly as wide as USD20–23.5/bbl by mid-November.

Figure 2. Urals–Brent discount, widening after sanctions.

Source: TradingEconomics.com.

 

According to CREA’s fossil fuel tracker for October 2025, “Russia’s monthly fossil fuel export revenues saw a 4 percent month-on-month decline to EUR 524 million (mn) per day — the lowest they have been since the full-scale invasion of Ukraine.” This corresponds to a 15 percent year-on-year drop in fossil fuel export revenues and resulted in a 26 percent year-on-year drop in tax revenues from oil and gas exports.

Over the medium to long term, these commercial pressures may accumulate and become consequential. Higher operating costs and lower revenues mean that both companies will have less capital available for investment. Because Russia’s upstream sector is both capital-intensive and dominated by Rosneft and Lukoil, with limited scope for independent or foreign producers to expand under current political and sanctions constraints, any sustained under-investment by these two companies is unlikely to be compensated by market reorganization. This raises the risk of faster production declines and a longer-term weakening of the entire industry.

Implications for the Russian State Budget

Lukoil and Rosneft are the two largest taxpayers in Russia, contributing through a broad range of fiscal streams and payments associated with state-owned infrastructure. In Rosneft’s case, where the state holds a majority stake, dividends are also a source of federal revenue. Any reduction in company profitability, therefore, translates directly into lower tax payments and smaller dividends.

Sanctions-driven increases in shipping, insurance, and compliance costs will further compress margins and reduce the tax base. The loss of foreign assets, or their sale at distressed prices, diminishes both current profit tax liabilities and future dividend streams.

Some taxes, such as the mineral extraction tax (MET), are based on production volumes rather than profitability, which reduces the immediate fiscal impact. But as profitability declines, and especially if the sector’s investment levels fall, the medium-term fiscal losses become more substantial as reduced investment ultimately erodes production volumes.

All in all, Rosneft and Lukoil together produce between 40 and 50 percent of the national oil output. Although the share of oil and gas revenues in the federal budget has decreased from the historical 35–40 percent to 25-30 percent, the potential fiscal impact remains substantial. According to Reuters, projected oil revenues for the current month are roughly 35 percent lower than in the same month of 2024, marking the weakest level in two and a half years.

Uneven Burden-sharing in the EU

These sanctions also carry costs for the EU itself. Their impact is felt unevenly across Member States, largely reflecting differences in pre-war dependence on Russian oil and gas. This is why EU sanctions on Russian energy have consistently included exceptions for highly dependent Member States in Central Europe, notably Hungary and Slovakia (and, before, Czechia). The Council explicitly acknowledged these exemptions were justified on the grounds of security of supply and fairness, recognizing that certain countries faced structural reliance on Russian oil and lacked immediate alternatives (Council Decision (EU) 2022/879 and the EU’s 6th package). At the same time, the financial significance of these exemptions for the EU’s pressure on Russia is very limited. According to CREA’s data for October 2025, Hungary purchased EUR 258 million of Russian fossil fuels that month and Slovakia EUR 210 million. This constitutes less than 4% of Russia’s global fossil-fuel export revenues for that month.

However, these exemptions produced asymmetric outcomes within the EU, complicating EU unity. Countries that retained access to Russian crude, typically priced below global benchmarks and substantially cheaper than LNG-based alternatives, effectively enjoyed a cost advantage over Member States that had already diversified or lost access to Russian supplies. They have avoided abrupt supply disruptions but also benefited from lower-cost inputs, while others absorbed higher market prices and the capital expenditure needed to secure alternative supply chains (including LNG terminals, new interconnectors, or upgrades to refineries).

The sanctions on Rosneft, Lukoil, and their EU subsidiaries offer a good example of how uneven the impact of energy measures can be across Member States. Rosneft holds significant shares in three German refineries, together accounting for around 12 percent of Germany’s refining capacity, but these assets have been under German state trusteeship since 2022 — meaning that Rosneft is still the legal owner, yet it no longer controls day-to-day operations. Lukoil, by contrast, directly owns major refineries in Bulgaria (Neftochim Burgas) and Romania (Petrotel Ploiești), and has a large stake in a Dutch refinery. For years, the countries hosting these assets benefited from cheaper Russian crude and gasoline, slower pressure to diversify, and more lenient implementation of EU sanctions.

As sanctions tighten and divestment of Russian-owned assets in Europe becomes unavoidable, these states now face higher prices and costly adjustments. In this sense, the current phase can be seen as a rebalancing act: the advantages these countries once enjoyed are gradually diminishing as their energy prices converge with those of other member states. At the same time, their exposure to supply disruptions may even be increasing, given the lack of earlier investment in diversifying their energy import sources.

But the politics remain contentious. Hungary’s push for renewed derogations and Slovakia’s threat in March 2025 to block EU support for Ukraine unless gas transit via Ukraine is reopened to Slovakia and Western Europe show how differing energy profiles still shape national positions on sanctions.

In the long term, however, solidarity cannot mean accepting the structurally uneven burden-sharing of sanctions costs. EU solidarity principles (reflected in the Treaties, the Clean Energy Package, and crisis-response mechanisms such as the 2022 gas solidarity regulation) imply that Member States should support one another to withstand shocks, not that some should bear permanent disadvantages. As highlighted in the energy-security literature, especially in the work of Le Coq and Paltseva (2009, 2012, 2022, or 2025), solidarity can be viewed as a mutual insurance mechanism that is most effective when tied to interconnection and diversification, enabling states with asymmetric exposure to external energy suppliers to cope with disruptions without undermining collective action.

Following this logic, solidarity should be understood as doing as much as possible to ensure that the Member States most exposed to Russian oil and gas are sufficiently integrated into the EU system—through stronger interconnections, diversified supply routes, and access to alternative sources—so that they can sustain tougher sanctions without requiring permanent derogations. The EU’s challenge, therefore, is to ensure a more even sharing of the sanctions’ burden, preventing any Member State from systematically free-riding by shifting the costs of sanctioning Russia (or other common policies) onto others, while preserving political cohesion.

Conclusion

The analysis of this episode carries important implications for EU policy.

First, it underscores both the strategic potential and the political limits of secondary sanctions as a policy tool. Legally, the EU’s treaties constrain extraterritorial action and anchor the Union in a territorial understanding of jurisdiction; furthermore, this take is consistent with the EU’s long-standing identity as a regulatory—rather than coercive—power. Practically, the Union lacks the federal-level enforcement structures needed to police foreign actors across jurisdictions. Politically, the use of secondary sanctions remains divisive: they raise concerns about infringing third countries’ sovereignty, provoking retaliation against EU trade, constraining diplomatic flexibility, and straining relations with key partners in the Global South. Member States’ exposure to international trade and to specific partners such as China, India, Türkiye, and the Gulf varies widely, making consensus difficult. At the same time, EU firms are deeply embedded in global supply chains, and the euro lacks the dollar’s reach, increasing the risk that aggressive measures, such as secondary sanctions, could accelerate de-euroization.

Within these constraints, the EU has opted for more limited, quasi-extraterritorial tools—most notably the “no-Russia clause”, which requires that EU exporters include a contractual ban on re-exporting their goods to Russia —to approximate the effects of secondary sanctions without formally adopting them. This calibrated approach has so far allowed the Union to signal resolve while limiting geopolitical and economic risks. But as U.S. secondary sanctions increasingly shape global trade patterns in ways that affect the EU, the question of whether this strategy remains sufficient is becoming harder to avoid.

Second, the episode highlights the need to make burden-sharing within common EU policies, including sanctions, more transparent and more equitable. Derogations for highly exposed Member States were justified in the short run on security-of-supply grounds, but their continuation produced persistent asymmetries in costs and benefits across the Union. These disparities have shaped national positions on sanctions, complicated collective decision-making, and, in some cases, been leveraged as political bargaining tools. As sanctions become a more permanent feature of the EU’s external action, clearer mechanisms will be needed to ensure that no Member State can systematically shift the economic or political costs of common measures onto others. This may involve revisiting the design of derogations, considering compensatory financial instruments, or more closely integrating sanctions policy with energy, industrial, and fiscal planning.

Ultimately, the credibility of the EU’s sanctions strategy will depend on its ability to align legal constraints, geopolitical ambition, and fair burden-sharing into a single, coherent framework.

References

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.

Humanitarian Demining and Ukraine’s Recovery: Lessons Yet to Learn

Posted on December 1, 2025 | Policy Brief

This policy brief examines how land mine action underpins Ukraine’s reconstruction and economic renewal. It outlines the current scale of contamination and the national humanitarian demining strategy. The brief also reviews international experience from countries around the world, discussing the economic recovery driven by demining and the economic efficiency of mine action. It documents significant variation in direct mine action costs across countries and contexts, complicating the assessment of these costs in the case of Ukraine. The brief also discusses the indirect costs arising from systemic inefficiencies in Ukraine’s demining effort, including fragmented governance, shortages of qualified personnel, outdated standards, and security constraints. It concludes that Ukraine’s success in transforming demining into a catalyst for recovery depends on effective coordination, data-driven planning, gender inclusion, and the adoption of best international practices.

Understanding the Scale and Current Need for Humanitarian Demining in Ukraine

As of mid-2025, approximately 137,000 km² of Ukrainian land remains potentially contaminated by mines and unexploded ordnance (UXO). While this is a reduction from 174,000 km² at the end of 2022, Ukraine remains one of the most mine-contaminated countries in the world (Ministry of Economy of Ukraine, 2023; UDA, 2025).

The problem of demining is multidimensional, encompassing both humanitarian and economic consequences. More than six million people currently live in at-risk areas, and the number of mine incidents has already exceeded one thousand. Without addressing the problem, the number of victims could rise to more than 9,000 by 2030 (Ministry of Economy of Ukraine, 2023). Contamination affects some of the world’s most fertile agricultural regions, as well as energy, transport, and residential zones.

The funding needs are substantial. According to UNDP (2024), Ukraine’s total demining bill could reach USD 34–35 billion, requiring tens of thousands of trained specialists. As of early 2025, Ukraine has more than 4,500 sappers and deminers, but this number remains far below national needs. Experts emphasize that the workforce must increase significantly to ensure the timely clearance of contaminated territories. At present, approximately 87 mine-action operators are active in Ukraine, encompassing government bodies, private companies, humanitarian organizations, and international partners (UN Women Ukraine, 2025).

At the same time, the potential economic benefits of demining are immense. According to the TBI (2024) estimates, Ukraine loses about USD 11.2 billion each year (compared to 2021) due to mine contamination. Frontline regions such as Kharkiv, Mykolaiv, Sumy, and Chernihiv are particularly exposed, experiencing a reduction in exports of USD 8.9 billion and a loss of regional tax revenues of USD 1.1 billion annually.

In addressing the problem, the government has recently adopted a National Mine Action Strategy until 2033, which aims to clear about 80% of the de-occupied territories within 10 years (Ministry of Economy of Ukraine, 2024). However, this ambitious plan faces serious systemic challenges, including the dispersion of power among government agencies, insufficient and inconsistent funding, and delays in public procurement and tender processes (UDA, 2025). Thus, humanitarian demining stands at the crossroads of Ukraine’s security and economic recovery, affecting how quickly the country can restore farmland, rebuild infrastructure, and attract investment. Its success depends on efficient resource use, data-driven planning, and the adoption of proven international practices. The following sections examine global experience and economic efficiency in mine action, as well as the key challenges Ukraine must address to achieve tangible and sustainable recovery.

Evidence and Lessons from Global Experience

The problem of humanitarian demining is widespread globally, affecting dozens of post-conflict states across Africa, Asia, the Middle East, and Europe. Many of these countries, such as Afghanistan, Mozambique, Eritrea, Sudan, Sri Lanka, Bosnia and Herzegovina, and Croatia, have already undergone large-scale clearance operations and provide tangible evidence of how demining drives economic recovery and social stabilization.

In Afghanistan, humanitarian demining produced wide-ranging socio-economic benefits. It vastly improved mobility and access to resources and markets, served as a prerequisite for broader development initiatives, restored agricultural productivity and employment, and positively influenced mental health and community relations by reducing fear, enabling return, and rebuilding trust within affected populations (UNMAS, 2021).

In Mozambique, large-scale railway clearance reopened a key regional trade corridor, creating more than 400 jobs. The operation restored transport connectivity, enabled the renewal of coal exports, and stimulated agricultural and industrial recovery in the surrounding areas (Lundberg, 2006). In Eritrea, humanitarian demining enabled the return of more than 20,000 refugees within a year, which allowed about 29 villages to resume crop cultivation and schooling; casualty rates for both residents and livestock fell to zero, restoring local food security and rural incomes (Lundberg, 2006).

Sudan offers a contrasting case, where political and logistical barriers pushed costs to nearly USD 45 per m² (Bolton, 2008). Despite high costs, the reopened transport corridors and access to markets demonstrated substantial humanitarian and trade benefits, underscoring that elevated expenditure in complex terrains can still deliver strong socio-economic returns.

Post-war European experiences reinforce these findings. In Bosnia and Herzegovina, humanitarian demining has served as a foundation for sustainable socio-economic recovery, enabling the rebuilding of housing and infrastructure, reducing flood risks, restoring agricultural and forest productivity, improving access to water, and ensuring safe mobility essential for trade and community development (GICHD & UNDP, 2022). Similarly, mine clearance in Croatia has been pivotal to national recovery, restoring access to agricultural and forest land, enabling infrastructure and EU-funded development projects, and supporting tourism and investment in previously contaminated regions (Mine Action Review, 2021).

Collectively, these cases demonstrate that the economic dividends of demining are consistent across contexts. Clearing mines enables agricultural revival, facilitates transport and trade, lowers accident-related health costs, and strengthens confidence in governance. However, incomplete data and fragmented decision-making might delay land release and inflate costs.

For Ukraine, where contamination covers more than 137,000 km² of high-value farmland and industrial zones, these global lessons confirm that mine action must be integrated as a central pillar of the reconstruction process.

Measuring the Economic Efficiency of Humanitarian Demining: Indicators and Limitations

The Geneva International Centre for Humanitarian Demining, in its recent report, defines efficiency in demining as “a measure of how economically resources or inputs are converted to results” (GICHD, 2023, p. 6). In humanitarian demining, this means achieving the maximum area of land safely released or the largest number of explosive items cleared using the least possible resources, without compromising safety. Efficiency, however, differs from effectiveness which is defined in the report as “the extent to which the intervention’s objectives were achieved, or are expected to be achieved, taking into account their relative importance” (GICHD, 2023, p.6).

Yet, the quantitative framework developed by GICHD primarily focuses on efficiency indicators, particularly cost-based metrics such as cost per square meter of land released, cost per square meter of land fully cleared, and cost per explosive item found. This narrow focus allows for financial comparison but risks overlooking effectiveness dimensions such as the humanitarian, developmental, and social outcomes of mine clearance.

To operationalize this concept, the GICHD study developed a framework of Key Performance Indicators (KPIs) to measure economic efficiency across 17 mine-affected countries between 2015 and 2019 (GICHD, 2023, pp.14-17). Three indicators are identified as central for assessing the financial efficiency of mine action operations:

  1. Cost per square metre of land released – measuring the overall cost of returning territory to productive use, encompassing land cleared, reduced, and cancelled. A lower value indicates greater cost efficiency in land release and better-targeted survey and clearance operations.
  2. Cost per square metre of land cleared – reflecting the technical cost of full clearance, which is higher due to intensive labour, equipment, and safety requirements.
  3. Cost per explosive item found – linking financial inputs to tangible outputs, i.e., the average expenditure needed to locate and neutralize one explosive ordnance.

These metrics allow analysts and policymakers to assess how funds are transformed into measurable clearance outcomes. However, as GICHD (2023) stresses, they should be used for internal evaluation and planning, not for direct comparison between countries. Differences in contamination types, topography, labour costs, access, and national data systems make cross-country benchmarking misleading. The report explicitly cautions that “no country should be considered as having a ‘good’ or ‘bad’ performance in terms of operational efficiency purely on the basis of the KPI values” (GICHD, 2023, p.21). Even similar indicators can yield different implications depending on whether operations are clearance-driven (activity-based) or survey-driven (decision-based). To illustrate the scale and variation in demining costs globally, Table 1 presents key indicators of humanitarian demining costs as of 30 November 2022.

As shown in Table 1, costs per square meter of released territory range from USD 0.02/m² (Thailand) to USD 5.87/m² (Lebanon), i.e., a 293-fold difference. Similarly, the cost per explosive item ranged from USD 274 (Sri Lanka) to USD 13,450 (Croatia) (Rohozian, 2024). Such disparities illustrate that comparing “price per m²” without context or establishing the “benchmark” in the field is quite problematic.

Table 1. Key indicators of the cost of demining across countries, as of 30 Nov. 2022

State  Cost per square meter of territory released from the local socio-economic system, USD Cost per square meter of territory that has been cleared in the local socio-economic system, USD Cost of a single found explosive item in the local socio-economic system, USD
Angola 0,32 7,88 9042
Afghanistan 0,79 1,48 911
Bosnia and Herzegovina 0,36 19,06 6059
Vietnam 0,28 0,65 500
Western Sahara 0,41 0,51 2183
Zimbabwe 1,89 4,49 289
Iraq 0,81 1,32 4437
Cambodia 0,22 0,37 678
Laos 0,99 0,99 356
Lebanon 5,87 10,65 2204
South Sudan 0,49 4,07 5667
Serbia 1,07 1,96 9757
Sudan 2,89 5,78 457
Tajikistan 1,29 1,98 1721
Thailand 0,02 2,25 281
Croatia 1,03 1,23 13450
Sri Lanka 2,26 3,65 274

Source: Rohozian, 2024.

Moreover, the study acknowledges limitations in data standardisation and completeness. Variations in how organisations record and report costs affect comparability. Aggregated national averages can obscure contextual factors such as contamination density or security conditions. For these reasons, GICHD recommends interpreting efficiency metrics in conjunction with qualitative information, including terrain, contamination type, and labour structure, and always balancing cost-efficiency with safety and effectiveness.

However, drawing on global patterns and Ukraine’s official USD 34–35 billion cost estimate, we can expect Ukraine to fall within the middle range of international demining costs. It will likely be more expensive than low-cost cases in Asian contexts but substantially below the extreme-cost cases, such as Lebanon, due to its terrain, institutional capacity, and ability to scale mechanized clearance.

Challenges in Ukraine’s Humanitarian Demining

In addition to the substantial direct costs of humanitarian demining, it is essential to understand the indirect costs generated by systemic inefficiencies, i.e., costs that arise not from clearance itself, but from delays, duplication, weak coordination, and different shortages.

A review of Ukraine’s current mine-action landscape allows us to identify the main structural challenges that contribute to elevated indirect costs. These include fragmented governance, incomplete and inconsistent data, security-related access constraints, and a shortage of trained personnel.

One of the most pressing challenges is the fragmentation of coordination and governance. Responsibilities remain dispersed across numerous actors, including the Ministry of Defence, the State Emergency Service, the Ministry of Internal Affairs, the Ministry of Economy, the National Mine Action Authority, and over 20 accredited NGOs and private contractors.

According to the UDA (2025), this overlap of mandates and inconsistent prioritisation frameworks frequently results in duplicated surveys and delayed task approvals, reducing efficiency and transparency. At the same time, the idea of consolidating all authority within a single centralised body would risk excessive concentration of power and reduced accountability. A more effective path forward would be to strengthen the existing Mine Action Center’s coordinating role while maintaining clear institutional separation between policymaking and operational implementation, ensuring transparency, competition, and sustained donor confidence.

A persistent shortage of qualified personnel represents one of the most critical challenges to scaling up humanitarian demining in Ukraine. According to UNDP (2025), the country currently employs around 4,500 trained deminers, while full national recovery will require at least 10,000 professionals over the next decade (TBI, 2024). The workforce is under pressure from wartime mobilization, which diverts potential recruits to defense roles, and from a shortage of experienced supervisors and explosive ordnance disposal (EOD) specialists, limiting the number of teams that can safely operate simultaneously. The National Mine Action Strategy for the Period up to 2033 (Ministry of Economy of Ukraine, 2024) further acknowledges that Ukraine’s training system is inadequate for the sector’s needs.

Current state-level training for the profession of “Sapper (demining)” follows military-oriented standards that demand extensive time and resources but offer limited relevance to humanitarian operations. Only ten educational institutions are licensed to train deminers, and only a few conduct active courses. To close this capacity gap, the Strategy calls for expanding domestic training infrastructure, establishing accredited qualification centers, recognizing informal and partial training, and developing new professional standards tailored to humanitarian demining.

Another set of pressing challenges in Ukraine’s humanitarian demining effort concerns data deficits and security limitations. Incomplete and inconsistent mapping of hazardous areas continues to undermine planning and coordination. According to the Ministry of Economy (2023), Ukraine inherited multiple legacy databases using different coordinate systems and lacking harmonized metadata, resulting in duplication and delays in verifying “released” land. The absence of a unified digital mine-action information management system constrains both operational oversight and donor transparency. As Rohozian (2024) observes, such imperfect information leads to “erroneous management decisions” that increase total costs and prolong recovery.

In addition, large areas in the east and south remain off-limits due to ongoing hostilities, unexploded ordnance, and damaged infrastructure. Fluctuating front lines, dense contamination, and logistical barriers raise insurance and hazard-pay costs, shorten fieldwork periods, and cause rapid equipment deterioration.

Thus, addressing these interconnected challenges is essential to accelerate Ukraine’s reconstruction and ensure that mine action effectively supports the safe return of communities, the revival of agricultural production, and the broader recovery of the national economy.

The Role of Women in Humanitarian Demining

The role of women in Ukraine’s humanitarian demining sector deserves special attention, as they have become an integral part of the national workforce serving as deminers, team leaders, and technical-survey dog handlers. Their growing participation reflects both professional competence and the importance of gender-inclusive recovery efforts (UN Women Ukraine, 2025).

However, until 2017, Ukrainian legislation classified demining as a “dangerous profession,” barring women from formal employment in this field (Ministry of Health of Ukraine, 2017). Following sustained advocacy by international organizations, this restriction was lifted, granting women official access to mine-action professions. Since then, the number of women in operational and leadership roles has grown steadily.

Nevertheless, persistent stereotypes suggesting that demining is unsuitable for women have been disproved by practice, as reported by UN Women Ukraine, 2025. In practice, modern safety protocols and technologies such as drones and remotely operated vehicles allow women and men to perform tasks under equal safety conditions.

Following the lifting of the employment ban in 2017, which opened demining professions to women, mine-action organizations began reconsidering how to better meet women’s practical needs in the field. Recognizing that protective gear and uniforms had long been designed for men, many operators are now adapting equipment to fit women’s bodies, enhancing both comfort and operational efficiency.

These findings further demonstrate that gender-inclusive employment contributes to a reconstruction process that benefits all citizens and fosters social recovery based on principles of equity and shared responsibility.

Conclusions

In conclusion, humanitarian demining represents a strategic prerequisite for Ukraine’s reconstruction, food security, and long-term economic recovery. International experience demonstrates that mine clearance delivers substantial socio-economic dividends by restoring access to land, enabling trade, and rebuilding local livelihoods. However, the economic efficiency of mine action cannot be measured through simple cross-country comparisons. Costs per square meter or per explosive item differ widely depending on terrain, contamination density, labor costs, and institutional frameworks. Therefore, efficiency should be evaluated in context, i.e., by how well resources are transformed into measurable recovery outcomes without compromising safety or inclusiveness.

For Ukraine, transforming demining into a genuine driver of recovery requires addressing several domestic challenges. Fragmented governance and overlapping mandates continue to reduce coordination and transparency, while limited training capacity and workforce shortages constrain operational progress. Inconsistent data systems and incomplete mapping impede strategic planning, and security conditions still restrict access to large contaminated areas in the east and south of Ukraine. Overcoming these barriers will require strengthening the coordinating role of the National Mine Action Center and expanding professional education and certification programs.

Equally important, the growing participation of women in mine action deserves special recognition. Since the 2017 reform that lifted employment restrictions, women have become active as deminers, team leaders, and survey specialists, demonstrating both competence and leadership in this traditionally male-dominated field. Promoting gender-balanced participation will strengthen Ukraine’s mine action capacity and align reconstruction with broader principles of equality and social inclusion.

Thus, ensuring that clearance efforts are efficient, transparent, data-driven, and inclusive will determine how effectively Ukraine can restore productive land, rebuild infrastructure, and regain investor confidence.

References

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.

Saving Lives During War: How to Make Evacuation Messages More Effective

Posted on November 26, 2025 | Policy Brief

When war threatens civilian populations, effective evacuation messages can mean the difference between life and death. Drawing on a controlled survey experiment conducted with 2,006 Ukrainians during the 2022 Russian invasion, we find that providing clear evacuation plans dramatically improves a message’s perceived effectiveness, while sophisticated message framing makes little difference. Our results indicate that people facing war are not naive about dangers—they need practical information on how to escape, not persuasion about why they should leave. This is especially true for those who do not have the means to evacuate autonomously. These findings offer guidance for authorities and humanitarian organizations: focus on providing concrete evacuation logistics rather than crafting perfect messaging.

The Life-or-Death Challenge of Wartime Evacuations

Each year, tens of thousands of civilians die in armed conflicts worldwide. Many of these deaths could be prevented through timely evacuations from danger zones. Yet despite imminent threats, many civilians hesitate to leave their homes. Understanding how to increase the effectiveness of evacuation messages has become a critical challenge for saving lives.

In July 2022, five months into Russia’s full-scale invasion of Ukraine, we conducted the first experimental study testing the effectiveness of evacuation messages during an active war. Working with 2,006 Ukrainians from regions directly affected by combat, focusing on areas that experienced occupation, shelling, and ground fighting, we tested two fundamental approaches to improving evacuation messaging.

Figure 1. Surveyed regions with the relative share of respondents.

Source: Martinez et al. (2025)

 

Testing What Works: Plans vs. Persuasion

Our experiment compared two strategies:

Strategy 1: Persuasive Nudges

We tested different message framings inspired by behavioral economics, emphasizing either the gains from evacuating (saving lives) or losses from staying (risking death), and highlighting either deteriorating living conditions or benefits to military effectiveness. These techniques have proven effective in other contexts, from increasing vaccination rates to promoting energy conservation.

Strategy 2: Practical Evacuation Plans

We tested whether adding concrete evacuation instructions improved message effectiveness. Half of our messages included specific details: free buses available at designated locations, phone numbers for reserving seats, and clear departure times.

Participants evaluated how effective each message would be in convincing residents of their city to evacuate, using a scale from 0 (completely ineffective) to 10 (very effective).

Key Finding: People Need Logistics, Not Persuasion

Our results deliver a clear message for policymakers and humanitarian organizations:

Providing evacuation plans works

Messages that included concrete evacuation plans were rated approximately 5% more effective than those without. This improvement is both statistically significant and practically meaningful—in Donetsk oblast alone, where 350,000 civilians remained in Ukrainian-controlled areas during our study, a 5% increase in evacuation rates could mean 17,500 additional lives moved to safety.

Message framing makes little difference

Surprisingly, none of our carefully crafted persuasive messages performed better than a simple, standard evacuation notice. Whether we emphasized gains or losses, living conditions or military benefits, the framing made no significant difference to perceived effectiveness.

Different groups respond differently

The evacuation plan’s effect was strongest among those who had not previously evacuated, which is exactly the population authorities most need to reach. This particular segment of the population is characterized by lower financial means and, therefore, a lower likelihood of owning a car, which turned out to be a crucial factor when it comes to timely evacuations. Finally, women responded more strongly to evacuation plans than men.

Figure 2. Experimental Treatment Effects.

Source: Martinez et al. (2025)

Understanding the Psychology of War Zone Evacuations

Why do practical plans matter more than persuasive messaging? Our findings suggest that people experiencing war are far from naive about the dangers they face. Among our respondents:

  • 82% perceived real risk of death or injury from missile strikes
  • 40% had already evacuated at least once
  • 50% of those who stayed had considered evacuating

Which seems to suggest that the barrier is not understanding risk—it is knowing how to act on it. Our correlational analysis supports this interpretation: those offered transportation during the early invasion were 12-18 percentage points more likely to evacuate, while simply receiving evacuation information showed weaker effects.

Policy Recommendations

Based on our findings, we recommend that authorities and humanitarian organizations prioritize the following:

  1. Focus resources on logistics, not messaging

Instead of investing in sophisticated communication strategies, dedicate resources to organizing concrete evacuation support: transportation, clear meeting points, advance booking systems, and designated evacuation routes.

  1. Provide specific, actionable information

Every evacuation message should include: exact locations for transportation pickup, specific departure times, contact information for coordination, clear instructions for what evacuees can bring, and confirmation of free transportation.

  1. Target messages strategically

Prioritize delivering evacuation plans to those who have not previously evacuated, women who show higher responsiveness to organized evacuations, and areas where residents lack personal evacuation plans, that is most likely in the lower socio-economic status neighborhoods.

  1. Act on timing

Our research captured a relatively stable period in the conflict. During acute escalations, rapid deployment of evacuation logistics likely matters even more than message optimization.

Implications Beyond Ukraine

While our study focused on Ukraine, approximately 50 active conflicts worldwide threaten civilian populations. Our findings suggest a fundamental shift in how international organizations approach emergency evacuations: from persuasion to facilitation.

The lesson is sobering, but actionable. People facing mortal danger do not need convincing that threats are real. They need practical help escaping them. This insight should reshape how humanitarian organizations allocate resources, how militaries plan for civilian protection, and how governments prepare for crisis scenarios.

Conclusion

Effective evacuation during war is not about finding the perfect words; it is about providing clear paths to safety. Our research suggests that even simple additions of logistical information can meaningfully improve an evacuation message’s perceived effectiveness. In contexts where every percentage point of improved evacuation rates translates to lives saved, focusing on practical evacuation support over persuasive messaging represents both an evidence-based and morally imperative policy choice. For the millions of civilians who may face evacuation decisions in current and future conflicts, the message from our research is clear: authorities must move beyond telling people to leave and start showing them exactly how.

References

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

Posted on November 24, 2025 | Policy Brief

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

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.

Between Progress and Pushback: Latvia and the Istanbul Convention

Posted on November 17, 2025 | Policy Brief

Protester holding a sign during a nighttime rally addressing Latvia Istanbul Convention Withdrawal.

On 25 September 2025, the Latvian Parliament voted to begin the process of withdrawing Latvia from the Council of Europe Convention on Preventing and Combating Violence Against Women and Domestic Violence (Istanbul Convention). This vote has been met with growing mass protests. We provide some background to understand the political and societal movements that underlie these events. Survey data shows that (a) violence against women is prevalent in Latvia and (b) there is public support for legislation aimed at combating a major expression of gender-based violence, such as intimate partner violence. However, the Latvian public appears polarized on perceptions about women’s and men’s roles in society, which might conflict with the Convention’s call for States to combat gender stereotypes. The vote’s significance in terms of Latvia’s geopolitical positioning between the EU and Russia also contributes to making the Convention a polarizing issue.

Introduction

Latvia ratified the Istanbul Convention in November 2023. The Convention entered into force on 1 May 2024. Since then, significant political debate has emerged around its continued implementation, with strong calls from some political parties and civic groups to withdraw. On 25 September 2025, the Saeima, Latvia’s parliament, considered withdrawal. On 31 October, Saeima voted to withdraw from the Istanbul Convention (56 in favor, 32 against). President Edgars Rinkēvičs, noting the potential harm to Latvia’s international standing, returned the law to the Saeima. Lawmakers then postponed further action until after the October 2026 elections. Mass protests erupted in the Latvian capital against the possible withdrawal. If the next Parliament pushes the withdrawal process to completion, Latvia will be the first EU country to withdraw from the Convention and the second among the original signatories to do so, after Turkey.

This policy brief outlines the background to the parliamentary vote and subsequent mass protests, traces the political process behind them, assesses their geopolitical significance, including Russian influence in Latvian politics, and considers whether the vote reflects a wider societal move away from the Convention’s core principles.

“We Don’t Say Gender Here”

The debate in Latvia centres primarily on concerns around the term “gender”  and how social roles are defined under the Convention, rather than its core aim of preventing violence and protecting victims. Specifically, Article 3(c) of the Convention defines gender as “the socially constructed roles, behaviours, activities and attributes that a given society considers appropriate for women and men.” This definition is instrumental in understanding violence against women as a fundamental expression of patriarchal norms that assign rigid roles in society to men and women. Such understanding is, in turn, considered a precondition for a holistic approach in combating gender-based violence (GBV) that includes legal protections but also profound cultural transformations. The controversy in Latvia surrounding this definition of gender, as opposed to biological sex, sits within a broader Latvian paradox. On the one hand, Latvia has a strong representation of women in the labour market and leadership – it ranks second in the European Union in terms of women in managerial positions (although this representation is weaker for political leadership; see Gerber, 2021, for more details). On the other hand, gender-role attitudes remain traditional: Latvia has one of the highest shares in the EU of respondents who believe caregiving is primarily a woman’s responsibility and consistently shows one of the largest gender gaps in time spent on care-related unpaid work (Ministry of Welfare of the Republic of Latvia, 2024; Statistics Latvia, 2024; European Institute for Gender Equality, 2023).

The concept of “gender” as a social construct has entered Latvian public discourse only recently, and there is no widely accepted everyday equivalent for the English word in the Latvian language. The term used in institutional and policy contexts, sociālais dzimums (literally “social sex”), is technical and unfamiliar to many Latvians. In general usage, “dzimums” refers to biological sex, and historically, Latvian policy and legal frameworks have operated under this binary understanding (Kalnbērziņa, 2023). Proponents of withdrawal, largely from conservative and nationalist political parties, argue that the Convention introduces ideas about “gender” that conflict with Latvian cultural values, family roles, and existing legal frameworks. For these actors, the Convention is perceived, or framed, less as a tool for protection against violence and more as a vehicle for social change initiated from outside, which, as such, allegedly undermines sovereignty.

Parties’ Positioning on the Convention

Against this background, political parties’ standing on the Convention has defined new fractures within the Saeima and in society more broadly, quickly becoming an increasingly polarizing matter with high significance for government stability, democratic representation, and alignment with EU core values. Although public debate has focused on ideological disagreements over gender, political dynamics played a significant role in the 2025 vote on withdrawing from the Istanbul Convention. New Unity, the largest party in the Saeima, led by Prime Minister Evika Siliņa, previously broke with its government coalition partners, the National Alliance and United List, to form a new coalition with the Greens and Farmers Union (ZZS) and The Progressives, partly to ensure the ratification of the Convention. The resulting government was sworn in September 2023 without new Parliamentary elections. The National Alliance and United List, long opposed to the treaty’s gender terminology, viewed this shift as a betrayal by New Unity and have since aligned more closely with Latvia First and For Stability! to push for withdrawal. Meanwhile, ZZS, a major player in Latvian politics, first supported ratification but later backed withdrawal, raising questions about policy consistency as its deputies effectively voted against their own earlier decision.

The result has left the governing coalition – still composed of New Unity, The Progressives, and ZZS – weakened and politically divided, with opposition parties exploiting the moment while the 2026 budget process remains critical. The situation also placed pressure on President Edgars Rinkēvičs, who eventually decided to return the withdrawal law to parliament, mentioning concerns over potential harm to Latvia’s international standing as a key factor behind his decision. He recommended that the issue should be reconsidered after the elections in 2026. Overall, political repositioning and coalition instability have become deeply intertwined with a key human-rights commitment. One side, mirroring ultra-conservative rhetoric across Europe, criticized the treaty as promoting “gender ideology,” encouraging sexual experimentation, and harming children. Supporters countered that these claims amounted to anti-EU rhetoric.

At the same time, public mobilisation has been significant. Over ten thousand people have gathered in multiple peaceful demonstrations in Riga to oppose withdrawal, expressing concern about potential setbacks to women’s rights and victim protection (Meduza, 2025; Hivert, 2025). International organisations have also highlighted that withdrawal would place Latvia in a unique position within the European Union, as no other EU member state has sought to leave this treaty (Amnesty International, 2025).

Geopolitical Significance

The Saeima’s vote to withdraw from the Istanbul Convention risks undermining Latvia’s long-built reputation as a Nordic-style liberal democracy with strong human-rights standards. If the withdrawal decision becomes law, Latvia would stand as the only country in the Nordic-Baltic Eight (NB8) outside the Convention, while Lithuania continues toward ratification. The move prompted an unusual diplomatic intervention: parliamentary speakers from several NB8 states and ambassadors from 15 close partners urged Latvia to remain in solidarity on violence prevention (Collier, 2025). These appeals were ignored. Internationally, Latvia would be grouped with Turkey as the only states to exit the treaty, raising concerns among partners about backsliding on women’s rights and domestic-violence protection. Observers warned that this decision could (and may still in 2026) reverse decades of work to portray Latvia as a modern, progressive European state, instead reinforcing outdated “post-Soviet” stereotypes. Rebuilding credibility requires diplomatic effort and clear, effective national action to protect victims.

It is also significant that the disagreement with other NB8 countries occurs at a time when, otherwise, there is growing cooperation between the NB8 members, in part in response to the geopolitical realities that make Latvia’s relationship with other EU and NATO members arguably ever more critical.

Geopolitics also matter because monitoring and survey data indicate that gender-related policy debates in Latvia are susceptible to wider geopolitical narratives. Approximately one-third of Latvian respondents believe that gender equality policies are “imposed by the EU,” a sentiment that is significantly more common among Russian-speaking residents (EC, 2017, 2019). Analyses of Latvian media ecosystems show that narratives opposing “gender ideology” are regularly amplified in Russian-language outlets, linking such policies to moral decline and loss of national identity (CEEPS, 2023). These framings align with broader Kremlin messaging, which positions European human-rights norms as threats to cultural sovereignty (EUvsDisinfo, 2024), though there is no evidence of direct Russian intervention. However, the Latvian State Security Service has noted that debates on gender and family values are used as entry points for polarisation and for undermining trust in Latvia’s Western partnerships (Latvian Security Service, 2024).

Taken together, this suggests that the controversy surrounding the Istanbul Convention does not occur in isolation. Rather, it intersects with information influence efforts that exploit pre-existing societal tensions around identity, norms, and Latvia’s European orientation.

What about Incidence and Perceptions Around Gender-based Violence in Society?

Meanwhile, survey data indicate that gender-based and domestic violence remain a significant and often under-reported problem in Latvia, suggesting that improvements in gender equality in the workplace have not yet translated into safety within households.

Estimates based on a 2021 survey on gender-based violence by the European Institute of Gender Equality (EGEN) show that one quarter of Latvian women aged 18-74 have experienced physical or sexual violence since the age of 15, and 16% have experienced violence from their intimate partner (IPV). 23% of these women had not told anyone about the violence before the survey interview. Notably, in 2022, Latvia also reported the highest femicide rate in the EU, with 2.9 women being intentionally killed by their partner, former partner, or family member per 100,000 inhabitants. The survey also depicts a culture not fully responsive to relatively subtle forms of gender-based violence and permeated with significant stereotypes. For instance, 53% of Latvian women and 41% of Latvian men believe or tend to believe that women who share their opinion on social media should expect sexist, demeaning and/or abusive replies (EU averages are 18 and 23% respectively); 45% of women and 47% of men believe that a woman who suffers sexual violence under the influence of alcohol or drugs is at least partially responsible (respective EU averages are 13 and 20%).

Nevertheless, a large majority of Latvians seem to support the notion that IPV should be legislated in some way. A FREE Network survey of a representative (based on age and gender) sample (around 900 individuals) of the Latvian population shows that, as of September 2021, nearly 90% of respondents thought that the State should have specific legislation addressing IPV, a key tenet of the Istanbul Convention. This average masks heterogeneity by gender, with relatively fewer men (81% vs. 97% of women) expressing support for such legislation. Consistently, more Latvian men (14%) than women (9%) appeared to think that a woman beaten by her partner should not seek any help, because it is a private matter. For comparison, in Sweden, a country that has long ratified the Convention (2014), these percentages are 4% and 3%, respectively. The same survey also confirms that the Latvian society is relatively less attuned to more subtle forms of IPV, namely, psychological violence. For instance, while the percentage of respondents in Latvia who believe that harmful beating is a form of IPV matches the percentage in Sweden (98%), only 77% of Latvians believe that the prohibition to dress as one likes is a form of IPV, against a Swedish percentage of 95%.

Finally, the FROGEE survey depicts a public opinion permeated by stereotypes about women and men’s roles in society: nearly 30% of Latvians appear to believe that if a job is scarce men should be given more right to a job than women, nearly a majority report agreeing with the statement that “what most women really want is a home and children”, and a majority (54%) thinks that a pre-school child suffers if his/her mother work.

In terms of attitudes toward DV legislation, it is also worth noting that the Latvian Parliament has recently strengthened its legal system to protect victims of domestic violence by approving, in February 2022, a law granting the police the right to separate the victim of domestic violence from the perpetrator, even without the victim’s request. The FROGEE survey reveals that public knowledge around this provision at the time of discussion within the government was relatively limited (30% of survey respondents reported being aware of such discussion, see Berlin-Perrotta et al., 2024), signalling that decisions around DV legislation did not feature prominently in the public debate, at least at the time of the interview.

In sum, the data suggest that gender-based violence and IPV are pressing issues in the Latvian context. The public does not seem to be especially polarized on the extent to which major expressions of IPV should be legislated. Beliefs about more subtle forms of violence, or violence that is more clearly an expression of a patriarchal culture that assigns specific roles to women and men, appear to be more polarized; the same can be said more generally about beliefs on gender roles.

Conclusion

In the face of the recent Latvian Parliament vote to withdraw from the Istanbul Convention and the growing public protests against it, we provided some background to understand the political and societal movements that underlie these events. Our analysis starts from the observation that, overall, the Parliamentary vote is not so much about the main purpose of the Istanbul Convention, which is to fight gender-based and domestic violence, but rather about the Convention’s definition of gender as a social construct. We document that at the societal level, there is general support for legislation aimed at combating a major expression of gender-based violence, such as IPV. However, the Latvian public appears to be more polarized on perceptions about women’s and men’s roles in society, with more traditional views being popular among large shares of the population.

The Parliamentary opposition to the Convention, therefore, can be at best understood as an expression of society’s unease with less traditional gender-based roles, coupled with political parties’ positioning with respect to an increasingly weakening governmental majority. However, framings of the Convention’s definition of gender as an attempt to override the binary definition of sex, despite this being neither a direct nor an indirect tenet of the Convention, might also have contributed to inflaming the related debate. These framings have charged stances on the Convention with significance in terms of Latvia’s geopolitical positioning between the EU, of which the country has long been a member, and Russia, a powerful reference especially for the ethnic Russian population. These factors combine to make stances on the Convention profoundly divided at a time when the country is exposed to increased external threat by Russia’s heightened aggressiveness in the Baltic region.

References

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.

Estimating Tax Evasion in Europe: Direct vs. Indirect Survey Methods

Posted on November 10, 2025 | Policy Brief

Stack of €50 euro banknotes in partial shadow, symbolizing hidden cash and tax evasion survey methods.

How can societies accurately gauge the share of the workforce engaged in the shadow economy when direct questions inspire selective silence or evasion? This policy brief presents findings from a new cross-country survey experiment combining direct questions and an indirect “list experiment” method, conducted in Latvia, Italy, and Denmark. Results show that, contrary to expectations, indirect methods did not yield higher estimates of undeclared work compared to direct questions. The research reveals that in environments with high tax morale and a substantial shadow economy, both direct and indirect measurements can be biased. Sharing information about prevailing tax norms with respondents can improve survey consistency, informing future tax evasion measurement and anti-evasion policymaking.

Social Desirability Bias in Tax Evasion Surveys

Surveys on tax evasion often provide respondents with multiple response categories beyond simple “yes” or “no.” For example, the survey for Latvia (Kantar, 2024) found that 3% openly acknowledged undeclared income, but refusal (2%) and “hard to say” responses (4%) illustrate additional uncertainty and possible underreporting due to social desirability bias when respondents consciously avoid disclosing disapproved or illegal acts to maintain a positive self-image or avoid perceived censure. This bias is potentially serious in tax compliance research, where both tax morale and fear of consequences can shape reporting behavior.

Indirect questioning techniques, such as list experiments, aim to reduce social desirability bias by allowing individuals to conceal answers within a broader set of innocuous items (Blair et al., 2020). In a typical list experiment, respondents are randomly assigned to receive either a list of non-sensitive items or the same list with an additional sensitive item; by comparing the mean number of items endorsed across groups, researchers estimate the prevalence of the sensitive behavior without requiring explicit disclosure (Blair & Imai, 2012; Glynn, 2013).

Recent empirical work employing list experimental designs has significantly advanced the understanding of tax evasion dynamics across diverse fiscal and cultural contexts. Fergusson, Molina, and Riaño (2019) analyzed VAT evasion among Colombian consumers and found minimal social desirability bias, with list experiments and direct self-reports yielding similar evasion rates (~20%). They attributed this to the normalization of evasion in high-informality regions, where descriptive norms (perceived prevalence of evasion) outweighed injunctive norms, reducing stigma.

This contrasts with Genest-Grégoire et al. (2022), who detected significant bias in Canadian income tax self-reports: list experiments revealed 13.5% income tax evasion (compared to 5.6% in direct questions) and 28.5% consumption tax evasion (compared to 26.2% in direct questions). The study identified stronger stigma around income tax evasion, particularly due to institutional withholding mechanisms that make income tax evasion more difficult compared to consumption taxes. Authors posit that divergent motivational mechanisms underlie these evasion types: income tax noncompliance triggers stronger moral condemnation due to its association with deliberate fraud, while consumption tax evasion is often rationalized as a “victimless” violation of complex regulations.

Hence, high tax morale, while generally associated with greater compliance, also leads individuals to conceal or misrepresent socially undesirable actions more rigorously, which amplifies social desirability bias in survey responses. This effect is particularly pronounced in environments where tax evasion is strongly stigmatized, as respondents may feel increased pressure to align their self-reports with prevailing moral standards, even if those reports do not reflect their true behavior. Conversely, in contexts where evasion is normalized or perceived as widespread, the stigma associated with noncompliance decreases, potentially making individuals less reluctant to report such behavior.  Nevertheless, both direct and indirect measurement techniques may still fail to accurately capture the true prevalence. This is because reduced stigma alone does not eliminate other sources of bias, including cognitive complexity, survey design imperfections, and strategic respondent behavior, such as misinterpreting instructions or using responses to send political or social signals beyond truthful self-disclosure.

Recognizing these persistent methodological challenges, this policy brief presents evidence from a study employing both direct and indirect questions on tax evasion across three European countries with varying levels of tax morale and shadow economy prevalence. By analyzing how social contexts influence reporting behaviors, the brief provides insights into the effectiveness and limitations of these survey approaches in different normative environments.

Approach

The research used a nationally representative sample of 6,915 respondents from Latvia, Italy, and Denmark, utilizing Norstat online panels in the respective countries. It was administered as an online Computer Assisted Web Interview (CAWI) in May 2024. Respondents in the study were randomly assigned to one of two list experiment conditions: half received a 5-item list including the sensitive tax evasion item, while the other half received a 4-item list without the sensitive item (see Figure 1). Importantly, all respondents—regardless of their list group assignment—were asked a direct question about undeclared income at the end of the survey. This design allows comparison between indirect and direct measures within the same individuals, clarifying reporting patterns and social desirability effects.

Figure 1. Indirect question for the control group of the list experimental study

Notes: The 5-item list for the treatment group included additional activity “Received all or part of the income without paying taxes (received money “off the books”)” and asked to indicate max 5 items. The activities were listed in random order for each respondent.

All participants also completed a placebo list experiment, in which both lists – i.e., containing 4 or 5 items – consisted entirely of non-sensitive behaviors (see Figure 2). Correspondingly, everyone was also asked a direct question about the non-sensitive behavior (“Bought a house or apartment (including on credit)”), thereby mimicking the structure of the tax evasion list experiment. This design allowed controlling for possible cognitive errors in filling out a complicated survey task, such as a list survey question, that are unrelated to social desirability bias.

In addition, half of all respondents were primed to information with actual data on how many citizens in their country consider tax evasion unacceptable, sourced from a recent representative survey that was carried out in January 2024. In this pre-survey, just 39% (i.e., minority) found tax evasion wholly unacceptable in Latvia; 59% in Italy, and 53% in Denmark (i.e., majority). The goal of this priming was to test whether informing respondents about local norms affected reporting patterns.

Figure 2. Placebo list of the study

Notes: The 5-item list for the treatment group included additional activity “Bought a house or apartment (including on credit)” and asked to indicate max 5 items. The activities were listed in random order for each respondent.

Key Findings

Results show that indirect list experiment estimates of undeclared work (4.1% overall) did not significantly differ from direct question estimates (7.2%). Hence, respondents did not find the topic sensitive enough to avoid honest answers in either format.

Priming respondents with information about the unacceptability of tax evasion in their country had no statistically significant effect on the direct measure of admitted undeclared income, nor on aggregate estimates from the indirect list experiment, indicating that willingness to disclose undeclared work remained unchanged regardless of norm priming.

Figure 3. Estimates of tax evasion from the list experiment and direct question

Source: Author’s estimate from the survey results.

However, country-level analysis revealed an anomaly in Italy: the list experiment produced an implausible negative estimate, driven by some respondents who marked zero items in the treatment list but later admitted to undeclared work in direct questioning. While this inconsistent response pattern was most prominent in Italy, the country with the highest tax morale (as based on pre-survey), and the largest shadow economy across the three countries (Medina and Schneider, 2018), it has also been recorded in the other two countries. Specifically, the pattern was observed among 11% of respondents who admitted to tax evasion in the direct question in Italy, compared to 5–7% in Latvia and Denmark.

Considering the complexity and unusual formulation of the question for the list experiment, one might attribute this pattern to a respondent’s confusion or cognitive error. However, this explanation is unlikely because of the responses to the placebo list experiment, where all list items and a direct question are non-sensitive. There, the specific response pattern – respondents reporting zero items on the list question while simultaneously admitting to the direct question – is observed substantially less frequently, indicating a low baseline error rate for misunderstanding or inconsistent reporting on non-sensitive items.

The comparison between the sensitive and placebo list experiment results indicates that the anomalous pattern observed in the tax evasion list experiment is unlikely to be due to confusion with the survey format, but rather represents a deliberate, context-specific form of strategic misreporting. One possible reason for this pattern might be that some Italians who admit to tax evasion in the direct question may believe that inflating shadow economy estimates will spur stronger policy reactions or public debate. In this way, their answers to the survey may represent strategic “signal sending.”

Priming respondents with accurate information about societal norms regarding the unacceptability of tax evasion – an approach referred to as vignette priming – consistently reduced the occurrence of this contradictory response pattern. Fewer respondents reported zero items in the list experiment while admitting to evasion in direct questioning, a change observed universally across the three countries.

Two main interpretations of the effects of such vignette priming can be suggested. The first interpretation, related to the strategic motive discussed above, suggests that vignette priming helps align respondents’ understanding of prevailing social norms on tax evasion. This improved awareness discourages deliberate misreporting, thus improving the overall validity and reliability of the survey’s methodology, even if it does not increase overall admissions of tax evasion itself. An alternative explanation is that vignette priming helps respondents better recognize and correctly count items in the list experiment, thereby improving response accuracy and alignment across question formats.

In other words, norm priming fosters more consistent survey responses, whether by reducing the temptation to manipulate results or by increasing recognition and attention among respondents.

Conclusion

Efforts to estimate tax evasion through surveys must strike a balance between the limitations of direct self-reports and the incomplete protection against bias afforded by indirect methods. This study finds that, in the surveyed countries, list experiments do not yield higher or more accurate prevalence estimates than direct questioning. However, particularly in high-morale environments with substantial shadow economies, some respondents may strategically manipulate survey results in hopes of prompting political action.

Norm priming through vignettes enhances experimental integrity and reduces strategic errors, underscoring the importance of accounting for social context in survey designs. For tax policy makers, measurement should always be validated with error diagnostics and social context cues, and survey formats should be adapted for cross-country comparability and public trust.

Acknowledgements

The study is financed by the European Commission’s Marie Sklodowska-Curie Individual Fellowship Action (Grant agreement ID: 101109679).

References

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.

How Generative AI is Going to Affect the Georgian Labor Market

Posted on October 27, 2025 | Policy Brief, Policy Papers

Modern glass office building with employees working late, representing the impact of generative AI on the labor market.

This policy paper investigates the potential impact of generative artificial intelligence (GenAI) on the Georgian labor market, identifying which occupations and demographic groups are most affected. Drawing on the International Labor Organization’s (ILO) 2025 exposure scores and detailed 2023 Georgian Labor Force Survey data, our findings reveal that 26% of Georgian workers are in occupations where part of their tasks could potentially be performed, fully or partially, by GenAI, with over a third of those in medium- to high-exposure roles. Compared with the broader Europe and Central Asia region, Georgia has fewer workers in occupations vulnerable to full automation, while a larger share of the workforce is engaged in roles with potential for task augmentation. The analysis also reveals that GenAI’s impacts are uneven, with women, urban workers, younger individuals, and those with higher education being disproportionately represented in high-exposure occupations. Importantly, exposure scores measure technological feasibility rather than actual displacement risk – actual outcomes will depend on adoption rates, regulatory frameworks, and organizational decisions. Thus, timely and active policy involvement – from targeted upskilling to addressing digital disparities – is crucial to turn AI challenges into opportunities and fully harness its benefits by strengthening workers’ capacity to complement AI in their tasks.

Introduction

Generative artificial intelligence is playing an increasingly prominent role in workplaces worldwide. Tools such as ChatGPT, Midjourney, Google Gemini, and others are transforming how tasks are performed, changing work routines, and creating new forms of collaboration between humans and machines.

GenAI represents both a challenge and an opportunity. While different GenAI tools offer productivity gains and cost savings, their implementation may deepen regional disparities and pressure vulnerable groups – especially if targeted upskilling and digital-inclusion measures are not in place. At the same time, GenAI can reshape occupations by creating AI-specific and complementary roles. Balancing these opportunities and challenges is therefore critical to harness the full potential of GenAI.

A structured way to understand the effects of AI in the workplace is by considering two distinct channels: automation and augmentation. Automation refers to the complete substitution of human-performed tasks that can now be executed independently by AI without human involvement. Typically, such tasks are routine and cognitive, such as basic content generation or data classification. In contrast, augmentation captures scenarios where GenAI acts as a complementary tool, enhancing human performance without replacing the worker. The distinction between automation and augmentation is crucial for evaluating the implications of GenAI: while the former may lead to job displacement, the latter suggests changes in task composition, potential shifts in skill demand, and enhancements in labor productivity.

Consequently, the way GenAI shapes the new labor market reality will be affected by the composition of these two effects. In particular, in developing countries like Georgia, the extent of automation and resulting job displacement might be limited, as a large share of employment is in manual, physical sectors largely insulated from AI. At the same time, developing countries might underutilize the benefits of augmentation because many workers lack digital skills or access to GenAI tools, limiting productivity gains.

This policy paper aims to investigate the potential impact of generative artificial intelligence on the Georgian labor market through the automation-augmentation lens. In doing so, we utilize the approach used in the International Labor Organization’s (ILO)  Global Index of Occupational Exposure to Generative AI (Gmyrek et al., 2025). Rather than treating automation and augmentation potentials as two opposing categories with a large area of uncertainty in between, Gmyrek et al. (2025) apply a more refined classification that captures a spectrum of AI exposure. The ILO’s task-based framework categorizes occupations into six distinct groups by evaluating the extent to which their tasks can be automated by Generative AI. These groups are constructed considering both the average exposure score of tasks within each occupation and the standard deviation of exposure scores across those tasks. This enables the differentiation of jobs not only by their average exposure to GenAI but also by distinguishing between occupations where exposure is relatively evenly distributed across tasks and those where it is concentrated in only a subset of tasks. Aligning closely with the notions of augmentation and automation potential in the earlier ILO framework described in Gmyrek et al. (2023), an occupation is considered to have an “augmentation potential” when the average exposure score is low, but deviation across tasks is high. In other words, while some tasks in these jobs may have high automation potential, many others continue to require human involvement (Gmyrek et al., 2025). Conversely, an occupation is said to have an “automation potential” when the average exposure score is high and there is a high consistency of exposure across tasks (i.e., there is low standard deviation). Occupations that fall in between these two categories can be viewed as being in transition, slowly shifting from augmentation toward automation potential.

By using the ILO’s 2025 exposure scores and detailed Georgian Labor Force Survey data from 2023, we identify which occupations and demographic groups have the highest exposure to GenAI. Findings suggest that a significant share (26%) of Georgian workers face some level of exposure to generative AI, ranging from low to high, with over a third of them (100,584 individuals) falling into the medium- to high-exposure categories. The remainder are either not exposed (59%) or minimally exposed (15%). In comparison to other countries in Europe and Central Asia, Georgia is less affected by the threat of job displacement coming from automation, while the potential for augmentation is higher.

The exposure trends vary markedly by gender, age, and region. Urban workers, particularly in Tbilisi, are the most exposed, while rural workers face lower immediate exposure, reflecting existing digital divides and regional occupational characteristics. Gender disaggregated analysis shows that women, who are slightly overrepresented in AI-exposed clerical and administrative roles, account for 63% of workers in medium- and high-exposure occupations. Age-wise, younger and more digitally skilled workers tend to occupy the roles most affected by generative AI.

This paper proceeds as follows. First, we describe the methodology and data used to assess exposure to Generative AI in the Georgian labor market. Next, we present the ILO’s global estimates of GenAI-exposed occupations. The subsequent sections provide the results for Georgian workers, disaggregated by occupation, education, demographic groups, and region. The final section summarizes the findings and offers some policy insights.

Methodology and Data

This section outlines the methodology and data sources used to assess occupational exposure to Generative AI in Georgia, combining international GenAI exposure scores with nationally representative labor market information.

Several studies have developed indices or measures of occupational automation/AI exposure, often using different methods and classifications. A pioneering study by Frey and Osborne (2013) labeled occupations as automatable or not by applying a machine-learning classifier to the Occupational Information Network (O*NET) database of tasks – a comprehensive database of occupational information maintained by the U.S. Department of Labor. Their approach effectively treated each occupation as a unitary risk category, which has been critiqued for ignoring within-job task differences. Arntz et al. (2016), an OECD analysis, relaxed Frey and Osborne’s (2013) assumptions by using PIAAC survey data to allow task variation within occupations. Felten et al. (2019, 2021) developed the AI Occupational Exposure (AIOE) index, which uses overlaps between occupations’ O*NET skill and task requirements and known AI capabilities to compute exposure scores.  Using AI exposure metrics sourced from Felton (2021) and the IMF Complementarity Index, PwC Global AI Jobs Barometer (2025) classifies jobs into “augmented” or “automated” categories. Specifically, occupations with high AI exposure (>0.5 on a 0–1 scale) are split by an AI-complementarity threshold: those with high complementarity are deemed “augmented” (AI enhances tasks), while low complementarity jobs are “automated” (AI replaces tasks).

The exposure framework proposed by Gmyrek et al. (2025) builds on this literature and captures the occupational exposure to generative AI by combining algorithmic prediction with extensive large-scale survey data, supplemented by expert validation and iterative revisions to arrive at a refined global index of exposure. The process begins by considering each job title as a composite of tasks, each with varying susceptibility to automation. This approach aligns with contemporary labor market research emphasizing the mixed nature of task automation potential within occupations rather than assuming uniform automation across entire job categories.

The initial steps used to develop exposure scores involve an algorithmic assessment of automation potential for 2,861 detailed tasks derived from the Polish 6-digit occupational classification system. Utilizing three advanced Large Language Models (LLMs) – GPT-4, GPT-4o, and Gemini Flash 1.5 –  Gmyrek et al. (2025) assign a synthetic automation score on a continuous scale from 0 to 1, where 0 indicates no potential for automation, a score from 0 to 1 means augmentation by GenAI, and 1 signifies full automation potential without human involvement. This phase leverages sequential Application Programming Interfaces calls wherein each LLM is provided with contextual information regarding the task’s occupational classification and is instructed to assign the scores and justify them. Repeated scoring by multiple LLMs for the same task enabled triangulation and helped identify inconsistencies between model outputs. The distribution of synthetic scores revealed GenAI exposure in cognitive-intensive occupational groups and lower exposure where physical tasks dominate.

Subsequently, the researchers conduct a large-scale human survey utilizing the Computer-Assisted Web Interview (CAWI) technique to capture workers’ perceptions of task automation potential. The sample included respondents from all ISCO-08 1-digit occupational groups. Each respondent evaluates the automation susceptibility of a randomized set of 35 tasks from their occupation on a 0-100 scale.

To reduce biases related to uneven task familiarity and varying levels of GenAI knowledge, Gmyrek et al. (2025) supplement the survey with an expert validation stage. A smaller group of international experts from the ILO, National Research Institute of the Ministry of Digital Affairs in Poland, and the Polish Ministry of Family, Labor and Social Policy – each with extensive labor market expertise – assess a sample of tasks across occupational groups. Their evaluations focus on practical feasibility and workplace realities, helping to correct potential over- or underestimations from the general survey and ensuring that results reflect grounded, pragmatic perspectives on automation potential.

Moreover, two independent AI models then reconcile differences between survey respondents and experts, analyzing task-level scores and generating adjusted automation potentials with justifications.

The final stage constructs the Adjusted Global Index of GenAI Exposure, classifying occupations at the ISCO-08 4-digit level into six categories based on the mean and standard deviation of task-level automation scores. These range from Not Exposed and Minimal Exposure to four ascending Exposure Gradients:

  • Gradient 1 (Low exposure, high task variability)
  • Gradient 2 (Moderate exposure, high task variability)
  • Gradient 3 (Significant exposure, high task variability)
  • Gradient 4 (Highest exposure, low task variability)

Occupations composed of tasks with low average GenAI exposure scores and substantial variability of these scores across tasks (high task variability) are more closely associated with augmentation, whereas occupations with high average exposure scores and low task variability are more closely associated with automation. This classification advances beyond the binary automation–augmentation lens of prior studies by incorporating task variability within occupations, thus reflecting the heterogeneous automation risks embedded in different tasks.

ILO’s global estimates of GenAI-exposed occupations

This section presents the ILO’s global estimates of occupations exposed to Generative AI, illustrating potential impacts on labor markets worldwide.

As noted by Gmyrek et al. (2025), approximately 24% of the global workforce is engaged in jobs that involve some level of exposure to GenAI (Figure 1). This exposure is more prevalent in higher-income nations, where 34% of total employment is affected, compared to just 11% in low-income countries (Gmyrek et al., 2025).

Figure 1. Global estimates of occupations potentially exposed to GenAI (% of employment by sex)

Source: Figure 20 from Gmyrek et al. (2025).

As Figure 1 shows, women are disproportionately overrepresented in higher-exposure roles, while men are slightly more concentrated in lower-exposure jobs. Among male employees, approximately 21% of positions fall into one of the exposure levels, with 3.1% classified in gradient 3 and 2.4% in the highest exposure level, gradient 4. Conversely, the proportion of female employment in potentially exposed roles is significantly greater, particularly in the upper two gradients, where 5.7% of female workers are in gradient 3 and an additional 4.7% are in gradient 4. These gender disparities also widen with country income levels, increasing to 9.6% for women in gradient 4 versus 3.5% for men in high-income countries (Gmyrek et al., 2025).

When it comes to Europe and Central Asia, as Figure 2 shows, in this region, about 32% of employees (136 million jobs) are exposed to GenAI, with 5.7% considered highly exposed.

Figure 2. Estimates of occupations potentially exposed to GenAI for the Europe and Central Asia region (% of employment by sex)

Source: Figure 20 from Gmyrek et al. (2025).

This region exhibits a notable gender disparity: 26% of men compared to 39% of women are exposed, and 3.3% of male-held jobs (61 million) versus 8.6% of female-held jobs (75 million) are highly exposed to GenAI.

Results for the Georgian Labor Market

For the current analysis, we applied the above-described exposure gradients to 361 ISCO-08 4-digit occupations from the 2023 Georgian Labor Force Survey (LFS), covering a workforce of 1,313,636, of whom 45% (594,064) were women. Occupations lacking sufficient detail or unclassified under ISCO-08 were excluded.

As shown in Figure 3, overall, about 26% of Georgian workers fall within one of the four exposure gradients, with over a third (7.6%) of those falling in upper (Gradient 3 and Gradient 4) exposure categories.

Figure 3. Estimates of occupations potentially exposed to GenAI in Georgia (% of employment by sex)

Source: Authors’ calculations based on Geostat’s LFS data and ILO’s estimates of occupations’ AI exposure.

Notably, female workers in Georgia are more concentrated in higher-exposure occupations compared to men. Among female workers, 30% of positions fall within the exposure gradients, compared to 23% among male employees. The gap is particularly evident in the upper gradients – 9.1% of women are in gradient 3 and 1.5% in gradient 4, versus 4.1% and 1.1% of men, respectively.

Compared to the broader Europe and Central Asia region, where 32% of employees are exposed to GenAI (versus 26% in Georgia), Georgia has a lower overall AI exposure. Moreover, the distribution across gradients also differs. Among those exposed to GenAI, higher gradients (Gradient 3 and Gradient 4) represent a smaller share of total employment in Georgia, while lower gradients (Gradient 1 and Gradient 2) represent a larger share. This indicates that, compared to the Europe and Central Asia region, fewer workers in Georgia are employed in jobs prone to automation, whereas a larger portion of workers are in jobs with potential for augmentation. One likely explanation of low overall exposure to AI in Georgia is the structure of the Georgian labor market, where a substantial share (16.5%) of employment is in agriculture, which is largely insulated from AI and automation. As for the higher share of Gradient 1 and Gradient 2 in Georgia, it is primarily driven by employment in the service industries, as shown in the sectoral analysis below. Following agriculture, a significant portion (15.5%) of Georgian workers are employed in the trade sector, with a large share of employment falling within the first two exposure gradients, aligning closely with the notion of augmentation (Figure 4).

Exposure by Occupations

Table 1 represents the top 20 most exposed occupations, disaggregated by gender. The occupations with the highest automation scores are predominantly clerical, administrative, and routine office roles (e.g., Data Entry Clerks; Typists and Word Processing Operators; Statistical, Finance, and Insurance Clerks, Financial Analysts, Payroll Clerks, and others). Among the occupations most exposed to AI, where gender disaggregation is feasible based on representativeness criteria, many are observed to be female-dominated in Georgia (Table 1).

Table 1. Top 20 AI-exposed occupations (by Gender)

Source: Authors’ calculations based on Geostat’s LFS data and ILO’s estimates of occupations’ AI exposure. Note: The table presents gender disaggregation only for occupations with more than 25 survey participants to ensure data representativeness

According to Webb (2020), sectors with high shares of routine cognitive tasks, such as public administration, finance, education, and clerical services, typically feature a lot of communication-heavy, document-based, or repetitive analysis that is becoming increasingly feasible for generative AI tools such as ChatGPT and Copilot to automate or assist in. Especially clerical and administrative roles demonstrate a strong concentration of high exposure categories, which indicates a large share of activities – e.g., scheduling, documenting, and internal correspondence – can be effectively executed by AI systems.

Exposure by Sector

The sector-level exposure of Georgia’s labor force to GenAI reveals stark sectoral differences in exposure to AI-driven transformation. This analysis highlights NACE Rev.2 section-level economic activities that face the most significant automation risks or the potential for augmentation, as well as those largely insulated from GenAI.

As Figure 4 below illustrates, at the high-exposure end, Financial and Insurance Activities stand out.

Figure 4. AI-exposure by Sector

Source: Authors’ calculations based on Geostat’s LFS data and ILO’s estimates of occupations’ AI exposure. Note: A – Agriculture, forestry and fishing, B – Mining and quarrying, C – Manufacturing, D – Electricity, gas, steam, E – Water supply and waste management, F – Construction, G – Wholesale and retail trade, H – Transportation and storage, I – Accommodation and food services, J – Information and communication, K – Financial and insurance activities, L – Real estate activities, M – Professional, scientific and technical, N – Administrative and support services, O – Public administration, P – Education, Q – Human health and social work, R – Arts, entertainment and recreation, S – Other service activities, T – Households as employers, U – Extraterritorial organizations.

Although only 6.2% of jobs (1,660 out of 26,606 workers) fall into Gradient 4 (the very high exposure category to GenAI), this is the highest share among service sectors. When Gradient 3 is included, the combined high-exposure share is even larger, further distinguishing this sector. Close behind Financial and Insurance Activities, Professional, Scientific, and Technical Activities also register elevated risk, with 2.2% of workers in Gradient 4 and 19.4% in Gradient 3. The Information and Communication sector – often seen as being at the forefront of digital transformation – has 19% of its workforce in Gradients 3 and 4. However, the majority of workers fall under Not Exposed (33.0%) or Minimal Exposure (36.1%).

The lowest exposure is found in sectors dominated by manual labor and physical tasks. Agriculture, Forestry and Fishing, Georgia’s one of the largest employing sectors with around 225 thousand workers, is overwhelmingly shielded: 86.8% are not exposed, and only 0.1% fall into Gradient 4. Construction shows a similar pattern, with 60.9% (71,721 of 117,770) unexposed and just 1.2% (1,412) in Gradient 4. Transportation and Storage, and Mining and Quarrying also report high insulation, with 51.1% and 65.6% of their workforces not exposed, respectively.

Furthermore, as Figure 4 shows, the higher prevalence of Gradient 1 and Gradient 2 roles, aligning closely with the notion of augmentation, is largely attributable to employment in Georgia’s service industries. After agriculture, a substantial portion of the workforce is employed in the trade sector, where most jobs fall within the first two exposure gradients, indicating strong potential for augmentation.

Exposure by Gender

The analysis uncovers stark gender differences in exposure to generative AI in the Georgian labor market. A larger share of the women falls in the middle to high exposure categories as compared to men. This is especially important in domains like clerical work, customer service, and administrative support, fields where women are typically overrepresented.

As Figure 5 shows that more men hold occupations with little or no exposure, while a larger share of women hold jobs in the Gradients 3 and 4 categories.

Figure 5. AI-exposure by Gender

Source: Authors’ calculations based on Geostat’s LFS data and ILO’s estimates of occupations’ AI exposure.

In particular, women make up more than 60% of workers in the highest-exposure occupations, while men represent the large majority of workers in low-gradient occupations where AI-driven task substitution is less likely to have significant effects.

Exposure by Age and Education

Traditionally, education has been viewed as a means of shielding workers from technological displacement (e.g., Acemoglu and Autor, 2011; Autor, Levy, and Murnane, 2003). However, as Webb (2020) shows, artificial intelligence will affect the labor market very differently than previous automation and computerization in earlier waves (technologies like software and industrial robots), primarily by impacting high-skilled, high-wage occupations rather than low- or middle-skilled ones. As the author claims, highly educated workers (with college degrees, including Master’s degrees), higher-wage earners, and more experienced workers are most exposed to AI. Many tasks that require higher education – such as drafting legal documents, producing code, preparing reports, analyzing data, or writing content – are precisely the kinds of tasks GenAI can now perform or augment.

Analysis of Georgian labor market data demonstrates that a significant proportion of Georgian workers with bachelor’s or master’s level degrees are employed in occupations (administrative, legal, or financial services) with mid to high exposure gradients (Figure 6). Less educated workers tend to take occupations that are shielded from GenAI exposure.

Figure 6. GenAI-exposure by Educational Level

Source: Authors’ calculations based on Geostat’s LFS data and ILO’s estimates of occupations’ AI exposure.

Analysis by age categories reveals that younger, more digitally skilled workers generally occupy occupations currently more affected by generative AI (Figure 7). In contrast, older workers tend to be more represented in the “Not Exposed” categories. This reflects that individuals aged 55 and above are less likely to work in roles requiring computer use or modern digital technologies, with many in this group being pensioners who remain active in agriculture and other physically demanding jobs.

Figure 7. GenAI-exposure by Age Group

Source: Authors’ calculations based on Geostat’s LFS data and ILO’s estimates of occupations’ AI exposure.

Regional Disparities in Exposure

Exposure to generative AI varies significantly across regions of Georgia, with urban areas – particularly Tbilisi – exhibiting higher levels of exposure. Considering only urban areas, approximately 35% of Georgian workers face some level of exposure (from Gradient 1 to Gradient 4), of which 11% (86,852 individuals) fall into the medium- to high-exposure categories.

In contrast, rural and mountainous regions generally exhibit lower exposure. This is primarily due to the occupational pattern in these regions, which includes agriculture, manual labor, and low-digital service industries. Such jobs are less susceptible to generative AI as they heavily rely on physical labor that currently remains beyond the capabilities of current GenAI technologies. Figure 8 and Figure 9 below illustrate this distinction.

Unsurprisingly, among the urban areas, Tbilisi – home to roughly 32% of the workers – has the highest share of workers in Gradients 3 and 4 (moderate to high exposure) at 13%, followed by Kvemo- and Shida Kartli, with 12% and 10% of exposed workers, respectively. These two regions together employ around 17% of all workers in Georgia. Regions such as Kakheti and Samtskhe-Javakheti have the highest proportion of workers in the “Not Exposed” category, both in rural and urban areas, but these regions are hosting only 9% and 5% of all Georgian workers, respectively.

Figure 8. GenAI Exposure in Urban Areas

Source: Authors’ calculations based on Geostat’s LFS data and ILO’s estimates of occupations’ AI exposure.

Figure 9. GenAI Exposure in Rural Areas

Source: Authors’ calculations based on Geostat’s LFS data and ILO’s estimates of occupations’ AI exposure.

Conclusion

Our analysis, based on ILO exposure scores and Georgian labor market data, reveals that compared to other European and Central Asian countries, where highly GenAI-exposed occupations are more prevalent, Georgia faces a lower feasibility of AI-driven displacement, with greater opportunities for task augmentation. This pattern reflects the structure of the Georgian labor market, with a large share of employment in agriculture – largely insulated from GenAI – and significant employment in service industries, particularly trade, which predominantly falls within the lower exposure gradients closely aligned with the notion of augmentation. At the same time, the observed impact of Generative AI is uneven across gender, age, region, and education. Women, urban workers, and individuals with higher education in Georgia are disproportionately represented in high-exposure roles. In contrast, rural and older workers are less engaged in occupations exposed to GenAI. This is likely due to factors such as limited connectivity, lower levels of digital literacy, fewer training opportunities, and the nature of jobs available in rural areas. Interestingly, higher education increases exposure in some cases, as graduates tend to cluster in cognitively routine jobs that are more vulnerable to automation. Regional disparities are also pronounced, with Tbilisi showing the highest concentration of high-exposure occupations.

While the above raises a serious concern, it is important to remember that the exposure scores measure technological feasibility rather than actual displacement risk; the latter will be influenced by adoption rates, regulatory frameworks, and organizational decisions.

Further, GenAI does not only substitute for existing tasks; it is actively reshaping task composition and creating new roles. These include AI-specific occupations such as machine-learning engineers, prompt engineers, AI product managers, and AI ethics/compliance officers, as well as complementary roles that augment human work through human-AI collaboration and oversight. Evidence from Acemoglu et al. (2022) demonstrates rapid growth in AI-related job postings and shifts in hiring patterns, showing that AI adoption can simultaneously reduce demand in some occupations while boosting it in others. The overall impact depends critically on the approach to technology adoption and investments in complementary skills and institutional frameworks. At this stage, no research has systematically examined these trends in Georgia. However, some examples can be observed in practice. For instance, there are services offering training on the use of AI in labor relations, including the ethical application of AI in human resources. In addition, ICT-sector vacancies often list familiarity with new technologies among the required tasks and emphasize that employees should be aware of and actively follow technological developments, including advances in artificial intelligence. Taken together, these examples suggest that AI-related specialization may gradually expand in the Georgian labor market.

Taken together, these findings highlight that generative AI presents both a challenge and an opportunity for the Georgian labor market. While certain occupations face high exposure to GenAI that could disrupt existing employment patterns, other sectors may experience productivity gains and/or new job creation. The lower overall exposure and higher prevalence of lower-gradient, augmentation-aligned roles suggest that Georgia is positioned to leverage AI for complementarity rather than face widespread automation. Acting early is crucial to turn challenges into opportunities and to fully harness the augmentation potential across all occupations. For this purpose, investing in targeted upskilling and reskilling programs is important not only for workers in high-exposure roles, enabling them to adapt and transition, but also for those in lower-gradient occupations, to strengthen their ability to complement GenAI in their tasks and enhance productivity. At the same time, the analysis highlights that exposure is unevenly distributed across regions and demographic groups, therefore underscoring the need to address digital skill and gender gaps, connectivity challenges, and regional disparities.

References

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.

Improving Women’s Political Representation Beyond Gender Quotas

Posted on October 20, 2025 | Policy Brief

Women waving Turkish flags during a political rally, symbolizing support for Political Representation Gender Quotas in Turkey.

While gender gaps in politics have narrowed considerably in recent decades, large disparities remain in several countries, especially those where binding gender quota laws have not been adopted. What are alternative pathways for increasing women’s political representation in these countries? We investigate one such pathway in the context of Turkey. A conservative dominant party, Erdogan’s AKP, is often challenged in local elections by a Kurdish party that promotes gender equality in electoral lists and in society more generally. Exploiting variation in Kurdish party wins in municipal elections during 2009-2019, we find that the Kurdish party winning leads AKP to increase its share of female candidates by 25 to 30% in the next election. Our data suggests that AKP’s response is primarily motivated by strategic considerations aimed at appealing to voters who may value gender-balanced representation. The implications of these findings extend beyond Turkey, suggesting that one party empowering women can help reduce gender gaps in lists across the board.

Pathways to Gender Equality in Political Participation

Across the world, women have historically been underrepresented in political institutions, but considerable progress has been made in recent decades. Legislated gender quotas are credited for having contributed significantly to such progress, especially in developing countries (Berevoescu and Ballington, 2021). Across different contexts, well-designed quotas have been shown to successfully increase the share of women in electoral lists and, although to a lesser extent, in legislative and leadership positions (see Campa and Hauser, 2020 for a review of this literature).

Research also suggests that the electoral system could influence women’s political participation, with more women being elected under proportional rather than majoritarian systems (Profeta and Woodhouse, 2022) and, within proportional systems, through closed rather than open lists (Gonzalez-Eiras and Sanz, 2021). Moreover, recent findings suggest introducing term-limits as a tool to boost women’s electoral prospects (Kansikas and Bagues, 2025).

However, despite the positive trends worldwide, large gender disparities in political representation persist in many countries. Some of the most entrenched inequalities are found in states governed by authoritarian or semi-authoritarian regimes promoting conservative values, where legal reforms to enhance gender equality are unlikely. For instance, the map in Figure 1, which assigns lighter shades of blue to countries where gender gaps in political empowerment are larger, shows that across Europe and Central Asia, four of the five lowest scoring countries are authoritarian or semi-authoritarian, namely Azerbaijan, Kazakhstan, Hungary and Turkey, which Freedom House ranks as “partly free” or “not free”.

Figure 1. Gender gaps in political empowerment

Source: World Economic Forum. Gender Gap Report 2025. Note: The figure shows country scores on the World Economic Forum’s Political Empowerment Index. Lighter shades of blue indicate a larger gender gap in political empowerment.

What are alternative pathways that may increase women’s political participation in such contexts, where gender quotas and other representation-enhancing electoral reforms are unlikely to be introduced?

In recent work – Campa et al. (2025) – we study one such pathway in the case of Turkey, namely the emergence of a competitive, albeit not dominant, party that commits to gender equality in lists and beyond.

Women’s Political Participation in Turkey

Despite early enfranchisement — municipal voting rights in 1930 and full suffrage in 1934 — women’s political representation in Turkey remains low. Women are severely under-represented in Parliament at around 20% after the 2023 elections. Turkey is also one of the 24 countries worldwide where women’s representation in local governance is below 15% (World Economic Forum). The share of female mayors was less than 0.5 percent between 1930 and 2004 (Koyuncu and Sumbas, 2016), with a minor increase observed since 2005. During this period, the share of female candidates in electoral lists for the municipal council also increased by 6 p.p., and the share of female councillors increased by 5 p.p., but as of 2019, these shares were still severely low, at, respectively, 14 and 12%.

AKP Versus the Kurdish Party

The under-representation of women in local governance masks stark differences between parties, especially between the ruling party, Erdogan’ Justice and Development Party (AKP henceforth), and one of the main opposition parties in local elections, the Kurdish party, which ran in 37% of the elections held between 2009 and 2019 and won 19% of them.

AKP is ideologically conservative and with a religious base. During the 20 years in power, it passed no law to increase women’s representation in politics, despite the vast gender gaps at all levels of government.

The Kurdish party instead stands out in the Turkish political landscape for its commitment to gender equality in many areas of society, including politics. For instance, currently the party pledges to enact a gender-mixed co-leadership system at the party level as well as a “zipper quota” in its electoral lists, and more generally advocates for a gender equal society “starting with the local governments” (see the party’s official website). Both the mixed-leadership system and a version of the candidate quota have been in place for two decades.

As a result, the share of female candidates for the municipal council is much higher in electoral lists associated with the Kurdish party, at 21% on average over the period 2009-2019, as compared to AKP’s 11%. The Kurdish party’s share of female candidates is also remarkably high in comparison to the other major opposition party, the Republican People’s Party (CHP henceforth), which averages 13% female representation in its local electoral lists. The higher feminisation of the Kurdish party’s lists is reflected in the share of women elected: on average, only 6% of the councillors elected with AKP are women; this number goes up to 12% for CHP and jumps to 28% for the Kurdish party (see Figures 2 and 3).

Figure 2. Female share in candidate lists in municipal elections in Turkey.

Source: Author’s calculation based on own digitisation of data released by Turkey’s Higher Election Council (YSK). Note: The figure shows the share of women in candidates’ lists for the election of municipal councillors by party, focusing on the major party that governs at the central level (AKP) and its two main competitors at the local level (CHP and the Kurdish party).

Figure 3. Share of women elected as municipal councillors in Turkey, by party.

Source: Author’s calculation based on own digitisation of data released by Turkey’s Higher Election Council (YSK). Note: The figure shows the share of women elected as municipal councillors by party, focusing on the major party that governs at the central level (AKP) and its two main competitors at the local level (CHP and the Kurdish party).

We also note that the Kurdish party tends to elect a much larger share of female mayors than its competitors. According to the High Election Council (YSK) Election Statistics, in the 2009, 2014, and 2019 elections, the share of female mayors elected by the Kurdish party was respectively 21, 30, and 45%, whereas AKP elected less than 1% of female mayors in 2009, and this percentage remained stable at 1% in the 2014 and 2019 elections.

The Effect of a Kurdish Party’s Win on AKP’s Behaviour

Against this background and given the recent improvement in the share of female candidates across all parties (see Figure 2), we ask whether a Kurdish party victory prompts AKP to improve the gender equality in its lists in subsequent elections. By studying this question, we hope to contribute to shedding light on the forces that might help close gender gaps in political representation in relatively traditional societies governed by authoritarian or semi-authoritarian governments, where the under-representation of women in political institutions is particularly severe and gender quotas are unlikely to be adopted.

Using a novel dataset covering municipal council elections in Turkey in 2009, 2014, and 2019 —including candidates’ gender —we exploit within-municipality variation in Kurdish party victories to identify their impact on AKP’s female candidates’ share. We find that a Kurdish party win leads to a 2.8 to 3.4 p.p. increase in AKP female share of candidates in the next election, representing a 25–30% increase from a baseline of 11 p.p.; the estimate is robust across different econometric specifications, and we document that AKP lists were not on a differential trend in terms of share of female candidates in places where the Kurdish party wins – in other words, the increase in female candidates is only subsequent to the Kurdish party victory, strongly suggesting that it is indeed the result of AKP’s response to the growing popularity of the Kurdish party, and not the product of a secular trend of growing women’s representation. We also find that a win from another major opposition party, CHP, prompts smaller and only marginally statistically significant increases in female representation, suggesting that it is not just electoral competition that would force AKP to improve the selection of its candidates, but the Kurdish party’s gender focus that matters.

Why does AKP respond to a Kurdish victory by increasing its share of female candidates? Its behaviour could be strategic — appealing to voters who appear to care about some form of gender balance in lists — or stem from learning through exposure to capable female councillors. To gauge the relative importance of these different explanations, we exploit a special feature of the Turkish electoral system, namely parties submitting, together with the “main” list of candidates to be selected by voters, a “special quota” list containing the candidates directly assigned to the municipal council by the party if it wins the plurality vote. Such a list is not very salient to voters, and often not visible to them. We find no increase in women on AKP’s special lists after the Kurdish party wins, indicating the motive is likely an electoral strategy rather than internal reform.

Conclusion

Across the world, women have historically been underrepresented in political institutions. While gender gaps in political participation have narrowed considerably in recent decades, particularly due to the adoption of gender quotas, large disparities remain in many countries. Some of the most entrenched inequalities are found in states governed by authoritarian or semi-authoritarian regimes, where legal reforms to promote gender equality in politics are unlikely. Understanding alternative pathways for increasing women’s political representation in these contexts is a pressing challenge. We investigate one such pathway in the case of Turkey.

Although the ruling party, AKP, has remained resistant to gender-based reforms, it has increasingly faced local-level competition from a Kurdish party that consistently champions gender equality. Leveraging a new dataset covering municipal council elections in 2009, 2014, and 2019, we find that when the Kurdish party wins a municipality, AKP increases the share of female candidates in its master list by approximately 25 to 30% in the subsequent election.

The implications of these findings extend beyond the Turkish case. In political systems where institutional reform is unlikely, competitive pressure from parties that prioritise gender equality can still drive changes in political behaviour. Even without quotas, such parties can shift norms and electoral expectations, thereby inducing rival parties to adopt more inclusive practices.

References

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.

How the Combination of Income and the Quality of Local Conditions Affects Well-being in Old Age

Posted on October 13, 2025 | Policy Brief

Elderly couple sitting on a park bench, enjoying a peaceful moment together, symbolizing financial stability and income well-being in Poland.

Contemporaneous income and the quality of local living conditions have both received recognition in the literature as important determinants of subjective well-being. However, little is known about their joint impact and the possible moderating influence each may have on the relationship with the well-being of the other. In a recent study (Myck et al. 2025), we investigated the role of income and quality of local area on different dimensions of well-being of older adults in Poland. Our findings show that a higher quality of local conditions amplifies the association between income and well-being, which implies that high-income older individuals tend to benefit more from improved local conditions. Our findings suggest that low incomes may constrain older people from taking advantage of local public services, and thus draw attention to policies aimed at improving access to these services, especially in low-income, peripheral areas. While the results also point towards broad benefits of targeted income transfers, it is notable that their effective translation into higher well-being strongly varies with the quality of municipal local conditions.

Introduction

As most developed countries face rapid population ageing, governments continue to seek effective policies to support older adults. Identifying effective policy solutions remains vital in supporting different population groups, including the growing group of older citizens. In this brief, we present a summary of results from a recent study (Myck et al. 2025), in which we examine the role of the combination of incomes and local conditions for the well-being of older individuals. The analysis is conducted on data from Poland, a country characterised by rapid population ageing and a recent prioritisation of monetary transfers in the policy mix, with much less attention given to the financing of local and centrally funded public services. The analysis aims at understanding the role of the quality of local conditions for the well-being of older individuals, and at identifying how the level of income modifies this role. In other words, we examine if higher income affects individual well-being differently in high- compared to low-quality regions.

Subjective well-being has for a long time been examined in relation to individual socio-economic characteristics, like education, health, material conditions and social relations (Layard 2006, Dolan et al. 2008). Many authors have also stressed the importance of the local environment and the quality of public services (Aslam and Corrado 2012), although the influence of local conditions on well-being has been documented mostly at high levels of aggregation (countries or large sub-national regions; Perovic and Golem 2010; Colombo et al. 2018). Principally, though, the combined implications of local conditions and the material situation at the individual level on well-being remain largely underexplored. In our study we explore granular local conditions at the level of municipalities, allowing us to examine the relationship accounting for significant within-country differences in a shared institutional framework. Such disaggregation seems especially important in analysing the quality of life of the older population due to the likely relevance of local health and care services, high-quality transport options, local safety, green spaces and other public services.

Individual and Local Factors

To examine the direct and moderating roles of local conditions on well-being and their relation with income, we rely on a combination of individual- and local-level data (for methodological details, see Myck et al., 2025).

The individual-level data comes from the Polish part of the Survey of Health, Ageing and Retirement in Europe (SHARE). This dataset provides detailed information on health, labour market activity, material situation and social relations of individuals aged 50 years and above for almost all European countries. In addition to the usual socio-demographic information (age, gender, education, marital status, and income), SHARE collects several self-reported measures of physical and mental health, as well as a number of broad dimensions of quality of life. One such measure is CASP, which aims to capture the quality of life among older individuals in four important dimensions:  Control, Autonomy, Self-realisation and Pleasure. With twelve questions (three for each dimension), each participant evaluates how often they feel in a certain way or experience certain situations. The final outcome is a summed score in the range of 12 to 48, with higher values indicating a higher quality of life.

For the purpose of our analysis, the individual dataset has been augmented with regional-level information. To capture as much variation in the quality of local conditions as possible, we rely on 14 indicators collected either at the municipal or county level (respectively, the bottom and middle tiers of the administrative division of Poland). They represent the quality of localities in terms of economic factors, housing infrastructure, green spaces and health services. Given the high correlation between these regional variables, they have been combined into a single local quality index using principal component analysis (PCA). The index is calculated on the municipality level, with higher values representing better quality of local conditions. Figure 1 below shows the spatial distribution of the index across all Polish municipalities, highlighting significant regional differences in the local quality of life in Poland, particularly between the Western and Eastern parts of the country.

The Role of Income and Local Conditions for Individual Well-being

We examine the relationship between well-being, contemporaneous household income, and local conditions in a panel random effects regression, controlling for an extensive vector of covariates. Our results confirm a strong positive association between income and well-being, with a 100 per cent increase in disposable income corresponding to increases of up to 0.66 points on the CASP scale. While this may seem small, given the scale of the CASP measure, the effect is similar to that of being employed relative to being retired (0.56 CASP points), married relative to being widowed (0.78), and very close to the average difference in CASP between men and women, conditional on other controls (0.57).

Figure 1. Distribution of the index capturing the quality of local conditions at the municipality level in Poland

Note: Municipality borders are in white, regional borders in yellow. Source: Myck et al. (2025).

We also find that the regional index is positively correlated with well-being. Importantly, though, since income and the quality of regional conditions are strongly correlated, we examine the importance of their interaction in the well-being regression. This facilitates the investigation of the differential reaction of well-being to income for different values of the index (and vice versa). In Figures 2a and 2b we present average marginal effects of each one of the variables as calculated at different percentile levels of the other.

The results indicate noticeable variation in the strength of the association between income and well-being, depending on the quality of local conditions (Fig. 2a). Income seems to matter little at the lower end of the distribution of the regional index and much more in localities of better quality.

Figure 2. Average marginal effects (AME) of income and the regional index on well-being

a) AME of log(Income) across distribution of the regional index

b) AME of the regional index across the distribution of log(Income)

Note: Figures show point estimates of AMEs and the corresponding 90% confidence intervals. Well-being is measured with a CASP score of 12-48. Source: Myck et al. (2025).

While the growing role of income as local conditions improve might seem surprising, it well aligns with the fact that consumption of some publicly provided goods and services is dependent on or related to income: apart from the obvious examples such as culture, more important dimension of access to public services might relate to the areas where rich and poor people live, the quality of public transport and easy access to highly localized public services.

Strong positive effects of regional quality on well-being are also observed among respondents with the highest incomes (Fig. 2b). The association for low-income individuals cannot be statistically differentiated from zero.

Conclusion

The results of our study suggest that for high-income older individuals in Poland, better local conditions are reflected more strongly in their well-being compared to that of low-income residents. For the poorest older individuals, improvements in local conditions have little or no bearing on their well-being. At the same time, increases in income are associated more strongly with well-being in areas with the highest levels of quality of local conditions.

The policy implications of our results thus highlight the detrimental consequences of the combination of low income and poor quality local conditions for individual well-being and the challenges to improving the latter. Our results suggest that effective policies aimed at increasing the well-being of older adults require a careful combination of direct and indirect measures, or otherwise a combination of support focused on income transfers with provision of, and better access to, the relevant range of public goods and services.

Our results also point towards targeted rather than simple universal income transfers: greater income increases are needed in low-quality areas compared to top-quality ones to secure the same change in well-being. Moreover, the fact that local quality translates differently into well-being for the rich and the poor suggests that there are significant disparities in access to local services by income level. This, in turn, calls for developments in access and mobility opportunities and investments in local public services to ensure better access to these services among low-income residents. Local policies in high-quality areas should become more sensitive to the needs of poorer older inhabitants, while improvement of local conditions in low-quality regions needs to accompany direct transfer policies for these to effectively translate into a higher quality of life of older individuals.

Acknowledgement

The authors acknowledge the support from the Swedish International Development Cooperation Agency, Sida.

The original study (Myck et al. 2025) was financed through a joint grant of the Polish National Science Centre (NCN, project no: 2018/31/G/HS4/01511) and the German Research Foundation (DFG, project no: BR 38.6816-1) in the international Beethoven Classic 3 funding scheme (project AGE-WELL).

References

  • Alesina, A., Di Tella, R. and MacCulloch, R., 2004. Inequality and happiness: are Europeans and Americans different? Journal of Public Economics, 88 (9–10), 2009–2042.
  • Aslam, A. and Corrado, L., 2012. The geography of well-being. Journal of Economic Geography, 12 (3), 627–649.
  • Colombo, E., Rotondi, V. and Stanca, L., 2018. Macroeconomic conditions and well-being: do social interactions matter? Applied Economics, 50 (28), 3029–3038.
  • Myck, M., Oczkowska, M. and Kulati, E., 2025. Income and well-being in old age: The role of local contextual factors. The Journal of the Economics of Ageing, 30, 100551.
  • Perovic, L. M. and Golem, S., 2010. Investigating Macroeconomic Determinants of Happiness in Transition Countries: How Important Is Government Expenditure? Eastern European Economics, 48 (4), 59–75.
  • Rossouw, S. and Pacheco, G., 2012. Measuring Non-Economic Quality of Life on a Sub-National Level: A Case Study of New Zealand. Journal of Happiness Studies, 13 (3), 439–454.

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.

Towards European Union Membership: Poland’s EU Pre-accession Funds and Infrastructure Development

Posted on October 6, 2025 | Policy Brief, Policy Papers

European Union flag waving during a public demonstration, symbolizing support and integration efforts related to EU Pre-Accession Funds.

In advance of formal membership, candidate countries are offered three pillars of EU assistance: trade concessions, stabilization and association agreements and financial support. These instruments aim both to prepare candidates economically, politically and administratively, and to signal accession’s benefits to their populations. In this paper we describe the channels in which the third pillar – the EU pre-accession funds – affected Poland’s economic and institutional development ahead of its 2004 membership. The funds were designed to accelerate institutional transformation, modernize agriculture, strengthen rural communities, improve transport networks, and promote environmental protection. In Poland, between the mid-1990s and 2003, they supported extensive investments that produced unprecedented improvements in technical infrastructure. Poland’s accession referendum in 2003 turned decisively in favor of EU membership, despite strong regional variation in support. While no causal evidence is available, we argue that without the EU-funded infrastructural transformation, its outcome would have been less certain. For current EU candidate countries, Poland serves as an excellent example of how targeted external financial assistance can support structural transformation ahead of integration with the EU.

Introduction

Seven countries are currently eligible to receive financial support through the European Union’s Instrument for Pre-Accession Assistance (IPA III): Albania, Bosnia and Herzegovina, Kosovo, Montenegro, North Macedonia, Serbia, and Türkiye. The funding allocated within the program for the 2021–2027 period amounts to 14.162 billion EUR (in 2021 prices; European Commission, 2024). IPA III is the successor to the former two IPA editions, which have provided support exceeding 24 billion EUR since 2007 to countries in the then EU enlargement region. IPA aims to support countries that have entered a pathway to EU membership, expected in the foreseeable future, to facilitate progressive alignment with EU rules, values, and various standards and policies enforced in the European Union before they become full members. It constitutes one of the pillars of assistance offered by the EU to countries with a prospect of membership, with trade concessions and stabilization and association agreements (SAAs) serving as the other two.

Next in line to obtain financial help through the pre-accession funding are Moldova and Ukraine, both of which were granted candidate status by the European Council fairly recently. While they have already started their accession negotiations and may benefit from trade concessions and SAAs, they still need to fulfill certain requirements to be eligible for IPA. Though formally also a candidate since late 2023, the accession process of Georgia is currently suspended due to concerns about democratic backsliding, implementation of controversial laws and disputed parliamentary elections.

In this paper, we examine Poland’s experience in utilizing the funding available prior to the 2004 EU enlargement to undergo important structural and systemic changes. Given the goals of the funding, we discuss the evolution of a number of economic indicators which can serve as evidence of the socio-economic advancement that occurred in Poland in the years leading to its EU accession. These examples illustrate different dimensions of development that societies in countries embarking on the EU accession process could benefit from on their way towards full integration.

EU Pre-accession Funding Options in the 1990s

Together with nine other countries, mainly from the Eastern European region and the former communist bloc (Cyprus, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Slovakia, and Slovenia), Poland joined the EU in 2004. It was the largest enlargement of the European community both in terms of the number of new countries and population-wise.

On the pathway to EU membership, these candidates benefited from a coordinated set of financial instruments designed to accelerate their political, economic, and institutional development. During the 1990s and early 2000s, three programs offered financial assistance: Phare, SAPARD, and ISPA. Each addressed a different strategic challenge that candidates faced during their accession period – many of which underwent the transition from centrally planned to free market economies.

From the pool of soon-to-be EU members, Hungary and Poland were the first among the post-communist Central and Eastern European countries to formally start the accession process as early as 1994 (Cyprus and Malta applied in 1990). These two countries also inaugurated the distribution of financial assistance among the EU applicants. They became the first beneficiaries of the Phare program, which concentrated on supporting public administration reform, improving institutional capacity, and preparing regions for effective absorption of EU structural funds. It also helped modernize local infrastructure and provided targeted assistance to sectors undergoing major restructuring. Phare was soon extended to cover all other candidate countries.

The second initiative – SAPARD, concentrated on the needs of the agricultural sector and rural communities. The goal was to raise the competitiveness of local farming and modernize food production.

The third program, ISPA, funded major environmental and transportation initiatives.

These three programs helped close the gap between the candidate countries and older EU member states by improving infrastructure and enhancing the functioning of their institutions. Formally, they also helped ensure that the new members met EU strict standards and legal directives and built the foundations for their long-term cohesion. More detailed descriptions of the objectives of each program, with a special focus on Poland, are included in Box 1.

Figure 1 presents the annual expenditures between 1990 and 2003 within each of the three analyzed instruments provided by the European Union to Poland (bars, left axis). With connected lines, we show the scope of each program in cumulative amounts over time (right axis). During the 1990s, the budget spent on Poland under the Phare program was kept under 200 million EUR annually (in the last year of the decade, it increased to almost 300 million EUR). However, after the program’s restructuring since the beginning of the 2000s, annual spending through this instrument doubled. Among the three, Phare was the major funding source for Poland, as the country received a total of 3.5 billion EUR until 2003 (equivalent to 1.9% of the Polish GDP in 2003) – almost five times more than under the SAPARD program. Poland also obtained the highest total amount of funding of all candidate countries at the time, corresponding to 30% of the overall provided financial assistance (Kawecka-Wyrzykowska & Ambroziak 2006).

Figure 1. Values of  EU pre-accession funds in Poland

Source: Own compilation based on Tables 3, 4, 6 from Kawecka-Wyrzykowska & Ambroziak (2006). Note: in 2003 prices.

In 2000, ISPA and SAPARD were introduced to further support specific areas identified during the 1990s as critical and requiring targeted funding – the agricultural sector, initiatives to enhance the transportation network, and environmental protection. Through SAPARD, projects related to farming and rural infrastructure received approximately 150 million EUR per year in Poland, accumulating to 700 million EUR over the four-year period until 2003. Since one of the prerequisites in SAPARD was national co-funding of ca. 25% of the public contribution in the investments, overall 1.1 bn EUR (0.6% of the 2003 GDP) of public money was committed to different projects in Poland through this instrument (ARiMR 2025; investments consisted in 50% of private resources).

Projects supported within ISPA on average obtained 300 million EUR annually in Poland, with total spending reaching 1.4 billion EUR until 2003 (0.8% of the 2003 GDP). Poland was still the major beneficiary of these two types of financial support, though the total share of the funding received within each of them was much lower than in the Phare program, respectively 32% in SAPARD and 34% in ISPA (Kawecka-Wyrzykowska & Ambroziak 2006).

 

Box 1. Financial instruments offered in the 1990s on the pathway to EU membership: Phare, SAPARD, ISPA

Originally known as Poland and Hungary Assistance for Restructuring of the Economy, Phare was launched in 1989 at a pivotal moment in European history. Initially designed to support the two countries in their transition from communism to democracy and a market economy, Phare quickly expanded to cover other parts of Central and Eastern Europe. Its mission was not only to help rebuild economies, but also to support political democratization. At first, it operated through national programs, but as regional cooperation gained importance, Phare introduced international initiatives to foster cross-border collaboration. The evolving challenges faced by the transforming countries led to a significant change in the program’s operation in the late 1990s. Financial support was now focused on two main pillars: investment in essential infrastructure, which consumed about 70 per cent of resources, and institutional development, which received the remaining 30 per cent. Poland benefited from several specialized initiatives within Phare. Socio-Economic Cohesion focused on modernizing regional infrastructure and preparing Polish regions to efficiently absorb EU structural funds. Cross-Border Cooperation strengthened ties between Poland and its neighbors. Institutional Building contributed to more efficient and transparent public administration.

The Special Accession Program for Agriculture and Rural Development, SAPARD, was established in 1999 to help transform the agricultural sectors and rural economies of ten countries aspiring to join the EU at the time. The goal was to prepare farmers and food processors to meet strict EU sanitary and veterinary standards. In Poland, SAPARD played a major role given the country’s vast rural landscape and the important role of agriculture in the economy – accounting for 7% of the GDP in 1995 (CSO 2014). Around 75% of the total budget was allocated from EU funds, with the remainder covered by national co-financing. However, the rules required an own contribution from each beneficiary, thus around half of the total value of all investments realized through SAPARD was private capital (Supreme Audit Office, 2002). SAPARD in Poland focused on, on the one hand, the modernization of agriculture and, on the other, on rural development. A large part of the program went into modernizing agricultural holdings, supporting farmers in buying new machinery, improving farm buildings, and upgrading agricultural production to meet EU standards. Equally important was the modernization of food processing industries, like meat, dairy, fruits and vegetables. Another significant part of the program concentrated on infrastructure in rural communities — building roads, sewage systems, and improving basic services. To encourage economic diversification, assistance was provided to develop non-farming businesses and create new job opportunities outside of agriculture (EU Council, 1999a).

Created in 1999, the main goal of ISPA was to finance large-scale projects in two critical sectors: transportation and environmental protection. Projects selected for funding were typically expensive, exceeding 5 million EUR, and had a strategic, national or at least regional impact (EU Council, 1999b). From the society’s perspective, these initiatives improved living standards, protected public health and the natural environment and promoted sustainable development. In the environmental sector, ISPA focused mainly on critical areas, including improving the quality of drinking water, building modern sewage treatment plants, managing waste more efficiently, and reducing air pollution. Given the EU’s strict environmental directives, addressing these issues was a fundamental condition for accession. ISPA concentrated also on modernizing and expanding major roadways and railway lines, especially those which were signified as part of the Trans-European Transport Network. Improved transport connections facilitated trade, mobility, and regional development, essential for increasing economic competitiveness and tightening of physical linkage with the rest of Europe.

The total amount of received funding was only one of the factors that may have played a role in the scope and pace of overall socio-economic changes in Poland. Importantly, the spatial distribution of investments provided a unique opportunity to reduce the geographical inequalities deeply rooted in Polish history and related, in particular, to the partitions of Poland lasting from the late 1700s till the end of World War I (Becker et al. 2016; Grosfeld & Zhuravskaya 2015). The eastern regions of Poland were historically much less developed, with the agricultural sector maintaining a critical position in economic activity and employment.

To illustrate the differences in regional distribution of the funding, we use a number of indicators related to investments realized with the help of the SAPARD instrument – which was specifically targeted at supporting infrastructure in rural areas and advancements in the agricultural sector. In Figure 2, we present three measures of investment allocation – the total (public+private) value of investments completed in each region (a), total value of investments per capita (b), and per hectare of agricultural land (c). Depending on the analyzed indicator, we obtain a slightly different picture of the distribution of the investments in SAPARD throughout the country. It appears that the Western regions of Poland received the least funding from SAPARD, whereas the Eastern and most rural regions were less successful in securing the funding. In all three cases, though, the Wielkopolskie Voivodship – a region in the Central-Western part of Poland – stands out as the one that collected the highest funding not only overall, but also when calculated per inhabitant or, most crucially, per area of agricultural land.

Figure 2. Spatial distribution of the SAPARD investments in Poland, total amount (public+private) for the period 2000-2003

Source: Own compilation based on Table 7.2 from Rudnicki (2008). Note: Converted from PLN to EUR using 4PLN/EUR exchange rate; c) per hectare of agricultural land. As compared to Fig. 1 the amounts for SAPARD include private resources spent

The most likely reason behind the particular allocation of the funding is related to the application process. The total amount of the funding was granted to Poland with limited distributional guidelines, and the funds were allocated on the first-come, first-served basis (ARiMR 2003). The maps in Figure 2 suggest that farmers, agricultural producers and manufacturers, and rural municipalities in Wielkopolskie region were quick and efficient when it came to funding applications. The scale and scope of the investments, though – looking at the three different measures – shows the flow of substantial benefits to all central and eastern regions.

Infrastructural Metamorphosis of Poland in the 1990s

As described above, an exceptional stream of additional funds from the EU was directed to Poland from the early days of its transition. The funding programs evolved with time during the 1990s and became more specialized closer to EU accession to address the specific needs of the candidate countries. While causal evidence of the impact of EU pre-accession funds on evolving infrastructure remains scarce and is methodologically challenging (with just a few exceptions on more recent pre-accession funding schemes, like Denti 2013), a simple overview of a number of key indicators might serve as strong suggestive evidence that the funds actually made a significant difference. In this part of the paper, we take a closer look at some examples of Polish infrastructure that underwent enormous progress in the late 1990s and early 2000s. We stipulate that the EU funding played a crucial role in the acceleration of this development.

All three analyzed EU instruments – Phare, SAPARD and ISPA – shared some common objectives, for instance, increasing access to clean water in the population, reducing pollution in lakes, rivers, and the sea, and improving road conditions, especially the low-rank ones in remote, rural areas. In Figures 3-5, we present the scale of improvement observed in these three areas on the lowest level of regional disaggregation, namely, in Polish municipalities. We compare the three selected indicators over almost a decade, between 1995, the initial year of data availability, and 2004.

We begin with Figure 3, which depicts the expansion of the water pipe network measured in kilometers per 1,000 inhabitants in each municipality. As specified in the legend, the darker the green category, the higher the density of the water pipe network. The rapid expansion of the network between 1995 and 2004 is evident, especially in some parts of the country. Most often, the upgrade to the top category happened in regions that lagged well behind the rest of the country in 1995. Here, the notable examples are the central regions of Poland (Kujawsko-Pomorskie and Lodzkie Voivodships, including the northern part of the Mazowieckie Voivodship) and the north-eastern frontiers (Podlaskie and Warminsko-Mazurskie Voivodships).

Figure 3. Length of the water pipe system (in km) per 1000 inhabitants in Polish municipalities in 1995 and 2004

Source: Own compilation based on the statistics from the CSO Local Data Bank (BDL); Geodata: National Register of Boundaries (PRG). Note: The legend is based on 2004 data: the two top and bottom categories in the legend cover 10% of observations each, and the rest of the categories cover 20% of observations each. Municipality borders marked in white, voivodship borders in yellow. Poland underwent an important administrative reform in 1999, when 49 voivodships were aggregated into the current 16. For the year 1995, we use the post-reform voivodship division of the country. Between 1995 and 2004, only negligible administrative changes took place at the municipal level.

In Figure 4, we show the share of the population enjoying access to sewage treatment plant services. The progress over time in this respect was related, on the one hand, to the construction of new treatment facilities and, on the other, to the concurrent expansion of the sewage pipeline network, which resulted in a higher share of users for the existing wastewater treatment plants. The increase in the usage of the treatment plants over time is striking, especially given that at the starting point, in 1995, only a limited number of municipalities had a wastewater treatment plant in operation. These municipalities were mainly concentrated in the northwestern corner of Poland and in the southwestern region of Silesia.

In comparison to the water pipe system in Figure 3, the development of sewage treatment plant access was concentrated in regions that were already ahead of the rest of Poland in 1995 – specifically, the northwestern and southwestern ones. However, a substantial increase in access to sewage treatment services is also visible in central and eastern parts of Poland, where in 1995 plants offering these services were extremely rare. This particular type of development can also be viewed from the perspective of the extent of pollution reduction in Poland’s internal waters. The number of scientific reports documented a sharp decline in biochemical factors of industrial, agricultural and household origin, hazardous to both humans and the environment, commonly polluting Polish rivers and lakes in the 1990s (Gorski et al, 2017; Marszelewski & Piasecki, 2020).

Figure 4. Number of residents connected to sewage treatment plants per 1000 inhabitants in Polish municipalities in 1995 and 2004

Source: see Figure 3. Note: The legend is based on 2004 data: due to high prevalence of zeros the bottom category in the legend covers 30% of observations, the rest of categories cover 10% of observations each. Municipality borders marked in white, voivodship borders in yellow (see Notes in Figure 3 for details).

The third pair of maps (Figure 5) illustrates the development of the country’s road network. The Figure shows the expansion and modernization of the lower rank roads administered by municipalities, which seem particularly important from the point of view of day-to-day transportation and quality of life of local populations.

Figure 5. Length of the municipality road network (in km) per 1000 inhabitants in Polish municipalities in 1995 and 2004

Source and Note: see Figure 3.

The data in Figure 5 cover both paved or hard-surfaced roads and dirt roads. One point to keep in mind here is that with an overall development of a municipality and of the neighboring region, the status of the municipality’s small-scale road may be updated to a higher rank, administered by the county or even by the voivodship. Figure 5 does not account for such an update of rank (in the Figure of roads), so the numbers presented are likely to represent a lower bound of the actual advancement. The maps in Figure 5 compare the length of municipal roads per 1000 inhabitants in 1995 and 2004. While a significant improvement in the road system is visible almost all over the country, the central regions seem to have gained the most, at least when it comes to this particular type of roads.

Investments and Development vs. Public Perception

Overall, all three figures above demonstrate that during the decade before Poland integrated with the EU, significant progress was achieved in terms of improving the quality of life, increasing accessibility of public utilities, reducing environmental degradation and capturing sustainable urban development. Substantial investments in rural areas had an important impact on reducing regional disparities.

Another important observation when examining all three figures together is that, while advancement occurred throughout the country, the bulk of improvement in each of the considered aspects was concentrated in slightly different parts of it, and almost all Polish municipalities recorded an important inflow of investments related to the pre-accession funding. While again we cannot provide any causal evidence, below we confront the spatial distribution of infrastructural modernization from Figures 3-5 with public support for joining the EU expressed in the referendum organized in 2003, a year before accession.

Figure 6. Support for the EU accession in the referendum in 2003

Source: Own compilation based on the statistics from the National Electoral Commission; Geodata: National Register of Boundaries (PRG). Note: The bottom category in the legend covers municipalities that voted against EU integration (12.3% of observations), the rest of the categories cover 25% of the remaining observations each. Municipality borders marked in white, voivodship borders in yellow.

In Figure 6, we present the results of the vote on the municipal level, with darker blue shades indicating higher support for EU membership. The map clearly highlights high geographical variation in support for European integration, with much stronger proportions of votes in favor of EU membership in western and northern Poland. In contrast, the support in central and eastern Poland was substantially lower, reflecting a higher degree of skepticism towards the benefits of the EU. Clearly, many factors influenced people’s choices at the time of the referendum. They depended on their economic conditions, the degree of exposure to relations with Western European countries, the level of awareness of the potential gains from integration, as well as fears concerning the future of local economies and those related to cultural influences.

Just by looking at the map of support, it is impossible to say much about the degree to which the EU pre-accession funds affected the outcome of the referendum. For that, we would need to know more about the dynamics of support across regions. Yet, while the share of votes in favor of integration in many eastern municipalities was below 50%, people in a substantial majority of localities expressed overwhelming support for joining the EU. The result of the referendum was 77,45% in favor. Although no causal analysis linked the results to EU pre-accession funds, the scale of investment and its visibility, as well as its tangible effects – the direct translation of EU funds into daily quality of life all across Poland, are very likely to have turned many people’s votes in the EU’s favor.

Conclusion

Since the early 1990s, on the path to EU membership in 2004, Poland, like other candidate countries, received generous European pre-accession financial assistance. The combination of three financial instruments in operation at the time – Phare, SAPARD, and ISPA – enabled Poland to make substantial investments in key economic sectors, including public administration, agriculture, environmental protection, and physical infrastructure. The early launch of the Phare program prepared Poland to follow various EU standards and prerequisites, and contributed to the implementation of the cohesion policy. Initiation of assistance within SAPARD and ISPA instruments since 2000 strengthened the rural economy and competitiveness of Polish agriculture, and allowed for modernization of the transportation and environmental infrastructure. In pre-accession assistance, Poland received a total of 5.5 billion euro (over 3% of the 2003 GDP), by far the highest support provided to the candidate countries at the time.

Substantial investments made during the 1990s and early 2000s, largely covered by pre-accession financial aid, had a remarkable impact on the quality of existing infrastructure in Poland. Kilometers of roads were built and renovated in Polish municipalities, thousands of households acquired a connection with the water pipe network, and hundreds of wastewater treatment plants were constructed. This is only a small subset of selected advancements that can be demonstrated using quantitative data collected in a comparable way over time. Numerous other types of infrastructure received substantial investments to support development, modernization or enhancement. On top of that, all these improvements have likely contributed to further spill-over effects through higher levels of regional growth, a boost in the labor market with the creation of new jobs, a reduction of unemployment, or enhanced labor productivity. All these changes, taken together, played a key role in determining the overall quality of life for the Polish population, reducing regional economic inequalities, and improving the quality of the local natural environment, etc.

The distribution of support for Poland’s accession to the EU, as reflected in the 2003 referendum results, differed significantly by region. Enthusiasm for the EU was significantly lower in the eastern parts of the country, while residents of many western municipalities voted overwhelmingly in favor of membership. Yet, even at a very fine geographical distribution, we see only a relatively small group of municipalities – 12.3% – where less than 50% of residents voted in favor of EU membership, and the overall outcome across the country was a decisive “YES”. Thus, although the substantial advancement in infrastructural development all across the country did not convince the majority of residents in each and every locality, the number and geographical scope of those voting in favor was very decisive. It is impossible to say how high/low the support would have been without the received support. Yet, given the scale of the resulting changes in various basic dimensions of quality of life, it seems safe to say that, thanks to the funds, many voters looked at the future integration with a higher degree of appreciation. Naturally, other factors played a role in determining people’s decisions in the referendum, with economic conditions and prospects for socio-economic development being just one factor, albeit a likely important one.

Pre-accession funds in the current candidate countries, how they are used, distributed, and how they change people’s daily lives, will again prove important in showcasing the benefits of integration. At the same time, to secure the kind of support that the Polish population expressed in the 2003 referendum, it will be important to also highlight the broader benefits of integration and address fears and concerns of various population groups.

The experience of Poland and other member countries from Central and Eastern Europe can serve not only as an example of the benefits of pre-accession funds, which we studied in this policy paper. The countries’ socio-economic success and the changes in the quality of life, both before and after accession, should be seen as a clear case of fundamental changes, which would have been highly unlikely had the countries decided to stay out of the European Union.

Acknowledgement

The authors acknowledge the support from the Swedish International Development Cooperation Agency, Sida. We are grateful to Patryk Markowski for his assistance in preparing this analysis and detailed background research.

References

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